Blogs

Who are today's analytics professionals?

Who are today's analytics professionals?

May 27, 2015 | by Pavel Abdur-Rahman, Senior Managing Consultant, IBM
Discover nine fields of study for corresponding data analysis professionals that contribute significantly to analytics projects, their key value propositions and challenges and high-level suggestions for categorizing and organizing the rapidly growing analytics resource pool.
How to get started with Apache Spark today

How to get started with Apache Spark today

May 27, 2015 | by James Kobielus, Big Data Evangelist, IBM
An increasing number of use cases for big data and analytics can be Apache Spark's sweet spots. Take a look at several low-latency applications in which Spark is well-suited for analysis of cached, live data.
Spark insights from the recent Cambridge meetup

Spark insights from the recent Cambridge meetup

May 21, 2015 | by Monica Fox, Content Marketing Manager, Emerging Markets, IBM
See why Spark has has grown rapidly and evolved into a more mainstream technology in this insightful report about a recent meetup in Cambridge, MA.
Machine learning as a fluid intelligence harvesting service

Machine learning as a fluid intelligence harvesting service

May 20, 2015 | by James Kobielus, Big Data Evangelist, IBM
Many machine-learning-as-a-service (MLaaS) offerings have natural language processing at their core to support applications such as concept expansion, language identification, machine translation, user modeling, visualization rendering and more. Discover how MLaaS boosts productivity by uncovering...
Taking the next step toward text analytics

Taking the next step toward text analytics

May 18, 2015 | by Jacques Roy, WW Technical Sales - Big Data: InfoSphere Streams, Informix TimeSeries, IBM
Even when learning a new language, becoming fluent within certain contexts can be easier than other contexts. When analyzing textual data, context is imperative to understand that data. And like corpora developed for linguistics research, a simple and straightforward conversion of textual data...
Geospatial analytics: Uncovering insights not found in charts and tables

Geospatial analytics: Uncovering insights not found in charts and tables

May 11, 2015 | by Mikhail Lakirovich, Product Marketing Manager, IBM
Predictive analytics that incorporates geospatial data can provide answers and insights not found in charts or tables, and it can be extremely helpful for organizations that want to answer the critical who, what and where questions for accurate forecasting.
The emergence of a new data science hero

The emergence of a new data science hero

May 4, 2015 | by Mikhail Lakirovich, Product Marketing Manager, IBM
Demand for data scientists is growing. Strong analytical skills and the ability to tap into the expertise of the larger analytical community helps new and seasoned data scientists keep up with new trends and continue to hone their skill sets.
The resurgent relevance of the data warehouse

The resurgent relevance of the data warehouse

April 23, 2015 | by James Kobielus, Big Data Evangelist, IBM
The data warehouse has never been more relevant than it is now. The DW’s role in the big data universe appears likely to grow. What the DW does, above all else (and this is far from its only role in many organizations) is serve as hub for governing your system-of-record data to be delivered into...
Machine-milled insights and the limits of algorithmic automation in cognitive computing

Machine-milled insights and the limits of algorithmic automation in cognitive computing

April 23, 2015 | by James Kobielus, Big Data Evangelist, IBM
Machine learning is a tool for making humans more productive. Machine learning methods vary in degrees of automation. Regardless of how one performs machine learning, data scientists must still prepare the data sets, specify the algorithms, execute them and interpret the results. The process of...
Develop a better world with Hadoop

Develop a better world with Hadoop

April 3, 2015 | by Jason Burns, ITSO Social Business Manager, IBM
How would you save the world? That’s the question we posed to the development community several months ago when we launched our Hadoop4Good Campaign.

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