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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. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts.

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13 Analytics & Business Intelligence Examples Illustrating The Value of BI

datapine

Digital data, by its very nature, paints a clear, concise, and panoramic picture of a number of vital areas of business performance, offering a window of insight that often leads to creating an enhanced business intelligence strategy and, ultimately, an ongoing commercial success. 1) Improving The Decision-Making Process.

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Using Business Intelligence in Demand Forecasting

Jet Global

Although it’s been around for decades, predictive analytics is becoming more and more mainstream, with growing volumes of data and readily accessible software ripe for transforming. In this blog post, we are going to cover the role of business intelligence in demand forecasting, an area of predictive analytics focused on customer demand.

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Business Intelligence Dashboard (BI Dashboard): Best Practices and Examples

FineReport

In today’s fast-paced business environment, making informed decisions based on accurate and up-to-date information is crucial for achieving success. With the advent of Business Intelligence Dashboard (BI Dashboard), access to information is no longer limited to IT departments.

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Business analytics in the age of disruption

IBM Big Data Hub

Specifically, we see an increase of line-of-business areas using planning for “what if” and scenario modelling, determining multiple pathways to success for comparison. They are using AI forecasting and decision optimization algorithms to enable success in a world of finite resources and time. This solution was a success for Novolex.

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Using Business Intelligence in Demand Forecasting

Jet Global

Although it’s been around for decades, predictive analytics is becoming more and more mainstream, with growing volumes of data and readily accessible software ripe for transforming. In this blog post, we are going to cover the role of business intelligence in demand forecasting, an area of predictive analytics focused on customer demand.

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Don’t Blink: You’ll Miss Something Amazing!

Cloudera

This real-time data, when captured and analyzed in a timely manner, may deliver tremendous business value. For example: In manufacturing, fast-moving data provides the only way to detect — or even predict and prevent — defects in real time before they propagate across an entire production cycle.