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. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

CIO Business Intelligence

JANUARY 20, 2023

The potential use cases for BI extend beyond the typical business performance metrics of improved sales and reduced costs. 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

datapine

JANUARY 31, 2022

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Domino Data Lab

JUNE 2, 2019

Co-chair Paco Nathan provides highlights of Rev 2 , a data science leaders summit. We held Rev 2 May 23-24 in NYC, as the place where “data science leaders and their teams come to learn from each other.” If you lead a data science team/org, DM me and I’ll send you an invite to data-head.slack.com ”.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

Business Over Broadway

MARCH 13, 2019

IBM is using the power of its Watson Studio platform to extend the power of AI to people who fall outside the realm of data science, machine learning and AI experts. IBM Watson Studio is an end-to-end analytics solution to help you gain insights from your data. The next step is to analyze the data.

Statistics 78

Statistics Measurement Descriptive Analytics Machine Learning 78

Grooper

AUGUST 19, 2019

What are the metrics that business wants to see and why it is valuable? Then we discover other metrics we can create to provide value along the line based on gathered requirements and interviewing right people and understanding business. Sounds like data scientists have to be great communicators. The data scientist does this.

Machine Learning 40

Machine Learning Metrics Descriptive Analytics Testing 40