Blogs

A sneak preview of hybrid data management at THINK 2019

A sneak preview of hybrid data management at THINK 2019

January 18, 2019 | by Thomas Chu, Director, Offering Management, Hybrid Data Management, IBM
With THINK 2019 just around the corner, 12 through 15 February, there’s no better time to discover the variety of hybrid data management solutions and strategies, along with how each can help uncover actionable insights.
Is your data ready for AI?  Part 1

Is your data ready for AI? Part 1

January 10, 2019 | by Rafi Ezry, Partner, North American Leader, Cognitive Business Decision Support (CBDS), IBM
Enterprise leaders understand the importance of integrating AI into their business models. However, there's a big difference between experimenting with AI and true enterprise-grade integration of AI.
Data Science: Influencers review 2018 and share their 2019 predictions

Data Science: Influencers review 2018 and share their 2019 predictions

January 8, 2019 | by Holly Nielsen, Social Media Strategist, IBM
Data science was one of the hot topics of 2018, and it’s likely to dominate again in 2019. We've asked five key data science influencers to take a look back at 2018 and look ahead at what's to come in 2019.
Why analytics pros should go to Think 2019

Why analytics pros should go to Think 2019

January 7, 2019
Are you working to collect, organize, analyze or modernize your company’s data? Is your business on the ladder to AI? Then you should join us at IBM Think 2019, the event of the year for analytics pros and business leaders.
How AMC uses machine learning to find out more about TV viewers

How AMC uses machine learning to find out more about TV viewers

January 3, 2019 | by Hemant Suri, Senior Offering Manager, IBM
Machine learning is a hot topic no matter the industry, and rightfully so. Many see it as a path to greater efficiency and deeper insights.
3 trends leading to multicloud adoption

Top 3 trends leading to multicloud adoption

December 31, 2018 | by Bharath Chari, WW Product Portfolio Marketing Manager, IBM Data Integration & Data Replication
Martec's law states, “Technology changes exponentially; organizations change logarithmically.” Translation? Technology will accelerate faster than companies can adapt to increasing data growth and adopt new business models.
From data collection to data consumption

From data collection to data consumption

A shift in enterprise data strategies

November 12, 2018 | by Jay Limburn, Director and Distinguished Engineer, Offering Management, IBM
Not every startup is going to become a world-changing behemoth, but when a small, agile company hits on a truly disruptive idea, it can transform an entire industry.
How data cataloging helps analytics cultures evolve

How data cataloging helps analytics cultures evolve

November 8, 2018 | by Jay Limburn, Director and Distinguished Engineer, Offering Management, IBM
Data catalogs help to herd tribal knowledge and manage all the different data assets across an organization, providing a simple, convenient way to find, access and democratize data.
Get an IBM data science professional certificate on Coursera

Get an IBM data science professional certificate on Coursera

November 6, 2018 | by Sonia Malik, Business Development Manager, IBM
The swelling demand for data scientists coupled with the evident skills gap has implications for the global economy as well as the tech industry. What’s causing it, and what can be done to address it?
Why data science at banks is missing the mark, and how to fix it

Why data science at banks is missing the mark, and how to fix it

October 15, 2018 | by Karan Sachdeva, Director, Data And AI, Asia Pacific, IBM
The business that gets there first won’t necessarily win digital and AI game. It will be the one that ingrains digital and AI in its business as much as possible. Starting from applying intelligent data science where it matters most and progressively using it in every aspect of the business.