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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

Today, the most common usage of business intelligence is for the production of descriptive analytics. . Descriptive Analytics: Valuable but limited insights into historical behavior. The vast majority of financial services companies use the data within their applications for what is called “ Descriptive Analytics.”

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

What are the four types of data analytics? 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).

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Business analytics and business intelligence (BI) serve similar purposes and are often used as interchangeable terms, but BI can be considered a subset of business analytics. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward. This is the purview of BI.

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Are You Getting The Most Out Of Your Marketing Data?

Smart Data Collective

It’s great to know what your customers have already done – what campaigns engage them and which they ignore, what they’ve already purchased, and so forth – but if you really want to outperform the competition, you need to think predictively. In recent years, though, there’s been significant growth in the use of predictive analytics.

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Improve Underwriting Using Data and Analytics

Cloudera

To me, this means that by applying more data, analytics, and machine learning to reduce manual efforts helps you work smarter. According to a recent McKinsey report , digitized underwriting can improve loss ratios three to five points. It’s not easy, but it can be done in pragmatic steps to yield results.

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AIOps reimagines hybrid multicloud platform operations

IBM Big Data Hub

Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the following: Collect and aggregate the huge and ever-increasing volumes of operations data generated by multiple IT infrastructure components, applications and performance-monitoring tools. Predictive analytics to show what will happen next.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

By conducting extensive research and analysis, they generate reports that inform strategic decisions, identify areas for enhancement, and guide the implementation of new initiatives. Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios.