The Rise Of Multidimensional Data in HR

Innovative Data Strategies: Leveraging AI For Smarter Enterprise Operations

Aug 14, 2024,10:15am EDT

From Hidden Energy To High Performance: How To Engage Introverts To Optimize Workplace Dynamics”,”scope”:{“topStory”:{“index”:1,”title”:”From Hidden Energy To High Performance: How To Engage Introverts To Optimize Workplace Dynamics”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9eaf2f4db016e24d098c/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”10:15″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723644900000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/from-hidden-energy-to-high-performance-how-to-engage-introverts-to-optimize-workplace-dynamics/”}},”id”:”3cdprf7g2i5000″},{“textContent”:”

Aug 14, 2024,10:00am EDT

ETL (Extract, Transform and Load) Definition: What does ETL mean

The Best Recipes For Human Connection In Healthcare Combine Digital And Analog Ingredients”,”scope”:{“topStory”:{“index”:2,”title”:”The Best Recipes For Human Connection In Healthcare Combine Digital And Analog Ingredients”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9df512367aad52f0b0e5/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”10:00″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723644000000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/the-best-recipes-for-human-connection-in-healthcare-combine-digital-and-analog-ingredients/”}},”id”:”2g9401pdpj3g00″},{“textContent”:”

Aug 14, 2024,09:45am EDT

Overcoming The Challenges Of Using AI Chatbots In Healthcare”,”scope”:{“topStory”:{“index”:3,”title”:”Overcoming The Challenges Of Using AI Chatbots In Healthcare”,”image”:”https://specials-images.forbesimg.com/imageserve/65eb37f10a2278925e9cdb57/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:45″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723643100000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/overcoming-the-challenges-of-using-ai-chatbots-in-healthcare/”}},”id”:”62f7h6f11km000″},{“textContent”:”

Aug 14, 2024,09:30am EDT

Extract, transform, load (ETL) – Azure Architecture Center

Becoming A Multi-Product Business”,”scope”:{“topStory”:{“index”:4,”title”:”Becoming A Multi-Product Business”,”image”:”https://specials-images.forbesimg.com/imageserve/65131d3bcb7a1fc00ce69c3b/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:30″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723642200000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/becoming-a-multi-product-business/”}},”id”:”9em1lk9cd1eo00″},{“textContent”:”

Aug 14, 2024,09:15am EDT

Analytic Trends Reshaping Delivery Optimization In Last-Mile Logistics”,”scope”:{“topStory”:{“index”:5,”title”:”Analytic Trends Reshaping Delivery Optimization In Last-Mile Logistics”,”image”:”https://specials-images.forbesimg.com/imageserve/6671beb282c978843a6a5fb3/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:15″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723641300000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/analytic-trends-reshaping-delivery-optimization-in-last-mile-logistics/”}},”id”:”3i6a864c5hl000″},{“textContent”:”

Aug 14, 2024,09:00am EDT

Understanding Business Intelligence Through Modernizing ETL

Reimagine Customer Experience, Risk And Regulation In Financial Services With AI”,”scope”:{“topStory”:{“index”:6,”title”:”Reimagine Customer Experience, Risk And Regulation In Financial Services With AI”,”image”:”https://specials-images.forbesimg.com/imageserve/63f90facfcef60e108d5759b/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:00″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723640400000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/reimagine-customer-experience-risk-and-regulation-in-financial-services-with-ai/”}},”id”:”40ogl34n020800″},{“textContent”:”

Aug 14, 2024,08:45am EDT

Are AI And BPO Natural Bedfellows?”,”scope”:{“topStory”:{“index”:7,”title”:”Are AI And BPO Natural Bedfellows?”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9ada3d7e765a91bfb70f/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”08:45″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723639500000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/are-ai-and-bpo-natural-bedfellows/”}},”id”:”4652j908q67g00″},{“textContent”:”

Aug 14, 2024,08:30am EDT

What is Business Intelligence (BI): Complete Implementation

Quantifying The ROI Of Generative AI With A Focus On Cost-Efficiency”,”scope”:{“topStory”:{“index”:8,”title”:”Quantifying The ROI Of Generative AI With A Focus On Cost-Efficiency”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9a38819d80a518672939/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”08:30″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723638600000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/quantifying-the-roi-of-generative-ai-with-a-focus-on-cost-efficiency/”}},”id”:”cmeqd98qj7fc00″}],”breakpoints”:[{“breakpoint”:”@media all and (max-width: 767px)”,”config”:{“enabled”:false}},{“breakpoint”:”@media all and (max-width: 768px)”,”config”:{“inView”:2,”slidesToScroll”:1}},{“breakpoint”:”@media all and (min-width: 1681px)”,”config”:{“inView”:6}}]};
Innovative Data Strategies: Leveraging AI For Smarter Enterprise Operations

Aug 14, 2024,10:15am EDT

From Hidden Energy To High Performance: How To Engage Introverts To Optimize Workplace Dynamics”,”scope”:{“topStory”:{“index”:1,”title”:”From Hidden Energy To High Performance: How To Engage Introverts To Optimize Workplace Dynamics”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9eaf2f4db016e24d098c/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”10:15″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723644900000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/from-hidden-energy-to-high-performance-how-to-engage-introverts-to-optimize-workplace-dynamics/”}},”id”:”3cdprf7g2i5000″},{“textContent”:”

Aug 14, 2024,10:00am EDT

ETL Development in Business Intelligence: Overview – Thinklayer

The Best Recipes For Human Connection In Healthcare Combine Digital And Analog Ingredients”,”scope”:{“topStory”:{“index”:2,”title”:”The Best Recipes For Human Connection In Healthcare Combine Digital And Analog Ingredients”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9df512367aad52f0b0e5/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”10:00″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723644000000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/the-best-recipes-for-human-connection-in-healthcare-combine-digital-and-analog-ingredients/”}},”id”:”2g9401pdpj3g00″},{“textContent”:”

Aug 14, 2024,09:45am EDT

Overcoming The Challenges Of Using AI Chatbots In Healthcare”,”scope”:{“topStory”:{“index”:3,”title”:”Overcoming The Challenges Of Using AI Chatbots In Healthcare”,”image”:”https://specials-images.forbesimg.com/imageserve/65eb37f10a2278925e9cdb57/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:45″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723643100000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/overcoming-the-challenges-of-using-ai-chatbots-in-healthcare/”}},”id”:”62f7h6f11km000″},{“textContent”:”

Aug 14, 2024,09:30am EDT

Becoming A Multi-Product Business”,”scope”:{“topStory”:{“index”:4,”title”:”Becoming A Multi-Product Business”,”image”:”https://specials-images.forbesimg.com/imageserve/65131d3bcb7a1fc00ce69c3b/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:30″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723642200000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/becoming-a-multi-product-business/”}},”id”:”9em1lk9cd1eo00″},{“textContent”:”

