CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 135

Data mining Data-driven Statistics OLAP 135

Smart Data Collective

OCTOBER 13, 2021

It can control changes in the sources from which it extracts data and includes Data Lineage capabilities, which means confidence for the user. How is Data Virtualization performance optimized? How does Data Virtualization complement Data Warehousing and SOA Architectures? Prescriptive analytics.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

AWS Big Data

MARCH 26, 2024

Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 104

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 104

FineReport

JULY 28, 2021

Definition: BI vs Data Science vs Data Analytics. Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Sisense

JUNE 30, 2020

Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. Predicting forthcoming trends sets the stage for optimizing the benefits your organization takes from them.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56