Remove Analytics Remove Big data Remove Mining Remove Unstructured data
article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

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.

article thumbnail

Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge. How does text mining work?

Mining 53
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data.

article thumbnail

Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? It’s also necessary to understand data cleaning and processing techniques.

article thumbnail

Part 2: OMG! Not another digital transformation article! Is it about the evolution from RIM to Content Services?

ARMA International

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. For example, once a health record has met the regulatory requirements, the record can be anonymized and kept for years for such purposes as medical research and predictive analytics. Artificial Intelligence.

article thumbnail

Capgemini and IBM Ecosystem strengthen partnership for Drone-as-a-Service

IBM Big Data Hub

It promises end-to-end solutions to manage and monitor a fleet of drones, runs inspection missions to capture high-quality data, accesses inspection reports and derives actionable information through AI-driven analytics—all through a single platform.

article thumbnail

Looking for a needle in a haystack couldn’t be easier!

CGI

Big data is a massive opportunity. We’ve all seen the big data statistics: every minute 1,820 TB of data is created, 204m emails and 11 million instant messages are sent, 700,000 Google searches are made and businesses receive 35,000 Facebook likes. Unstructured Social data, sentiment and trend analysis.

Mining 40