Aug 14, 2024,09:15am EDT

Analytic Trends Reshaping Delivery Optimization In Last-Mile Logistics”,”scope”:{“topStory”:{“index”:5,”title”:”Analytic Trends Reshaping Delivery Optimization In Last-Mile Logistics”,”image”:”https://specials-images.forbesimg.com/imageserve/6671beb282c978843a6a5fb3/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:15″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723641300000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/analytic-trends-reshaping-delivery-optimization-in-last-mile-logistics/”}},”id”:”3i6a864c5hl000″},{“textContent”:”

Aug 14, 2024,09:00am EDT

Reimagine Customer Experience, Risk And Regulation In Financial Services With AI”,”scope”:{“topStory”:{“index”:6,”title”:”Reimagine Customer Experience, Risk And Regulation In Financial Services With AI”,”image”:”https://specials-images.forbesimg.com/imageserve/63f90facfcef60e108d5759b/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:00″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723640400000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/reimagine-customer-experience-risk-and-regulation-in-financial-services-with-ai/”}},”id”:”40ogl34n020800″},{“textContent”:”

Aug 14, 2024,08:45am EDT

Are AI And BPO Natural Bedfellows?”,”scope”:{“topStory”:{“index”:7,”title”:”Are AI And BPO Natural Bedfellows?”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9ada3d7e765a91bfb70f/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”08:45″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723639500000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/are-ai-and-bpo-natural-bedfellows/”}},”id”:”4652j908q67g00″},{“textContent”:”

Aug 14, 2024,08:30am EDT

Quantifying The ROI Of Generative AI With A Focus On Cost-Efficiency”,”scope”:{“topStory”:{“index”:8,”title”:”Quantifying The ROI Of Generative AI With A Focus On Cost-Efficiency”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9a38819d80a518672939/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”08:30″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723638600000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/quantifying-the-roi-of-generative-ai-with-a-focus-on-cost-efficiency/”}},”id”:”cmeqd98qj7fc00″}],”breakpoints”:[{“breakpoint”:”@media all and (max-width: 767px)”,”config”:{“enabled”:false}},{“breakpoint”:”@media all and (max-width: 768px)”,”config”:{“inView”:2,”slidesToScroll”:1}},{“breakpoint”:”@media all and (min-width: 1681px)”,”config”:{“inView”:6}}]};
Innovative Data Strategies: Leveraging AI For Smarter Enterprise Operations

Aug 14, 2024,10:15am EDT

From Hidden Energy To High Performance: How To Engage Introverts To Optimize Workplace Dynamics”,”scope”:{“topStory”:{“index”:1,”title”:”From Hidden Energy To High Performance: How To Engage Introverts To Optimize Workplace Dynamics”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9eaf2f4db016e24d098c/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”10:15″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723644900000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/from-hidden-energy-to-high-performance-how-to-engage-introverts-to-optimize-workplace-dynamics/”}},”id”:”1e2kkfndmnmq00″},{“textContent”:”

Aug 14, 2024,10:00am EDT

The Best Recipes For Human Connection In Healthcare Combine Digital And Analog Ingredients”,”scope”:{“topStory”:{“index”:2,”title”:”The Best Recipes For Human Connection In Healthcare Combine Digital And Analog Ingredients”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9df512367aad52f0b0e5/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”10:00″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723644000000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/the-best-recipes-for-human-connection-in-healthcare-combine-digital-and-analog-ingredients/”}},”id”:”11c0o135oo2280″},{“textContent”:”

Aug 14, 2024,09:45am EDT

Overcoming The Challenges Of Using AI Chatbots In Healthcare”,”scope”:{“topStory”:{“index”:3,”title”:”Overcoming The Challenges Of Using AI Chatbots In Healthcare”,”image”:”https://specials-images.forbesimg.com/imageserve/65eb37f10a2278925e9cdb57/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:45″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723643100000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/overcoming-the-challenges-of-using-ai-chatbots-in-healthcare/”}},”id”:”7b3h8l7a6bl400″},{“textContent”:”

Aug 14, 2024,09:30am EDT

Becoming A Multi-Product Business”,”scope”:{“topStory”:{“index”:4,”title”:”Becoming A Multi-Product Business”,”image”:”https://specials-images.forbesimg.com/imageserve/65131d3bcb7a1fc00ce69c3b/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:30″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723642200000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/becoming-a-multi-product-business/”}},”id”:”k3o1dqc25cq80″},{“textContent”:”

Aug 14, 2024,09:15am EDT

Analytic Trends Reshaping Delivery Optimization In Last-Mile Logistics”,”scope”:{“topStory”:{“index”:5,”title”:”Analytic Trends Reshaping Delivery Optimization In Last-Mile Logistics”,”image”:”https://specials-images.forbesimg.com/imageserve/6671beb282c978843a6a5fb3/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:15″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723641300000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/analytic-trends-reshaping-delivery-optimization-in-last-mile-logistics/”}},”id”:”1qbhbq57316m00″},{“textContent”:”

Aug 14, 2024,09:00am EDT

Reimagine Customer Experience, Risk And Regulation In Financial Services With AI”,”scope”:{“topStory”:{“index”:6,”title”:”Reimagine Customer Experience, Risk And Regulation In Financial Services With AI”,”image”:”https://specials-images.forbesimg.com/imageserve/63f90facfcef60e108d5759b/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”09:00″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723640400000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/reimagine-customer-experience-risk-and-regulation-in-financial-services-with-ai/”}},”id”:”e8hhcl672g5k00″},{“textContent”:”

Aug 14, 2024,08:45am EDT

Are AI And BPO Natural Bedfellows?”,”scope”:{“topStory”:{“index”:7,”title”:”Are AI And BPO Natural Bedfellows?”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9ada3d7e765a91bfb70f/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”08:45″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723639500000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/are-ai-and-bpo-natural-bedfellows/”}},”id”:”2ofd0q1jccc800″},{“textContent”:”

Aug 14, 2024,08:30am EDT

Quantifying The ROI Of Generative AI With A Focus On Cost-Efficiency”,”scope”:{“topStory”:{“index”:8,”title”:”Quantifying The ROI Of Generative AI With A Focus On Cost-Efficiency”,”image”:”https://specials-images.forbesimg.com/imageserve/66bb9a38819d80a518672939/290×0.jpg”,”isHappeningNowArticle”:false,”date”:{“monthDayYear”:”Aug 14, 2024″,”hourMinute”:”08:30″,”amPm”:”am”,”isEDT”:true,”unformattedDate”:1723638600000},”uri”:”https://www.forbes.com/councils/forbestechcouncil/2024/08/14/quantifying-the-roi-of-generative-ai-with-a-focus-on-cost-efficiency/”}},”id”:”36c3imn2b65o00″}],”breakpoints”:[{“breakpoint”:”@media all and (max-width: 767px)”,”config”:{“enabled”:false}},{“breakpoint”:”@media all and (max-width: 768px)”,”config”:{“inView”:2,”slidesToScroll”:1}},{“breakpoint”:”@media all and (min-width: 1681px)”,”config”:{“inView”:6}}]};
How to use MS Excel’s powerful business intelligence tools

Excel has evolved into a robust platform for data analysis and reporting, thanks to its advanced business intelligence tools: Power Query, Power Pivot, Data Model, and DAX. These powerful features can streamline your data workflows, making them more efficient and less time-consuming. In this guide, we’ll explore how to leverage these tools to create a comprehensive sales report for a fictional company, Maven Electronics, using data from various sources.

