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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. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

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What Leaders Want: Shifting to AI-Driven Healthcare

DataRobot Blog

The main themes emerging from our conversations cover data integration, security and humility, strategy, and workforce development: Join siloed data together to create longitudinal, ready-to-analyze datasets. The push to predictive and prescriptive analytics requires strategy and C-Suite ownership.

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Machine Learning and AI Underpin Predictive Analytics to Achieve Clinical Breakthroughs

Cloudera

For those asking big questions, in the case of healthcare, an incredible amount of insight remains hidden away in troves of clinical notes, EHR data, medical images, and omics data. To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities.

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Four starting points to transform your organization into a data-driven enterprise

IBM Big Data Hub

This capability will provide data users with visibility into origin, transformations, and destination of data as it is used to build products. The result is more useful data for decision-making, less hassle and better compliance. Data integration. Data science and MLOps. Start a trial. Start a trial.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.