Historical application of vector mathematics and the study of unstructured text data can be an important approach to understanding and actualizing the value of data. See how mathematical exploration of text data can unearth insight that translates into enhanced decision making.
Although formerly exclusive to the IBM Hadoop Platform, the extension of Big SQL to the Hortonworks Data Platform (HDP) meets the challenge of complex data warehousing queries on Hadoop. See what Paul Yip, worldwide product strategy for Hadoop and Spark at IBM, has to say about what this transition
Chris Snow, a data and application architect, enjoys helping customers with their data architectures and is working extensively on an open source app project in his spare time. Hear what Snow has to say about his IT experience spanning several industries, his current efforts with customers and his
The future of cognitive computing is bright and Chief Data Officers have the chance to lead the way for their organizations. Not just a science-fiction dream, machines that are experts, expressive, educated, and evolving have the potential to create a stunning reality by driving meaningful market
Now introducing the “Insight Ops” model. This new model will embrace and enable an agile environment for discovery and exploration and manage the transition necessary to deploy the insight to make it actionable.
Don’t let your business come to a standstill as a result of technical debt. Discover how a decision debt approach to tools and analytics help overcome the quick-fix solutions that contribute to technical debt and its impact on business.
Data scientists and others often encapsulate big data by its dimensions known as the four Vs: volume, variety, velocity and veracity. But when considering big data as a source for insight to enhance decision making, it may be best characterized by its three Cs—confidence, context and choice—with
Ubiquitous data is so easily generated, and for that reason many enterprises today are exceedingly challenged to handle it all successfully. Take a look at a comprehensive information lifecycle governance solution that can help prevent enterprises from becoming submerged in their own sea of data.
What five ongoing challenges often face companies who are planning to move data to the cloud? Learn how to rescue your data while increasing efficiency, reducing costs, meeting regulations and reducing risks.
Deriving actionable insight from data and analytics is shifting to unified, cloud-based platforms that can be used by a variety of analysis personas. Take a look at a national retail chain scenario demonstrating how a comprehensive portfolio of end-to-end analytics in the cloud can provide the
How do you handle your semi-structured data? In this whitepaper from IBM Cloud Data Services, find out how keeping your data warehouse on the cloud can help you gain the competitive advantage by freeing valuable resources.
Open source is a disruptor that never quits, and it is seemingly penetrating and transforming every aspect of established data, analytics and application ecosystems. Give this podcast, recorded at IBM InterConnect 2016, a listen to learn how open source initiatives are transforming machine learning.
Organizations today have tremendous opportunities to transform their professions, businesses and industries. They must optimize their use of advanced analytics and capitalize on all available data. With the right solutions, they can gain clarity about their business, generate new insights and take