Excel : Learn Power Query, Power Pivot & DAX

By following the step-by-step guide outlined in this guide, you can harness the power of Excel to create a fictional comprehensive sales report for a company. However the principles and techniques discussed here can be applied to a wide range of data analysis scenarios, making Excel an indispensable tool in your data toolkit.

Key Takeaways :

Excel’s advanced business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—can revolutionize data analysis and reporting processes. Power Query is essential for data extraction, transformation, and loading (ETL), connecting to various data sources and cleaning data. Power Pivot enables exploration and summarization of data, allowing for complex data models and advanced calculations using DAX. Data Model helps create and manage relationships between tables, integrating data from multiple sources for comprehensive analyses. DAX is a formula language used in Power Pivot for advanced data calculations and metrics, enabling sophisticated data analysis. Understanding the Key Tools

Before diving into the practical application, let’s take a closer look at each of these essential tools:

Power Query: This tool is indispensable for data extraction, transformation, and loading (ETL). It enables you to connect to a wide range of data sources, clean and transform the data, and load it into Excel for further analysis. Power Query’s intuitive interface and powerful features make it a go-to tool for data professionals. Power Pivot: Power Pivot empowers you to explore and summarize your data effectively. It allows you to create complex data models and perform advanced calculations using DAX (Data Analysis Expressions). With Power Pivot, you can handle large datasets without the limitations of traditional Excel spreadsheets. Data Model: The Data Model is crucial for creating and managing relationships between tables. It enables you to integrate data from multiple sources seamlessly and perform comprehensive analyses. By establishing relationships between tables using primary and foreign keys, you can ensure data integrity and accuracy. DAX: DAX is a powerful formula language used in Power Pivot for advanced data calculations and metrics. It allows you to create calculated columns and measures, allowing sophisticated data analysis. With DAX, you can perform complex calculations, such as time intelligence and iterative functions, to gain deeper insights into your data.

Here are a selection of other articles from our extensive library of content you may find of interest on the subject of improving your skills with Microsoft Excel spreadsheets :

Creating a Sales Report: Step-by-Step Guide

Now, let’s walk through the process of creating a sales report for Maven Electronics’ regional managers. In this scenario, the data comes from a SQL database, a CSV file, and a PDF file. We’ll demonstrate how to use Excel’s business intelligence tools to tackle this task efficiently.

1: Harnessing the Power of Power Query

Begin by using Power Query to connect to your data sources. Power Query’s ETL capabilities allow you to extract data from the SQL database, CSV file, and PDF file effortlessly. Once the data is loaded, you can leverage Power Query’s transformation features to clean and shape the data according to your analysis requirements. By automating repetitive tasks using workflows and ensuring data quality through data profiling and quality checks, you can streamline the data preparation process.

2: Constructing the Data Model

With the data prepared, the next step is to build the Data Model. This involves creating relationships between tables using primary and foreign keys. The Data Model ensures accurate data integration and enables you to perform analyses across multiple data sources. Power Pivot’s ability to handle large datasets without row limitations makes it an ideal tool for managing extensive data.

3: Exploring and Summarizing Data with Pivot Tables and Charts

Once the Data Model is in place, Power Pivot becomes your playground for exploring and summarizing the data. Its user-friendly drag-and-drop interface allows you to create pivot tables effortlessly. By integrating multiple data tables, you can gain a comprehensive view of the sales data. Pivot charts provide a visual representation of the data, making it easier to identify trends, patterns, and outliers.

4: Unleashing the Power of DAX for Advanced Calculations

DAX is the secret weapon for defining calculated columns and measures in your sales report. With DAX, you can create measures for key metrics such as Total Orders and Total Revenue. DAX’s iterator functions enable you to perform complex calculations, such as calculating year-over-year growth or identifying the top-selling products. By leveraging DAX, you can uncover valuable insights that might otherwise remain hidden in the data.

5: Finalizing the Report with Interactive Visualizations

To make your sales report truly impactful, incorporate data visualizations that present the information in a clear and engaging manner. Create interactive dashboards that allow regional managers to explore the data dynamically. Use slicers to enable dynamic filtering, empowering users to drill down into specific regions, time periods, or product categories. By making the report user-friendly and interactive, you encourage data-driven decision-making and collaboration.

Excel’s business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—are catalysts for data professionals. By mastering these tools, you can significantly enhance your data analysis and reporting capabilities. The ability to integrate data from multiple sources, perform advanced calculations, and create interactive visualizations empowers you to derive meaningful insights and drive better business decisions. If you need further information on using MS Excel jump over to the official Microsoft Support website.

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Talent Intelligence: Unlocking The Power Of Multidimensional Data

Joanna Riley, CEO & cofounder of Censia. Striving for a more just and efficient global economy through better talent data and technology.

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In the age of data-driven decision-making, the significance of structured, multidimensional data cannot be overstated. This data type forms the backbone of advanced AI systems, facilitating nuanced insights and predictive analytics essential for modern business strategies, including talent management.

Data-Driven Recruiting And Talent Management

Companies that harness data in talent management have seen remarkable improvements in both efficiency and insights into workforce dynamics. For instance, incorporating data-driven strategies in recruiting has been shown to significantly enhance the quality of the workforce, increase productivity, and support unbiased hiring decisions. Workable’s comprehensive guide on data-driven recruiting emphasizes the importance of choosing the right data and metrics, collecting data efficiently, and acting on this data to improve hiring processes.

The Rise Of Multidimensional Data in HR

Multidimensional data isn’t a new concept. Most business intelligence (finance, consumer behavior, etc.) relies on structured data across multiple dimensions to gain profound insight and determine future strategy. HR has always been the big exception because HR has traditionally been one-dimensional (a linear resume of qualifications matched to a linear list of job requirements), often inaccurate or messy (outdated profiles, multiple job titles meaning similar things, etc.), and limited only the candidate and the role—not, for instance, other important factors such as the industry or the organization.

