As the data used by an enterprise grows in size, variety and importance, it is no longer acceptable that the gathering and maintenance of metadata remains an under-funded and neglected afterthought for data-driven organizations. Metadata management needs to become a key focus of an organization's
Whether organizations want to extract customer data beyond names and addresses from unstructured data sources; pull specific dates, times or monetary amounts; predict trends from sentiment data; or engage in many other uses, text analytics is the way to go. Learn the details of text analytics, and
Data science takes collaborate teams of data scientists engaging in productive, open data development initiatives that can ensure strong workflow, governance, security and management. See why open environments are revolutionizing the data science landscape.
A growing number of businesses and industries are finding innovative ways to apply graph analytics to a variety of use-case scenarios because it affords a unique perspective on the analysis of networked entities and their relationships. Gain an understanding of how four different types of graph
Discover what happened when a developer and a data scientist joined forces to create an exciting new app—and why the lessons they learned are spurring collaboration among data professionals everywhere.
Spark just seems to be getting big play everywhere in the technology arena. What is Spark? And do you need it? Get a good glimpse into its in-memory execution capabilities, some of its key components, its integrations and its availability as a service.
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?
The open source Hadoop framework accommodates distributed storage and processing of large data sets on clusters of computers through the use of programming models. If that description sounds complex, then dig into this breakdown of Hadoop components to gain an understanding of just how flexible
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
This short series of blogs for the business user is designed to turn key technologies into easy to understand concepts to help explain why they are needed in a modern digital enterprise. When looking at consumer and business transactions in today’s online world, many people may ask, “Why big data
The rapid rise of the Internet of Things requires a new breed of developer. Often moonlighting to develop solutions that are transforming the Internet of Things, many of these developers have day jobs in a wide array of disciplines. And their job titles can range from application developer to
An open ecosystem thrives on a mature core platform. It also depends on partnering arrangements that incentivize solution providers to continue developing standards-based interoperability around the shared environment. Take a deeper dive into recent announcements of new open ecosystem milestones
A variety of organizational roles interact with business data, and each role faces its own particular challenges in collaborating with its IT counterparts. In this installment of the InsightOut series, learn more about the responsibilities of these personas, exploring the considerations that govern
Exploiting external, cloud-based data can bolster competitive advantage for cognitive businesses, but combining it with internal, business-outcome data brings challenges. Consider several actions that organizations can take using cloud data services to capitalize on the value of external data.