Blogs

Lean data science with Apache Spark

Lean data science with Apache Spark

May 25, 2016 | by Aaron Merlob, Executive Education Lead, Galvanize
One modern tool that supports a data-science-as-start-up philosophy is Apache Spark. The community behind Spark seems to be building the tool using these lean product principles.
Boosting the productivity of the next-generation data scientist

Boosting the productivity of the next-generation data scientist

May 24, 2016 | by James Kobielus, Big Data Evangelist, IBM
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...
InsightOut: The case for open metadata and governance

InsightOut: The case for open metadata and governance

May 20, 2016 | by Mandy Chessell, Distinguished Engineer, IBM Analytics Group CTO Office, IBM
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...
What is text analytics?

What is text analytics?

Making the complex simple

May 19, 2016 | by Mike Ferguson, Managing Director of Intelligent Business Strategies Limited, Intelligent Business Strategies Limited
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...
It takes a team: Collaboration and workflow in open data science

It takes a team: Collaboration and workflow in open data science

May 19, 2016 | by James Kobielus, Big Data Evangelist, IBM
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.
Spark and R: The deepening open analytics stack

Spark and R: The deepening open analytics stack

May 19, 2016 | by James Kobielus, Big Data Evangelist, IBM
As Spark continues to mature into mainstream adoption in the data science community, the open data analytics stack and open source tools grow more robust, giving data scientists rich core workbenches to develop evermore innovative applications.
Why a cloud first strategy can benefit customers with IBM BigInsights on Cloud

Why a cloud first strategy can benefit customers with IBM BigInsights on Cloud

May 17, 2016 | by Dinesh Nirmal, Vice President, Next Generation Platform, Big Data & Analytics on z, IBM
With BigInsights having established itself as a leader and with IBM focused on a Cloud First Strategy, we saw the opportunity to help customers reduce these capital and management costs, to enable them to focus on running the analytics for business advantage while providing BigInsights on a dynamic...
What is graph analytics?

What is graph analytics?

Making the complex simple

May 17, 2016 | by Mike Ferguson, Managing Director of Intelligent Business Strategies Limited, Intelligent Business Strategies Limited
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...
What is machine learning?

What is machine learning?

Making the complex simple

May 11, 2016 | by Mike Ferguson, Managing Director of Intelligent Business Strategies Limited, Intelligent Business Strategies Limited
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...
Bridging NoSQL databases into open data science initiatives

Bridging NoSQL databases into open data science initiatives

May 10, 2016 | by James Kobielus, Big Data Evangelist, IBM
As a foundation for data lakes and refineries, NoSQL databases provide access, processing and storage to structured and unstructured data for high-performance statistical modeling and exploration. Take a look at the multitude of advantages of NoSQL databases and opportunities to bridge them to open...

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