By cleaning and structuring this talent data and introducing new layers of information (company size, revenue levels, company events, industry and more), the insight that AI can derive from this data grows immensely.

The deployment of structured, multidimensional data in talent management allows organizations to gain a deep and holistic understanding of their workforce, encompassing diverse dimensions such as people, jobs, skills, and industries. This comprehensive dataset supports AI-driven solutions, enabling organizations to navigate complexities with precision and agility. MyHRfuture highlights how data-driven HR impacts recruitment and talent management by measuring key talent acquisition data points for greater impact, supporting workforce planning, and facilitating training and development.

Inferring Skills And Bridging Gaps

The capacity of structured data to infer skills is invaluable in talent acquisition and workforce planning, where accurate skill assessment is crucial. Analyzing patterns and contextual information allows AI-powered systems to uncover latent skills, providing a broader understanding of individuals’ capabilities.

Transformative Impact Of AI In Talent Management

The convergence of structured data and AI heralds a new era in talent management, with organizations increasingly turning to AI-driven solutions to streamline processes and decision-making. Korn Ferry’s insights into the telecom sector, for example, reveal the critical role of strategy and talent in organizational success, emphasizing the importance of learning agility as a predictor of long-term leadership potential.

To further underscore the transformative power of data in talent management, it’s essential to recognize the nuanced ways in which organizations leverage this data to foster a culture of continuous learning and adaptability. A data-driven approach streamlines recruitment and talent development and underpins strategic workforce planning and development initiatives. According to research by Deloitte, integrating data analytics into HR practices enables organizations to forecast talent needs, identify skill gaps, and optimize resource allocation more effectively. This strategic alignment ensures that talent management efforts are about filling positions and building a resilient, skilled workforce capable of driving long-term business growth.

Moreover, adopting AI and data analytics in talent management extends beyond operational efficiency to enhancing the employee experience. Organizations can address individual career aspirations and skill development needs by personalizing learning and development opportunities, thereby increasing engagement and retention. This personalized approach, grounded in data, signifies a shift from traditional, one-size-fits-all HR practices to more dynamic, responsive strategies that value and cultivate individual talent.

In this rapidly evolving landscape, harnessing and interpreting multidimensional data becomes a critical competitive advantage, enabling organizations to navigate the complexities of the modern workforce with agility and insight.

Common Pitfalls When Adopting Talent Intelligence

Several common pitfalls occur when organizations adopt this type of technology. The first is that system implementations are prone to failure. According to a Deloitte study, 70% of digital transformation efforts are considered less than successful, and organizations require three years to start competing in digital markets. Working with APIs or native integrations to upgrade current systems is one way to avoid the financial, time and engagement loss caused by this.

The other big pitfall is not understanding the data well enough. It is essential to ask how the data is collected, cleaned and structured. If a provider runs new algorithms on old data or limited source data, you’ll get biased and unreliable results.

And finally, you’ll want to understand the legal restrictions you might face in your field. Several regions have already restricted the use of AI in HR decision-making, so you’ll want to make sure that you deploy it in a way that assists, not replaces, your team and their decisions.

Embracing A Data-Driven Future

As organizations undergo digital transformation, the importance of leveraging structured, multidimensional data and AI will continue to grow. McKinsey’s guide on building a data-driven strategy highlights the need for an integrated approach to data sourcing, model building, and organizational transformation tailored to the company’s desired business impact.

In conclusion, structured, multidimensional data is the cornerstone of AI-driven talent management, enabling organizations to unlock insights, optimize processes, and drive strategic outcomes. By leveraging advanced analytics and AI technologies, organizations can chart a course toward a data-driven future where talent becomes a true differentiator in driving business success.

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How to use MS Excel’s powerful business intelligence tools

Excel has evolved into a robust platform for data analysis and reporting, thanks to its advanced business intelligence tools: Power Query, Power Pivot, Data Model, and DAX. These powerful features can streamline your data workflows, making them more efficient and less time-consuming. In this guide, we’ll explore how to leverage these tools to create a comprehensive sales report for a fictional company, Maven Electronics, using data from various sources.

Excel : Learn Power Query, Power Pivot & DAX

By following the step-by-step guide outlined in this guide, you can harness the power of Excel to create a fictional comprehensive sales report for a company. However the principles and techniques discussed here can be applied to a wide range of data analysis scenarios, making Excel an indispensable tool in your data toolkit.

Key Takeaways :

Excel’s advanced business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—can revolutionize data analysis and reporting processes. Power Query is essential for data extraction, transformation, and loading (ETL), connecting to various data sources and cleaning data. Power Pivot enables exploration and summarization of data, allowing for complex data models and advanced calculations using DAX. Data Model helps create and manage relationships between tables, integrating data from multiple sources for comprehensive analyses. DAX is a formula language used in Power Pivot for advanced data calculations and metrics, enabling sophisticated data analysis. Understanding the Key Tools

Before diving into the practical application, let’s take a closer look at each of these essential tools:

Power Query: This tool is indispensable for data extraction, transformation, and loading (ETL). It enables you to connect to a wide range of data sources, clean and transform the data, and load it into Excel for further analysis. Power Query’s intuitive interface and powerful features make it a go-to tool for data professionals. Power Pivot: Power Pivot empowers you to explore and summarize your data effectively. It allows you to create complex data models and perform advanced calculations using DAX (Data Analysis Expressions). With Power Pivot, you can handle large datasets without the limitations of traditional Excel spreadsheets. Data Model: The Data Model is crucial for creating and managing relationships between tables. It enables you to integrate data from multiple sources seamlessly and perform comprehensive analyses. By establishing relationships between tables using primary and foreign keys, you can ensure data integrity and accuracy. DAX: DAX is a powerful formula language used in Power Pivot for advanced data calculations and metrics. It allows you to create calculated columns and measures, allowing sophisticated data analysis. With DAX, you can perform complex calculations, such as time intelligence and iterative functions, to gain deeper insights into your data.

Here are a selection of other articles from our extensive library of content you may find of interest on the subject of improving your skills with Microsoft Excel spreadsheets :

Creating a Sales Report: Step-by-Step Guide

Now, let’s walk through the process of creating a sales report for Maven Electronics’ regional managers. In this scenario, the data comes from a SQL database, a CSV file, and a PDF file. We’ll demonstrate how to use Excel’s business intelligence tools to tackle this task efficiently.

1: Harnessing the Power of Power Query

Begin by using Power Query to connect to your data sources. Power Query’s ETL capabilities allow you to extract data from the SQL database, CSV file, and PDF file effortlessly. Once the data is loaded, you can leverage Power Query’s transformation features to clean and shape the data according to your analysis requirements. By automating repetitive tasks using workflows and ensuring data quality through data profiling and quality checks, you can streamline the data preparation process.

