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

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. AI is used for investments, automating accounting, fraud detection, claims prediction, credit scoring and risk profiling among others. Source: Gartner Research). Source: PwC).

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

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. JPMorgan Chase & Co.:

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 54

Machine Learning Data Science Statistics Deep Learning 54

FineReport

APRIL 26, 2023

Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting. Prescriptive Analytics provides precise recommendations to respond to the query, “What should I do if ‘x’ occurs?”

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 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