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 86

Data Science Data Analytics Prescriptive Analytics Analytics 86

CIO Business Intelligence

JULY 5, 2022

What are the benefits of business analytics? What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics. Predictive analytics: What is likely to happen in the future? Prescriptive analytics: What do we need to do?

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Smart Data Collective

OCTOBER 14, 2019

From artificial intelligence and machine learning to blockchains and data analytics, big data is everywhere. A global retailer like Amazon with its same-day shipping and multi-channel services might have billions of data points across several sectors. Gartner estimates a retail IT spend forecast of $210.9

Big Data 75

Big Data Software Data mining Prescriptive Analytics 75

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 61

Machine Learning Data Science Statistics Deep Learning 61

Alation

MARCH 21, 2023

As an industry with tight margins, travel and tourism companies can use analytics to detect trends that help them reduce costs, decide future product and service offerings, and develop successful business strategies. Why is data analytics important for travel organizations? How is data analytics used in the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Domino Data Lab

JUNE 2, 2019

She had much to say to leaders of data science teams, coming from perspectives of data engineering at scale. And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. Worse than flipping a coin! That may take a while.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110