Birst BI
OCTOBER 30, 2018
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.”
CIO Business Intelligence
JUNE 7, 2022
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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CIO Business Intelligence
JULY 5, 2022
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.
datapine
MARCH 25, 2022
On the other hand, BA is concerned with more advanced applications such as predictive analytics and statistic modeling. By using Business Intelligence and Analytics (ABI) tools, companies can extract the full potential out of their analytical efforts and make improved decisions based on facts.
Smart Data Collective
MARCH 29, 2021
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.
IBM Big Data Hub
SEPTEMBER 19, 2023
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.
Cloudera
SEPTEMBER 22, 2022
The next step leads to performing exploratory, descriptive analytics, “why is this happening,” and so on. Finally, the end goal is to enable proactive, predictive analytics — “what if” — using applied ML and AI to better predict what will happen and recommend actions to prevent or manage activities as necessary.
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