2: Constructing the Data Model

With the data prepared, the next step is to build the Data Model. This involves creating relationships between tables using primary and foreign keys. The Data Model ensures accurate data integration and enables you to perform analyses across multiple data sources. Power Pivot’s ability to handle large datasets without row limitations makes it an ideal tool for managing extensive data.

3: Exploring and Summarizing Data with Pivot Tables and Charts

Once the Data Model is in place, Power Pivot becomes your playground for exploring and summarizing the data. Its user-friendly drag-and-drop interface allows you to create pivot tables effortlessly. By integrating multiple data tables, you can gain a comprehensive view of the sales data. Pivot charts provide a visual representation of the data, making it easier to identify trends, patterns, and outliers.

4: Unleashing the Power of DAX for Advanced Calculations

DAX is the secret weapon for defining calculated columns and measures in your sales report. With DAX, you can create measures for key metrics such as Total Orders and Total Revenue. DAX’s iterator functions enable you to perform complex calculations, such as calculating year-over-year growth or identifying the top-selling products. By leveraging DAX, you can uncover valuable insights that might otherwise remain hidden in the data.

5: Finalizing the Report with Interactive Visualizations

To make your sales report truly impactful, incorporate data visualizations that present the information in a clear and engaging manner. Create interactive dashboards that allow regional managers to explore the data dynamically. Use slicers to enable dynamic filtering, empowering users to drill down into specific regions, time periods, or product categories. By making the report user-friendly and interactive, you encourage data-driven decision-making and collaboration.

Excel’s business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—are catalysts for data professionals. By mastering these tools, you can significantly enhance your data analysis and reporting capabilities. The ability to integrate data from multiple sources, perform advanced calculations, and create interactive visualizations empowers you to derive meaningful insights and drive better business decisions. If you need further information on using MS Excel jump over to the official Microsoft Support website.

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Transforming Your Organization with the Power of Business Intelligence

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With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.

Understanding Business Intelligence

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.

The Four Pillars of Business Intelligence

Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.

Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.

Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.

Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.

The Transformative Impact of Business Intelligence Improved Decision Making

BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.

Operational Efficiency

The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.

Improved Bottom Line

Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.

Competitive Advantage

Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.

Ethical Considerations in BI

The Future of Business Intelligence

Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.

Conclusion

Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.

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Business Intelligence Market worth USD 56,200.9 million by 2033 – Exclusive Report by Future Market Insights, Inc.

The global business intelligence market size is predicted to surpass a valuation of US$ 28,216.8 million in 2023. It is anticipated to hit a valuation of US$ 56,200.9 million by 2033. The market is projected to thrive at a CAGR of 7.1% from 2023 to 2033.

The capabilities of business intelligence systems have been considerably improved by ongoing technological breakthroughs. Such as in cloud computing, big data analytics, artificial intelligence, and machine learning. Scalability, flexibility, and affordability are all features of cloud-based BI solutions that enable BI to be used by businesses of various sizes.

More advanced data analysis and predictive modeling are possible by AI-powered analytics tools and machine learning algorithms, enabling firms to find important patterns and insights.

Organizations are aware that successfully utilizing data may provide them with a competitive advantage. Businesses may acquire a greater knowledge of their customers, markets, and operations by utilizing business intelligence tools to find hidden patterns, trends, and correlations in their data. These insights may be utilized to improve consumer experiences, find new market possibilities, optimize corporate strategy, and spur innovation.

Self-service analytics are now supported by business intelligence platforms, enabling users to access and evaluate data without relying heavily on IT or data analysts. Self-service BI technologies allow non-technical people to independently examine data, produce reports, and develop insights due to their easy user interfaces, drag-and-drop capabilities, and visualizations. Within enterprises, this movement has democratized data analytics and increased the user base of business intelligence.

The business intelligence system’s more up-to-date sophisticated analytics and improved statistical support are also contributing to the market’s expansion. Business intelligence technologies and machine learning aid corporate settings in problem-solving strategies and forecasting potential outcomes.

Additionally, this aids in streamlining internal corporate operations, boosting revenue development, and connecting technology. To improve processing, giving businesses an advantage over rival brands, thereby surging Business Intelligence market growth consistently.

Key Takeaways:

The global business intelligence market size expanded at a CAGR of 5.0% from 2018 to 2022. In 2018, the global market size stood at US$ 21,962.1 million. The market size stood at US$ 26,745.8 million in 2022. In 2022, the solution segment captured 68.9% of market shares. The sales and marketing segment captured 42.3% shares in the global market. In 2022, the United States captured 19.4% shares in the global market. China held 8.3% shares in the global business intelligence industry in 2022. In 2022, the United Kingdom captured 6.7% shares in the global market.

Key Players:

IBM Oracle Microsoft SAP Google

Recent Developments Observed:

Ramp announced its ambitions to provide new artificial intelligence technologies in May 2023. The business plans to introduce the new tools with a function that might ascertain whether a firm has overpaid for its software contracts. SoftLedger debuted a business intelligence dashboard with real-time data in December 2022. The purpose of this publication is to assist Chief Financial Officers (CFOs) in making tactical decisions for their company.

Market Segmentation:

By Component:

Solution Dashboards and Scorecards Data Integration and ETL Reporting and Visualization Query and Analysis Service Consulting Services Deployment and Integration Services Support and Maintenance Services

By Organization Size:

By Business Function:

Human Resources Finance Operations Sales and Marketing

By Vertical:

Retail Manufacturing Government and Public Services Media Entertainment Transportation and Logistics BFSI Telecom and IT Healthcare and Hospitality

By Deployment:

By Region:

North America Latin America Europe East Asia South Asia Oceania The Middle East & Africa (MEA)

Elevate Your Business Strategy! Purchase the Report for Market-Driven Insights

About Future Market Insights (FMI)

Future Market Insights, Inc. (ESOMAR certified, recipient of the Stevie Award, and a member of the Greater New York Chamber of Commerce) offers profound insights into the driving factors that are boosting demand in the market. FMI stands as the leading global provider of market intelligence, advisory services, consulting, and events for the Packaging, Food and Beverage, Consumer Technology, Healthcare, Industrial, and Chemicals markets. With a vast team of over 400 analysts worldwide, FMI provides global, regional, and local expertise on diverse domains and industry trends across more than 110 countries. Join us as we commemorate 10 years of delivering trusted market insights. Reflecting on a decade of achievements, we continue to lead with integrity, innovation, and expertise.

