Big Data Diagnostic Analytics Predictive Analytics 
CIO Business Intelligence
JUNE 7, 2022
In business analytics, this is the purview of business intelligence (BI). Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance. In business, predictive analytics uses machine learning, business rules, and algorithms.
IBM Big Data Hub
SEPTEMBER 19, 2023
To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. For example, retailers can predict which stores are most likely to sell out of a particular kind of product.
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BizAcuity
MARCH 31, 2022
By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Source: Gartner Research). Source: TCS).
Birst BI
FEBRUARY 13, 2018
Birst’s patented Automated Data Refinement extracts data from any source (data stores, applications, warehouses, big data, and unstructured external sources) into a unified semantic layer. The Birst platform also makes it easy for enterprises to create their own analytics products or monetize their data.
FineReport
MARCH 24, 2024
Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis.
Rocket-Powered Data Science
OCTOBER 6, 2023
There are other dimensions of analytics that tend to focus on hindsight for business reporting and causal analysis – these are descriptive and diagnostic analytics, respectively, which are primarily reactive applications, mostly explanatory and investigatory, not necessarily actionable. This is predictive power discovery.
Jet Global
MAY 1, 2023
Ideally, your primary data source should belong in this group. Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more.
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