Blogs

Easing the journey to AI through full-function, untimed trials and streamlined database upgrades

Easing the journey to AI through full-function, untimed trials and streamlined database upgrades

August 19, 2019 | by Kip Yego, Db2 Product Marketing Manager, IBM
Choosing the right data management solutions as the foundation for AI is crucial. Enabling AI optimization and usability is paramount, as is easy scalability to accommodate the increasing amount of data used by AI applications. This is true no matter where you store your data: on-premises, in the...
6 DataOps essentials to deliver business-ready data

6 DataOps essentials to deliver business-ready data

August 15, 2019 | by Aliye Ozcan, Portfolio Marketing Leader, WorldWide, IBM
Nearly every business is under competitive, disruptive, and regulatory pressures. As companies face digital transformation and modernization to meet their customers’  expectations, leveraging data and AI at the speed of business can be the biggest differentiator. However, according to MIT Sloan, 81...
Why hybrid cloud environments require live data replication technology

Why hybrid cloud environments require live data replication technology

August 12, 2019 | by Holly Vatter, Product Marketing Manager for Data Lake & Hortonworks Partnership, IBM
The best decisions are made by extracting value from all the disparate data across your business. Yet aggregating data across external sources, regional silos and various forms of storage is not an easy challenge to solve. Data-powered businesses need always-on access to data to keep operations...
Sample-based analysis: A new approach for unstructured data management

Sample-based analysis: A new approach for unstructured data management

August 9, 2019 | by Priyanka Jain, Offering Manager, IBM
Introducing IBM StoredIQ Instascan for accelerated compliance and risk assessments. Read to learn more.
Exploring Python's popularity and use with SQL databases

Why Python is getting more popular...and how to use it with SQL databases

August 8, 2019 | by Roger Sanders, DB2 for LUW Offering Manager, IBM
For the past nine years, Stack Overflow, a question-and-answer website for programmers, has polled developers to understand what technologies they are using and to find out what technologies they want to work with next. This year, the nearly 90,000 survey participants revealed that, once again,...
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 & Hortonworks 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 +...
Data virtualization powers AI across a multicloud environment

Data virtualization powers AI across a multicloud environment

July 30, 2019 | by Scott Hebner, Vice President of Marketing for Data & AI, IBM
Data quality. Talent. Trust. Find out how Cloud Pak for Data—with data virtualization—treats these three major pain points when managing your data estate.
Driving the culture of AI forward with MongoDB

Driving the culture of AI forward with MongoDB

How MongoDB and “partner of the year” IBM collaborate to drive your AI practice

July 30, 2019 | by Nikhil Shetty, Product Marketing Manager - Open Source DB and Data Management Tools, IBM
“In 2021, AI augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity,” according to Gartner. It will do so largely by learning how to make better predictions over time and supplementing people’s ability to complete tasks in more natural ways...
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...
An easy upgrade from Netezza to the IAS brings major benefits for Capitalogix

An easy upgrade from Netezza to the IAS brings major benefits for Capitalogix

July 17, 2019 | by Holly Vatter, Product Marketing Manager for Data Lake & Hortonworks Partnership, IBM
Capitalogix is a hedge fund, but it’s really a data science firm in disguise. They work to understand and exploit capital markets by building custom data science models that can analyze massive amounts of data from as many sources as possible. Capitalogix’s need for high-performance analytics and...

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