Remove Business Analytics Remove Data Engineering Remove Machine Learning
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What is data analytics? Analyzing and managing data for decisions

CIO

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 methods and techniques.

Analytics 203
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Forget the Rules, Listen to the Data

Hu's Place - HitachiVantara

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

Data 90
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Achieving Business Analytics Success

Datavail

Today’s thriving companies are embracing emerging data analytics programs to upgrade their business modeling technology from systems maintenance to value creation. The data indicate high success for enterprises that use data to develop their corporate strategies and then implement them into winning business operations.

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What Do CIOs Have To Know About Business Intelligence?

The Accidental Successful CIO

Understanding Business Intelligence vs. Business Analytics. Business intelligence tools provide insights into the current state of the business or organization: where are sales prospects in the pipeline today? It also gets to the heart of the question of who business intelligence is designed for.

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Change The Way You Do ML With Applied ML Prototypes

Cloudera

Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses. The work of a machine learning model developer is highly complex. We work with the largest companies in the world to help tackle their most challenging ML problems.

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

Cloudera

And all of this should ideally be delivered in an easy to deploy and administer data platform available to work in any cloud. This is especially necessary when combining real-time data with prepared data, and adding predictive concepts into our augmented dashboards and reports.

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The Ethics of AI Comes Down to Conscious Decisions

Cloudera

This could be addressed with an explanation of how a technology works — how, for instance, machine learning (ML) engines get better at their tasks by being fed gobs of data. It’s not the machine’s fault. A chatbot that now relies mostly on canned answers eventually becomes more precise and useful.