Contact Us:

Future Market Insights Inc.Christiana Corporate, 200 Continental Drive,Suite 401, Newark, Delaware – 19713, USAT: +1-845-579-5705For Sales Enquiries: sales@futuremarketinsights.comWebsite: https://www.futuremarketinsights.comLinkedIn| Twitter| Blogs | YouTube

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How to use MS Excel’s powerful business intelligence tools

Excel has evolved into a robust platform for data analysis and reporting, thanks to its advanced business intelligence tools: Power Query, Power Pivot, Data Model, and DAX. These powerful features can streamline your data workflows, making them more efficient and less time-consuming. In this guide, we’ll explore how to leverage these tools to create a comprehensive sales report for a fictional company, Maven Electronics, using data from various sources.

Excel : Learn Power Query, Power Pivot & DAX

By following the step-by-step guide outlined in this guide, you can harness the power of Excel to create a fictional comprehensive sales report for a company. However the principles and techniques discussed here can be applied to a wide range of data analysis scenarios, making Excel an indispensable tool in your data toolkit.

Key Takeaways :

Excel’s advanced business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—can revolutionize data analysis and reporting processes. Power Query is essential for data extraction, transformation, and loading (ETL), connecting to various data sources and cleaning data. Power Pivot enables exploration and summarization of data, allowing for complex data models and advanced calculations using DAX. Data Model helps create and manage relationships between tables, integrating data from multiple sources for comprehensive analyses. DAX is a formula language used in Power Pivot for advanced data calculations and metrics, enabling sophisticated data analysis. Understanding the Key Tools

Before diving into the practical application, let’s take a closer look at each of these essential tools:

Power Query: This tool is indispensable for data extraction, transformation, and loading (ETL). It enables you to connect to a wide range of data sources, clean and transform the data, and load it into Excel for further analysis. Power Query’s intuitive interface and powerful features make it a go-to tool for data professionals. Power Pivot: Power Pivot empowers you to explore and summarize your data effectively. It allows you to create complex data models and perform advanced calculations using DAX (Data Analysis Expressions). With Power Pivot, you can handle large datasets without the limitations of traditional Excel spreadsheets. Data Model: The Data Model is crucial for creating and managing relationships between tables. It enables you to integrate data from multiple sources seamlessly and perform comprehensive analyses. By establishing relationships between tables using primary and foreign keys, you can ensure data integrity and accuracy. DAX: DAX is a powerful formula language used in Power Pivot for advanced data calculations and metrics. It allows you to create calculated columns and measures, allowing sophisticated data analysis. With DAX, you can perform complex calculations, such as time intelligence and iterative functions, to gain deeper insights into your data.

Here are a selection of other articles from our extensive library of content you may find of interest on the subject of improving your skills with Microsoft Excel spreadsheets :

Creating a Sales Report: Step-by-Step Guide

Now, let’s walk through the process of creating a sales report for Maven Electronics’ regional managers. In this scenario, the data comes from a SQL database, a CSV file, and a PDF file. We’ll demonstrate how to use Excel’s business intelligence tools to tackle this task efficiently.

1: Harnessing the Power of Power Query

Begin by using Power Query to connect to your data sources. Power Query’s ETL capabilities allow you to extract data from the SQL database, CSV file, and PDF file effortlessly. Once the data is loaded, you can leverage Power Query’s transformation features to clean and shape the data according to your analysis requirements. By automating repetitive tasks using workflows and ensuring data quality through data profiling and quality checks, you can streamline the data preparation process.

2: Constructing the Data Model

With the data prepared, the next step is to build the Data Model. This involves creating relationships between tables using primary and foreign keys. The Data Model ensures accurate data integration and enables you to perform analyses across multiple data sources. Power Pivot’s ability to handle large datasets without row limitations makes it an ideal tool for managing extensive data.

3: Exploring and Summarizing Data with Pivot Tables and Charts

Once the Data Model is in place, Power Pivot becomes your playground for exploring and summarizing the data. Its user-friendly drag-and-drop interface allows you to create pivot tables effortlessly. By integrating multiple data tables, you can gain a comprehensive view of the sales data. Pivot charts provide a visual representation of the data, making it easier to identify trends, patterns, and outliers.

4: Unleashing the Power of DAX for Advanced Calculations

DAX is the secret weapon for defining calculated columns and measures in your sales report. With DAX, you can create measures for key metrics such as Total Orders and Total Revenue. DAX’s iterator functions enable you to perform complex calculations, such as calculating year-over-year growth or identifying the top-selling products. By leveraging DAX, you can uncover valuable insights that might otherwise remain hidden in the data.

5: Finalizing the Report with Interactive Visualizations

To make your sales report truly impactful, incorporate data visualizations that present the information in a clear and engaging manner. Create interactive dashboards that allow regional managers to explore the data dynamically. Use slicers to enable dynamic filtering, empowering users to drill down into specific regions, time periods, or product categories. By making the report user-friendly and interactive, you encourage data-driven decision-making and collaboration.

Excel’s business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—are catalysts for data professionals. By mastering these tools, you can significantly enhance your data analysis and reporting capabilities. The ability to integrate data from multiple sources, perform advanced calculations, and create interactive visualizations empowers you to derive meaningful insights and drive better business decisions. If you need further information on using MS Excel jump over to the official Microsoft Support website.

Video Credit: Source

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Talent Intelligence: Unlocking The Power Of Multidimensional Data

Joanna Riley, CEO & cofounder of Censia. Striving for a more just and efficient global economy through better talent data and technology.

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In the age of data-driven decision-making, the significance of structured, multidimensional data cannot be overstated. This data type forms the backbone of advanced AI systems, facilitating nuanced insights and predictive analytics essential for modern business strategies, including talent management.

Data-Driven Recruiting And Talent Management

Companies that harness data in talent management have seen remarkable improvements in both efficiency and insights into workforce dynamics. For instance, incorporating data-driven strategies in recruiting has been shown to significantly enhance the quality of the workforce, increase productivity, and support unbiased hiring decisions. Workable’s comprehensive guide on data-driven recruiting emphasizes the importance of choosing the right data and metrics, collecting data efficiently, and acting on this data to improve hiring processes.

The Rise Of Multidimensional Data in HR

Multidimensional data isn’t a new concept. Most business intelligence (finance, consumer behavior, etc.) relies on structured data across multiple dimensions to gain profound insight and determine future strategy. HR has always been the big exception because HR has traditionally been one-dimensional (a linear resume of qualifications matched to a linear list of job requirements), often inaccurate or messy (outdated profiles, multiple job titles meaning similar things, etc.), and limited only the candidate and the role—not, for instance, other important factors such as the industry or the organization.

By cleaning and structuring this talent data and introducing new layers of information (company size, revenue levels, company events, industry and more), the insight that AI can derive from this data grows immensely.

