Data analytics is the science of analyzing raw data to make conclusions about that information. It helps businesses perform ...

The answer lies in “EDSEL”—an acronym I use for a framework of five key considerations for determining whether data analytics makes sense on a cost/benefit basis.

Radiant Advisors' John O'Brien outlines the components of a modern data architecture in this clip from his presentation at Data Summit Fall Connect 2020.

SEE: Data Governance in Entertainment (TechRepublic) Can you use BI, AI, and data analytics together? Analytics and AI can be integrated into a larger BI framework, but they don’t have to be.

Organizations that invest in analytics without an aligned data & analytics strategy are burning money in the name of data. Here’s how you can create a successful data strategy that delivers value.

With the Climate Data Analytics Framework (CDAF), Leidos provides solutions for climate data operations to government and commercial customers.

Master data cleaning with the CLEAN framework, a tested method to turning chaotic datasets into clarity and precision. Clean messy datasets ...

Data modeling is the framework that lets data analysis use data for decision-making. A combined approach is needed to maximize data insights.

Regulations also change, as does the macro-economic environment, and to continue to meet the DOJ expectations the data analytics framework must evolve too, with new tests and approaches applied.

Here’s their four-stage framework for data analytics, presented in order of both increasing complexity and increasing value to the athlete or coach: Descriptive: What happened?