CIO Business Intelligence

JANUARY 20, 2023

Increased competitive advantage: A sound BI strategy can help businesses monitor their changing market and anticipate customer needs. Business intelligence vs. business analytics Business analytics and BI serve similar purposes and are often used as interchangeable terms, but BI should be considered a subset of business analytics.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Domino Data Lab

JANUARY 21, 2021

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. Each dataset has properties that warrant producing specific statistics or charts. There is no clear end state. ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

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.”

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Sisense

JUNE 30, 2020

The primary objective of data visualization is to clearly communicate what the data says, help explain trends and statistics, and show patterns that would otherwise be impossible to see. Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. Visualizations: past, present, and future.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Sisense

SEPTEMBER 12, 2019

A business intelligence strategy is a blueprint that enables businesses to measure their performance, find competitive advantages, and use data mining and statistics to steer the business towards success. . Most companies find themselves in the bottom left corner, in the Descriptive Analytics and Diagnostic Analytics sections.

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

FineReport

MARCH 24, 2024

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

MARCH 2, 2018

In the nonprofit sector, early applications of data analytics and machine learning have mostly focused on improving fundraising and marketing. Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques. In many settings this is the best information available.

Data-driven 43

Data-driven Prescriptive Analytics Machine Learning Descriptive Analytics 43

Alation

NOVEMBER 28, 2022

Spreadsheets dominate the activities of gathering and preparing data, and performing descriptive analytics. Demand generation marketing teams rely on spreadsheets for analyzing the performance and ROI of different channels. Or they don’t have the technical skill to extract, cleanse, or transform data they need.

Descriptive Analytics 52

Descriptive Analytics Sales Risk Data-driven 52

CIO Business Intelligence

APRIL 9, 2025

One of the most fundamental tenets of statistical methods in the last century has focused on correlation to determine causation. For example, an analytics dashboard that correlates shipping data gaps in a logistics view could be correlated to quantities released for distribution in a warehouse.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

Jet Global

MAY 1, 2023

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52