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Fundamentals of Data Mining

Data Science 101

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

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Transforming Credit and Collection with Predictive Analytics

BizAcuity

Today, it’s no secret that most forward-thinking businesses are keenly following the latest developments on big data, artificial intelligence, machine learning, and predictive analytics. With Big Data, it is possible to acquire and segregate data with laser sharp focus with respect to one singular debtor.

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. Business analytics techniques. This is the purview of BI.

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Data Analytics Assures Quality Assurance with Software Development Outsourcing

Smart Data Collective

Big data can play a surprisingly important role with the conception of your documents. Data analytics technology can help you create the right documentation framework. You can use data mining tools to inspect archives of open-source Agile documentation from other developers.

Software 100
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Make Your Investment in Analytic Technology Pay Off With Decision Requirements Modeling

Decision Management Solutions

Like many enterprises, you’ve likely made a hefty investment in analytic technology—from interactive dashboards and advanced visualization tools to data mining, predictive analytics, machine learning (ML), and artificial intelligence (AI). All these elements have a significant role in analytic projects.

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Challenges Data Analytics Can Solve in the Call Center Industry

Smart Data Collective

The good news is that data analytics technology can help with employee training. Companies use data analytics software to see how employees are progressing across various metrics. Data analytics can also help with compliance. Data analytics is also surprisingly important with cybersecurity.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

The data science lifecycle Data science is iterative, meaning data scientists form hypotheses and experiment to see if a desired outcome can be achieved using available data. For example, retailers can predict which stores are most likely to sell out of a particular kind of product.