Reimagine the data science experience as an open experience with this IDE, which aims to facilitate a full range of development tasks, from data acquisition and data mining to prototyping and programming. When you do, discover how you can use Apache Spark and R to pursue open analytics by building
A world that grows increasingly complex calls for disruptive innovation in an open, collaborative environment. See how open data science provides an ecosystem of expertise, skill sets and advanced open source data science tools that fuels collaborative creativity in the development and deployment
Use open-source tools to supercharge the data science lifecycle, giving data science teams a boost as they work to provide compelling results in the complex team environments that mark modern corporations. Learn how you can make open data science an ongoing part of your business environment when
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
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
Businesses can benefit enormously from analysis-derived rules that enable understanding why certain events occur and the corresponding actions to take. Learn more about a widely used six-phase methodology for building predictive analytics models that can reveal hidden rules for meaningful business
The really cool thing about big data and multiple data sources for today’s advanced, web-based applications is that a variety of open source databases can provide specialized support for different application components. If you’re involved in application development, discover why achieving polyglot
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.
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.
Open source is a disruptor that never quits. It seems to be penetrating and transforming every aspect of established data, analytics and application ecosystems. In this podcast, recorded at IBM InterConnect 2016, listen to David Taieb, a cloud data services developer advocate at IBM, share his
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.
Graph database technology powered by open source initiatives is helping fraud detection units catch intruders in the act of breaching data security. Tune in for an enlightening discussion of how modern approaches to analytics are bringing descriptive and predictive analytics together to help stop
Open source is a disruptor that never quits, and it seems to be penetrating and transforming every aspect of established data, analytics and application ecosystems. In this podcast, recorded at IBM InterConnect 2016, listen to Kamille Nixon, portfolio marketing manager at IBM, share her expert
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