CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? It is frequently used for risk analysis.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

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. AWS S3: Offers cloud storage for storing and retrieving large datasets.

Statistics 52

Statistics Data mining Visualization Reporting 52

IBM Big Data Hub

JULY 6, 2023

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57

BizAcuity

MARCH 31, 2022

85% of AI (marketing) projects fail due to risk, confusion, and lack of upskilling among marketing teams.(Source: AI Adoption and Data Strategy. More use-cases are being tried, tested and built everyday, the innovation in this field will not cease for the next few years. Source: Gartner Research). Source: PwC). AI in Marketing.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. 4) Predictive And Prescriptive Analytics Tools.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Alation

AUGUST 26, 2021

Data intelligence has thus evolved to answer these questions, and today supports a range of use cases. Examples of Data Intelligence use cases include: Data governance. Cloud Data Migration. Privacy, Risk and Compliance. Let’s take a closer look at the role of DI in the use case of data governance.

Metadata 64

Metadata Data Governance Dashboards Software 64

Jet Global

MAY 1, 2023

All of the above points to embedded analytics being not just the trendy route but the essential one. Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” It will help to eliminate some of the development risks.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52