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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Over the past decade, business intelligence has been revolutionized. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. 2019 was a particularly major year for the business intelligence industry. Data exploded and became big.

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What Is The Difference Between Business Intelligence And Analytics?

datapine

1) What Is Business Intelligence And Analytics? 4) How Do BI And BA Apply To Business? If someone puts you on the spot, could you tell him/her what the difference between business intelligence and analytics is? We already saw earlier this year the benefits of Business Intelligence and Business Analytics.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Experience the power of Business Intelligence with our 14-days free trial! Why Is Business Intelligence So Important? The power of knowledge.

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Top 10 Analytics And Business Intelligence Buzzwords For 2020

datapine

Business intelligence has undergone many changes in the last decade. Each year, we hear about buzzwords that enter the community, language, market and drive businesses and companies forward. That’s why we have prepared a list of the most prominent business intelligence buzzwords that will dominate in 2020.

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Building your First Power BI Report from Scratch

Analytics Vidhya

PowerBI is used for Business intelligence. What is equally important here is the ability to communicate the data and insights from your predictive models through reports and dashboards. Introduction In this article, we will explore one of Microsoft’s proprietary products, “PowerBI”, in-depth.

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Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

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Data Insights for Everyone — The Semantic Layer to the Rescue

Rocket-Powered Data Science

The data scientists need to find the right data as inputs for their models — they also need a place to write-back the outputs of their models to the data repository for other users to access. The BI team may be focused on KPIs, forecasts, trends, and decision-support insights. That’s data insights for everyone.