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 +
Financial services organizations face considerable challenges today. From regulatory changes to globalization to shifting customer expectations, the urgent need to re-engineer outdated systems to better manage vast amount of data can apply additional pressure. Organizations must deal with the
Owens-Illinois (O-I), the world’s largest manufacturer of glass containers, recently undertook a global migration from Oracle to Db2. Learn more about the migration and its success from O-I executives.
Big data doesn’t need to be a daunting challenge for small or midsized business (SMBs). Accessing, storing and exploring big data can be done by businesses of any size. An influx of data from sensors, streaming audio and video log files, web, and social media are increasing the volume, velocity,
A company only survives for 115 years by reinventing itself, questioning assumptions, and constantly looking for an edge. Owens-Illinois (O-I), the world’s largest manufacturer of glass containers, used worldwide by many leading food and beverage brands, recently began just such a reinvention.
The focus on customer needs for greater choice and flexibility is a constant at the IBM Think 2019 conference. Nowhere is this more evident than in IBM Hybrid Data Management, which supports data of any type, source and structure, be it on-premises or in the cloud.
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.
If you’ve heard the debate among IT professionals about data lakes versus data warehouses, you might be wondering which is better for your organization. You might even be wondering how these two approaches are different at all.
The IBM Integrated Analytics System (IIAS), is a unique, cloud-ready appliance and machine learning platform wields the power of an in-memory, massively parallel processing database engine with embedded Spark. It also runs on market-leading IBM Big Data Servers and IBM FlashSystem 900 storage