In the past few years, we’ve seen an explosion in the number and variety of organizations that are adopting big data technologies such as Hadoop and Spark and the recent trend to leverage data services in the cloud. How are enterprises coping?
Apache Spark not only excels at data warehousing, in-memory environments for building data marts and other functions, it also is well suited for pulling data from a wide range of sources and transforming and cleansing that data in an Apache Hadoop cluster. And then there is Spark’s complementary
Implementing advanced analytics practices in the government sector can be particularly challenging because of infrastructure and software, security, agility and internal human obstacles. But there is a way to bring the community closer to analytics-driven government and to leave behind the
In 2016 and beyond, the data warehouse will continue to be relevant, but the new requirement will be for hybrid data warehouse solutions. As organizations strive to be more data-driven, new types of analytics are coming to the forefront. IBM has again been named a leader in the Gartner Magic
Since the relational database first came to be, back in the 1980's, there's been a need for organizations to continuously evolve their analytical architectures. A new report talks about how modern groups are getting their data and analytics architecture updated for a new century—and a new set of
Dealing with slow technology is a major concern for anyone who needs quick access to analytic insights. For this reason, it’s vital to have a data warehouse appliance with sufficient speed that allows all users to make the most of its analytic power.
Big data has shown itself to be an illuminating force for sourcing the insight that is powering a tremendous transformation in modern life. To keep pace with the rapid changes, today’s organizations are seeking to improve their capabilities, competencies and culture to turn data into business value
Rather than shying away from ever increasing amounts of data, today’s businesses are using data-driven decision-making as a secret weapon. Learn more about why logical data warehouses are the natural next step for the analytics culture.
Regardless of your specific DW requirements, it’s as important as ever to partner with a vendor that has the proven breadth and depth of solutions to fit each of these needs. Gartner cites IBM’s “broad offering and integration across products that can support all four major data warehouse use cases
As exciting as the Big Data for Social Good Challenge is, it is also a little intimidating to think of an idea big enough for big data. In this post, I’ll share some tips to get you going on the Challenge. Just like a term paper, beginning is the key to finishing, so let's get started.