The deployment of structured, multidimensional data in talent management allows organizations to gain a deep and holistic understanding of their workforce, encompassing diverse dimensions such as people, jobs, skills, and industries. This comprehensive dataset supports AI-driven solutions, enabling organizations to navigate complexities with precision and agility. MyHRfuture highlights how data-driven HR impacts recruitment and talent management by measuring key talent acquisition data points for greater impact, supporting workforce planning, and facilitating training and development.

Inferring Skills And Bridging Gaps

The capacity of structured data to infer skills is invaluable in talent acquisition and workforce planning, where accurate skill assessment is crucial. Analyzing patterns and contextual information allows AI-powered systems to uncover latent skills, providing a broader understanding of individuals’ capabilities.

Transformative Impact Of AI In Talent Management

The convergence of structured data and AI heralds a new era in talent management, with organizations increasingly turning to AI-driven solutions to streamline processes and decision-making. Korn Ferry’s insights into the telecom sector, for example, reveal the critical role of strategy and talent in organizational success, emphasizing the importance of learning agility as a predictor of long-term leadership potential.

To further underscore the transformative power of data in talent management, it’s essential to recognize the nuanced ways in which organizations leverage this data to foster a culture of continuous learning and adaptability. A data-driven approach streamlines recruitment and talent development and underpins strategic workforce planning and development initiatives. According to research by Deloitte, integrating data analytics into HR practices enables organizations to forecast talent needs, identify skill gaps, and optimize resource allocation more effectively. This strategic alignment ensures that talent management efforts are about filling positions and building a resilient, skilled workforce capable of driving long-term business growth.

Moreover, adopting AI and data analytics in talent management extends beyond operational efficiency to enhancing the employee experience. Organizations can address individual career aspirations and skill development needs by personalizing learning and development opportunities, thereby increasing engagement and retention. This personalized approach, grounded in data, signifies a shift from traditional, one-size-fits-all HR practices to more dynamic, responsive strategies that value and cultivate individual talent.

In this rapidly evolving landscape, harnessing and interpreting multidimensional data becomes a critical competitive advantage, enabling organizations to navigate the complexities of the modern workforce with agility and insight.

Common Pitfalls When Adopting Talent Intelligence

Several common pitfalls occur when organizations adopt this type of technology. The first is that system implementations are prone to failure. According to a Deloitte study, 70% of digital transformation efforts are considered less than successful, and organizations require three years to start competing in digital markets. Working with APIs or native integrations to upgrade current systems is one way to avoid the financial, time and engagement loss caused by this.

The other big pitfall is not understanding the data well enough. It is essential to ask how the data is collected, cleaned and structured. If a provider runs new algorithms on old data or limited source data, you’ll get biased and unreliable results.

And finally, you’ll want to understand the legal restrictions you might face in your field. Several regions have already restricted the use of AI in HR decision-making, so you’ll want to make sure that you deploy it in a way that assists, not replaces, your team and their decisions.

Embracing A Data-Driven Future

As organizations undergo digital transformation, the importance of leveraging structured, multidimensional data and AI will continue to grow. McKinsey’s guide on building a data-driven strategy highlights the need for an integrated approach to data sourcing, model building, and organizational transformation tailored to the company’s desired business impact.

In conclusion, structured, multidimensional data is the cornerstone of AI-driven talent management, enabling organizations to unlock insights, optimize processes, and drive strategic outcomes. By leveraging advanced analytics and AI technologies, organizations can chart a course toward a data-driven future where talent becomes a true differentiator in driving business success.

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How to use MS Excel’s powerful business intelligence tools

Excel has evolved into a robust platform for data analysis and reporting, thanks to its advanced business intelligence tools: Power Query, Power Pivot, Data Model, and DAX. These powerful features can streamline your data workflows, making them more efficient and less time-consuming. In this guide, we’ll explore how to leverage these tools to create a comprehensive sales report for a fictional company, Maven Electronics, using data from various sources.

Excel : Learn Power Query, Power Pivot & DAX

By following the step-by-step guide outlined in this guide, you can harness the power of Excel to create a fictional comprehensive sales report for a company. However the principles and techniques discussed here can be applied to a wide range of data analysis scenarios, making Excel an indispensable tool in your data toolkit.

Key Takeaways :

Excel’s advanced business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—can revolutionize data analysis and reporting processes. Power Query is essential for data extraction, transformation, and loading (ETL), connecting to various data sources and cleaning data. Power Pivot enables exploration and summarization of data, allowing for complex data models and advanced calculations using DAX. Data Model helps create and manage relationships between tables, integrating data from multiple sources for comprehensive analyses. DAX is a formula language used in Power Pivot for advanced data calculations and metrics, enabling sophisticated data analysis. Understanding the Key Tools

Before diving into the practical application, let’s take a closer look at each of these essential tools:

Power Query: This tool is indispensable for data extraction, transformation, and loading (ETL). It enables you to connect to a wide range of data sources, clean and transform the data, and load it into Excel for further analysis. Power Query’s intuitive interface and powerful features make it a go-to tool for data professionals. Power Pivot: Power Pivot empowers you to explore and summarize your data effectively. It allows you to create complex data models and perform advanced calculations using DAX (Data Analysis Expressions). With Power Pivot, you can handle large datasets without the limitations of traditional Excel spreadsheets. Data Model: The Data Model is crucial for creating and managing relationships between tables. It enables you to integrate data from multiple sources seamlessly and perform comprehensive analyses. By establishing relationships between tables using primary and foreign keys, you can ensure data integrity and accuracy. DAX: DAX is a powerful formula language used in Power Pivot for advanced data calculations and metrics. It allows you to create calculated columns and measures, allowing sophisticated data analysis. With DAX, you can perform complex calculations, such as time intelligence and iterative functions, to gain deeper insights into your data.

Here are a selection of other articles from our extensive library of content you may find of interest on the subject of improving your skills with Microsoft Excel spreadsheets :

Creating a Sales Report: Step-by-Step Guide

Now, let’s walk through the process of creating a sales report for Maven Electronics’ regional managers. In this scenario, the data comes from a SQL database, a CSV file, and a PDF file. We’ll demonstrate how to use Excel’s business intelligence tools to tackle this task efficiently.

1: Harnessing the Power of Power Query

Begin by using Power Query to connect to your data sources. Power Query’s ETL capabilities allow you to extract data from the SQL database, CSV file, and PDF file effortlessly. Once the data is loaded, you can leverage Power Query’s transformation features to clean and shape the data according to your analysis requirements. By automating repetitive tasks using workflows and ensuring data quality through data profiling and quality checks, you can streamline the data preparation process.

