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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

An analytics alternative that goes beyond descriptive analytics is called “Predictive Analytics.”. Predictive Analytics: Predicting Future Outcomes. While descriptive analytics are focused on historical performance, predictive analytics are about predicting future outcomes.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Having the right data strategy and data architecture is especially important for an organization that plans to use automation and AI for its data analytics. The types of data analytics Predictive analytics: Predictive analytics helps to identify trends, correlations and causation within one or more datasets.

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

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Disrupt and Innovate in a Data-Driven World

Cloudera

Applying data analytics and machine learning to large raw datasets will likely also yield us new and unexpected insights as these techniques and tools allow us to unearth patterns and seek potential explanations for those in contrast to responding to a predefined set of questions.

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

AWS Big Data

Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse.