Remove Data Integration Remove Machine Learning Remove Prescriptive Analytics
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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.

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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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Machine Learning and AI Underpin Predictive Analytics to Achieve Clinical Breakthroughs

Cloudera

To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities. Additionally, organizations are increasingly restrained due to budgetary constraints and having limited data sciences resources.

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What is the Future of Business Intelligence in the Coming Year?

Smart Data Collective

The current BI trends show that in the future, the BI software will be more accessible, so that even non-techie workers will rely on data insights in their working routine. Prescriptive Analytics. Advantage: unpaired control over data. . This shows why self-service BI is on the rise. QlickSense.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The company’s Findability.ai

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Trending Technologies for BI & Financial Planning and AnalysisMaking AI Real (Part 2)

Jedox

Part one of our blog series explored how people are the driving force behind the digital transformation and how it is fueled by artificial intelligence and machine learning. Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive.

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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.