What is Microsoft Fabric? A big tech stack for big data

Microsoft Fabric is an end-to-end, software-as-a-service (SaaS) platform for data analytics. It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment. Microsoft Fabric encompasses data movement, data storage, data engineering, data integration, data science,…

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Building an Effective Data Strategy for Edge Deployments

Data analytics and integration are the key components of building a data strategy. For organizations to have an effective data strategy, it requires the definition of measurable metrics and proper consideration of all data sources. An effective data strategy also needs to define how data can be moved from various sources to a location where…

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Webinar: Beyond the Hype – The Real Impact of AI on Business Intelligence

Download the slides here>> This webinar is sponsored by: About the Webinar Join us to learn how the user journey with BI can change for the better by integrating AI. We’ll take a look at the perspectives of both Analysts and Business Users, to understand where the practical application of AI can help in the…

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The FAAR Framework for Consuming Insights from Data and Analytics 

Faced with overwhelming amounts of data, organizations across the world are looking at leveraging data and analytics (D&A) to derive insights to increase revenue, reduce costs, and mitigate risks. McKinsey found that insight-driven companies report EBITDA (earnings before interest, taxes, depreciation, and amortization) increases of up to 25% [1]. According to Forrester, organizations that use data and insights…

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How Data Analytics Is Transforming Due Diligence

Due diligence is the complex process of assessing a potential investment and ensuring it is a sound one. It involves the gathering, classifying, and analyzing of large volumes of data. Given its very nature, it’s the perfect field for data analytics, which can speed processes up and assess the quality and reliability of data. Due…

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Business Intelligence and Analytics Trends in 2024

As organizations continue to generate massive amounts of data from various sources, the need for effective data analytics and business intelligence (BI) solutions has never been more pressing.  Here are some general trends for data analytics and BI:  Use of Advanced Algorithms in Data Analysis  Advancements in machine learning (ML) and artificial intelligence (AI) are…

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Data Governance: Your Key To Unlocking an Insights-Driven Business

Organizations are constantly seeking ways to gain a competitive edge by transforming data into actionable insights through analytics. However, achieving analytical success goes beyond just collecting large volumes of data and building dashboards. The key to turning data into meaningful and actionable insights across the organization lies in a frequently overlooked area – establishing a…

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What to Expect at Solutions Review’s Solution Spotlight with Infragistics on February 15

Solutions Review’s Spotlight with Infragistics is entitled: How Embedded Analytics Empowers Analytics Empowers Organizations for Digital Transformation. What is a Solutions Spotlight? Solutions Review’s Solution Spotlights are exclusive webinar events for industry professionals across enterprise technology. Since its first virtual event in June 2020, Solutions Review has expanded its multimedia capabilities in response to the…

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Analytics and Data Science News for the Week of February 2; Updates from Databricks, Microsoft, ThoughtSpot & More

Solutions Review Executive Editor Tim King curated this list of notable analytics and data science news for the week of February 2, 2024. Keeping tabs on all the most relevant analytics and data science news can be a time-consuming task. As a result, our editorial team aims to provide a summary of the top headlines…

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How to Become a Citizen Data Scientist

The job responsibilities of a citizen data scientist include dealing with new data, using automated tools to process big data, and creating additional models to gain additional insights. Their primary job is not to make predictions directly from big data, or develop prescriptive analytics, but to build models and use tools that accomplish those goals….

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