2: Constructing the Data Model

With the data prepared, the next step is to build the Data Model. This involves creating relationships between tables using primary and foreign keys. The Data Model ensures accurate data integration and enables you to perform analyses across multiple data sources. Power Pivot’s ability to handle large datasets without row limitations makes it an ideal tool for managing extensive data.

3: Exploring and Summarizing Data with Pivot Tables and Charts

Once the Data Model is in place, Power Pivot becomes your playground for exploring and summarizing the data. Its user-friendly drag-and-drop interface allows you to create pivot tables effortlessly. By integrating multiple data tables, you can gain a comprehensive view of the sales data. Pivot charts provide a visual representation of the data, making it easier to identify trends, patterns, and outliers.

4: Unleashing the Power of DAX for Advanced Calculations

DAX is the secret weapon for defining calculated columns and measures in your sales report. With DAX, you can create measures for key metrics such as Total Orders and Total Revenue. DAX’s iterator functions enable you to perform complex calculations, such as calculating year-over-year growth or identifying the top-selling products. By leveraging DAX, you can uncover valuable insights that might otherwise remain hidden in the data.

5: Finalizing the Report with Interactive Visualizations

To make your sales report truly impactful, incorporate data visualizations that present the information in a clear and engaging manner. Create interactive dashboards that allow regional managers to explore the data dynamically. Use slicers to enable dynamic filtering, empowering users to drill down into specific regions, time periods, or product categories. By making the report user-friendly and interactive, you encourage data-driven decision-making and collaboration.

Excel’s business intelligence tools—Power Query, Power Pivot, Data Model, and DAX—are catalysts for data professionals. By mastering these tools, you can significantly enhance your data analysis and reporting capabilities. The ability to integrate data from multiple sources, perform advanced calculations, and create interactive visualizations empowers you to derive meaningful insights and drive better business decisions. If you need further information on using MS Excel jump over to the official Microsoft Support website.

Video Credit: Source

Filed Under: Guides

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Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Transforming Your Organization with the Power of Business Intelligence

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With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.

Understanding Business Intelligence

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.

Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.

The Four Pillars of Business Intelligence

Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.

Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.

Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.

Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.

The Transformative Impact of Business Intelligence Improved Decision Making

BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.

Operational Efficiency

The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.

Improved Bottom Line

Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.

Competitive Advantage

Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.

Ethical Considerations in BI

The Future of Business Intelligence

Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.

Conclusion

Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.

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This doesn’t fit right here… please change the placement [SD2]

Business Intelligence Market worth USD 56,200.9 million by 2033 – Exclusive Report by Future Market Insights, Inc.

The global business intelligence market size is predicted to surpass a valuation of US$ 28,216.8 million in 2023. It is anticipated to hit a valuation of US$ 56,200.9 million by 2033. The market is projected to thrive at a CAGR of 7.1% from 2023 to 2033.

The capabilities of business intelligence systems have been considerably improved by ongoing technological breakthroughs. Such as in cloud computing, big data analytics, artificial intelligence, and machine learning. Scalability, flexibility, and affordability are all features of cloud-based BI solutions that enable BI to be used by businesses of various sizes.

More advanced data analysis and predictive modeling are possible by AI-powered analytics tools and machine learning algorithms, enabling firms to find important patterns and insights.

Organizations are aware that successfully utilizing data may provide them with a competitive advantage. Businesses may acquire a greater knowledge of their customers, markets, and operations by utilizing business intelligence tools to find hidden patterns, trends, and correlations in their data. These insights may be utilized to improve consumer experiences, find new market possibilities, optimize corporate strategy, and spur innovation.

Self-service analytics are now supported by business intelligence platforms, enabling users to access and evaluate data without relying heavily on IT or data analysts. Self-service BI technologies allow non-technical people to independently examine data, produce reports, and develop insights due to their easy user interfaces, drag-and-drop capabilities, and visualizations. Within enterprises, this movement has democratized data analytics and increased the user base of business intelligence.

The business intelligence system’s more up-to-date sophisticated analytics and improved statistical support are also contributing to the market’s expansion. Business intelligence technologies and machine learning aid corporate settings in problem-solving strategies and forecasting potential outcomes.

Additionally, this aids in streamlining internal corporate operations, boosting revenue development, and connecting technology. To improve processing, giving businesses an advantage over rival brands, thereby surging Business Intelligence market growth consistently.

Key Takeaways:

The global business intelligence market size expanded at a CAGR of 5.0% from 2018 to 2022. In 2018, the global market size stood at US$ 21,962.1 million. The market size stood at US$ 26,745.8 million in 2022. In 2022, the solution segment captured 68.9% of market shares. The sales and marketing segment captured 42.3% shares in the global market. In 2022, the United States captured 19.4% shares in the global market. China held 8.3% shares in the global business intelligence industry in 2022. In 2022, the United Kingdom captured 6.7% shares in the global market.

Key Players:

IBM Oracle Microsoft SAP Google

Recent Developments Observed:

Ramp announced its ambitions to provide new artificial intelligence technologies in May 2023. The business plans to introduce the new tools with a function that might ascertain whether a firm has overpaid for its software contracts. SoftLedger debuted a business intelligence dashboard with real-time data in December 2022. The purpose of this publication is to assist Chief Financial Officers (CFOs) in making tactical decisions for their company.

Market Segmentation:

By Component:

Solution Dashboards and Scorecards Data Integration and ETL Reporting and Visualization Query and Analysis Service Consulting Services Deployment and Integration Services Support and Maintenance Services

By Organization Size:

By Business Function:

Human Resources Finance Operations Sales and Marketing

By Vertical:

Retail Manufacturing Government and Public Services Media Entertainment Transportation and Logistics BFSI Telecom and IT Healthcare and Hospitality

By Deployment:

By Region:

North America Latin America Europe East Asia South Asia Oceania The Middle East & Africa (MEA)

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About Future Market Insights (FMI)

Future Market Insights, Inc. (ESOMAR certified, recipient of the Stevie Award, and a member of the Greater New York Chamber of Commerce) offers profound insights into the driving factors that are boosting demand in the market. FMI stands as the leading global provider of market intelligence, advisory services, consulting, and events for the Packaging, Food and Beverage, Consumer Technology, Healthcare, Industrial, and Chemicals markets. With a vast team of over 400 analysts worldwide, FMI provides global, regional, and local expertise on diverse domains and industry trends across more than 110 countries. Join us as we commemorate 10 years of delivering trusted market insights. Reflecting on a decade of achievements, we continue to lead with integrity, innovation, and expertise.

Contact Us:

Future Market Insights Inc.Christiana Corporate, 200 Continental Drive,Suite 401, Newark, Delaware – 19713, USAT: +1-845-579-5705For Sales Enquiries: sales@futuremarketinsights.comWebsite: https://www.futuremarketinsights.comLinkedIn| Twitter| Blogs | YouTube

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