Today, more than ever, businesses need to put the ability to analyze data into the hands of business analysts, data scientists, stakeholders and decision makers. Take an evolutionary look at how Apache Spark and big data discovery are just beginning to open up a diverse and powerful set of
Data engineers have much to learn from water management professionals, who have mastered the art of keeping filtered water on tap—ready at a moment’s notice. As information volumes begin to deluge data repositories and outpace traditional approaches, data professionals must use every tool at their
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.
Organizations that have built a data-driven culture are seeing gains in efficiency and capability that are allowing them to become leaders in their industries. Learn how you can begin integrating data science into your organization, enabling new ways of activating data as part of an enterprise-wide
Is your organization stuck at the edge of Hadoop adoption, searching for a path to broad use that doesn’t hold back your most proficient users? Big data discovery technology aims to help you bridge the chasm between early adoption and majority use, bringing rank-and-file users into the fold without
Creating a visualization whose design serves its intended function—rather than the other way around—can be intoxicating, but don’t get so high on data that you lose sight of your audience. Find out how including too much information can neutralize your visualization—and your message with it.
As we’ve learned, choosing an appropriate level of detail lays the foundation for an effective visualization. But if you simply take your first design idea and run with it, you might be doing your data a disservice. Find out why redundant visualizations can turn detail into too much of a good thing
How can you make the most of Hadoop in your enterprise? Create a pattern of success in your organization by incorporating Hadoop in your broader data architecture as a way of providing meaningful insights to your company.
Openness was a common refrain at Insight 2015, and the opportunities of open systems, technologies and the IBM analytics platform are abundant. Check out some observations from the conference and a few shining examples from its demo center.
As a strategic sponsor, IBM was represented in full force at Strata + Hadoop World 2015 in New York, New York. Day one proved to be a buzz of activity that included IBM data science experts getting a hands-on lab course on practical data science underway, IBM spokespeople discussing offerings and
By banishing “bankers’ hours,” mobile technology has transformed the banking industry. Learn how one New Zealand bank is using digital tools, real-time data and a reimagined strategy to strengthen customer relationships.
Choose a solution that can deliver deep insights into data without reinventing the wheel. Standardization can help you move large quantities of data across multiple systems, allowing you to take advantage of data no matter its source.
What are your big data requirements? Determine which type of Apache Hadoop user you fit most closely. Take a short quiz to see what kind of Hadoop user you likely are and what you likely need from Hadoop to be successful.
Sorting through data inconsistencies, particularly in hybrid data, can add a slew of confusing definitions and contexts that impact productivity and efficiency. With more valuable metadata than ever before at their disposal, organizations need a comprehensive strategy for metadata that helps them
Ensuring that third-party data in hybrid environments meets the quality standards many organizations follow for maintaining trust and confidence in their in-house data is imperative. Check out best practices for preparing, maintaining and monitoring third-party data to help boost efficiency and