datapine

MAY 9, 2019

This concept is known as business intelligence. Business intelligence, or “BI” for short, is becoming increasingly prevalent across industries each year. But with business intelligence concepts comes a great deal of confusion, and ultimately – unnecessary industry jargon. Learn here! But more on that later.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems vs. business intelligence DSS and business intelligence (BI) are often conflated. Decision support systems are generally recognized as one element of business intelligence systems, along with data warehousing and data mining. Some experts consider BI a successor to DSS.

Data mining 144

Data mining Data-driven Statistics OLAP 144

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 77

Data Science Data Analytics Prescriptive Analytics Analytics 77

Rocket-Powered Data Science

JULY 7, 2019

Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). NLG is a software process that transforms structured data into human-language content. Examples: Cars, Trucks, Taxis.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

FineReport

JUNE 24, 2021

Once the data becomes more extensive or more complex, Excel or other simple solutions may “fetter” your potentialities. That’s why business intelligence solutions(BI solutions) come into our minds. Business Intelligence Solutions Definition. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

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 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98