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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. In business analytics, this is the purview of business intelligence (BI). Data analytics and data science are closely related.

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A Guide To The Methods, Benefits & Problems of The Interpretation of Data

datapine

Through the art of streamlined visual communication, data dashboards permit businesses to engage in real-time and informed decision-making and are key instruments in data interpretation. Typically, quantitative data is measured by visually presenting correlation tests between two or more variables of significance.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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10 Big Data Examples Showing The Great Value of Smart Analytics In Real Life At Restaurants, Bars, and Casinos

datapine

When you think of big data, you usually think of applications related to banking, healthcare analytics , or manufacturing. After all, these are some pretty massive industries with many examples of big data analytics, and the rise of business intelligence software is answering what data management needs. What’s the motive?

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A Complete Guide On How To Set Smart KPI Targets And Goals

datapine

KPI targets are short-term performance measurements used by businesses to track the progress of their strategies towards achieving general goals. With the help of KPI reports , all of these targets can be visualized together to get a complete picture across departments. From sales to procurement, we now cover the production area.

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Change The Way You Do ML With Applied ML Prototypes

Cloudera

They need strong data exploration and visualization skills, as well as sufficient data engineering chops to fix the gaps they find in their initial study. The project launches an interactive visualization for exploring the quality of representations extracted using multiple model architectures. Deep Learning for Image Analysis.

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Fast Provisioning of data through Data Virtualization in the Era of ever-increasing Data Fluidity

Data Virtualization

We are in the midst of a significant transformation in each and every sphere of business. The way products are getting manufactured is being transformed with automation, robotics, and. We are witnessing an Industrial 4.0 revolution across the industrial sectors.