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 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

CIO Business Intelligence

FEBRUARY 16, 2023

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

FineReport

JULY 28, 2021

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. What is Data Science? Typical tools for data science: SAS, Python, R.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Smart Data Collective

OCTOBER 13, 2021

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement. There is little use for data analytics without the right visualization tool.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

CDW Research Hub

SEPTEMBER 15, 2020

Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Traditional data warehouses are often too slow and can’t handle large volumes of data or different types of semi-structured or unstructured data.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52