Blogs

Filter Content

Hadoop
Reality and misconceptions about big data analytics, data lakes and the future of AI

Reality and misconceptions about big data analytics, data lakes and the future of AI

December 19, 2019 | by Holly Vatter, Product Marketing Manager for Data Lake & Cloudera Partnership, IBM
With the amount of choices surrounding big data analytics, data lakes and AI, it can sometimes be difficult to tell fact from fiction. With more than 40% of organizations expecting AI to be a “game changer,” it’s important to have a complete picture of the capabilities and opportunities available.
Unpacking Gartner’s assessment of IBM in the 2019 Magic Quadrant for Operational DBMS

Unpacking Gartner’s assessment of IBM in the 2019 Magic Quadrant for Operational DBMS

November 26, 2019 | by Matthias Funke, Director Hybrid Data Management, IBM Analytics
With the publication of Gartner’s 2019 Magic Quadrant (MQ) for Operational Database Management Systems, we were happy to see recognition of some of our key efforts from the past year. The integration of the Db2 common SQL engine and other rich features, edition simplification, commitment to...
Making the connection: how SQL on Hadoop brings together data for deeper insight

Making the connection: how SQL on Hadoop brings together data for deeper insight

August 22, 2019 | by Holly Vatter, Product Marketing Manager for Data Lake & Cloudera Partnership, IBM
The fusing of analytics with leading technologies can unlock significant business value and bring new transformation opportunities for enterprise companies. In order to be successful, analytics-based initiatives such as AI and the Internet of Things (IoT) need massive amounts of big data—and also...
The cost of data warehouse appliance complexity: Comparing IAS and IntelliFlex

The cost of data warehouse appliance complexity: Comparing IAS and IntelliFlex

August 5, 2019 | by Holly Vatter, Product Marketing Manager for Data Lake & Cloudera Partnership, IBM
In a previous blog, I explained how data science capabilities, massive parallel processing (MPP) and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice? Research firm Quark +...
Advancements in streaming data storage, real-time analysis and machine learning

Advancements in streaming data storage, real-time analysis and machine learning

July 25, 2019 | by Sue Green, Product Marketing Manager, IBM Data & AI, IBM
It’s no surprise:  most companies working with stream data today say they are planning to make changes to drive greater value. Advancements in machine learning (ML) and very-high-speed data persistence for real-time analytics are reshaping strategies and architectures. In addition, 88 percent of...
Submit your entry for Call for Code 2019

Join the app development competition aiming to save lives worldwide

Submit your entry for Call for Code 2019

July 15, 2019 | by Sue Green, Product Marketing Manager, IBM Data & AI, IBM
Last year, more than 100,000 developers from 156 nations built 2,500+ applications in Call for Code 2018, an IBM initiative to create meaningful change through technology. This year, it's your turn. Join Call for Code 2019 and you’ll have the opportunity to create sustainable software solutions...
How IBM is advancing DataOps and Watson Anywhere with new capabilities

How IBM is advancing DataOps and Watson Anywhere with new capabilities

June 27, 2019 | by Daniel G. Hernandez, VP, Data and AI, IBM
While data is an enterprise’s most valuable resource when it comes to gaining competitive advantage and improving business performance, time is a critical component. Businesses run 24x7, tasking our data citizens to maximize actionable insights that will drive the actions of tomorrow. However, if...
How enterprises benefit from a database powered by and built for AI

How enterprises benefit from a database powered by and built for AI

June 26, 2019 | by Pandit Prasad, Offering Management, IBM Cloud and Cognitive Software, IBM
Businesses should consider a database that is both powered by, and built for, AI. Learn why you should start your AI journey with Db2 11.5.
Why analysts are hailing Db2 11.5 as the database for AI

Why analysts are hailing Db2 11.5 as the database for AI

June 20, 2019 | by Kevin Oliver, Portfolio Marketing Manager, Hybrid Data Management, IBM
Learn why analysts and journalists hail Db2 11.5 has already as “a major upgrade” and as the AI database.
Making monitoring AI bias a little easier

Making monitoring AI bias a little easier

June 17, 2019 | by Susannah Shattuck, Product manager, Watson OpenScale, IBM
Starting today, we are making it easier to detect and mitigate bias against protected attributes like sex and ethnicity with Watson OpenScale through recommended bias monitors.

Pages