Big Data and Analytics

Master the four dimensions of big data: Volume, Velocity, Variety, and Veracity

Contribute to big data and analytics open source projects. Now available on IBM developerWorks Open.

Learn from our experts

Real-time analytics

Do real-time analytics with the VoltDB database in IBM SoftLayer

Learn how cloud environments can be suitable for doing real-time analytics on big data. A step-by-step example shows you how to install VoltDB and run a sample VoltDB application in the IBM SoftLayer cloud.​


Create SQL reports from a NoSQL database

Use services in IBM Bluemix to generate SQL-based reports from JSON data stored in a Cloudant NoSQL database.​

Business Intelligence

Use IBM SPSS Statistics for business intelligence, Part 1: How to generate tables, graphs, crosstabs, and statistics

This first article in the series introduces sample raw data and generates frequency tables, graphs, crosstabs, and statistics. Business-level conclusions from statistical analysis are also explored in this article.

Sentiment analysis

Perform sentiment analysis in a big data environment

Sentiment analysis can be performed against data that is gathered from disparate sources (tweets, RSS feeds, and mobile apps). This data can be aggregated, transformed, or reformatted and then stored in a Hadoop Distributed File System (HDFS).


Use the IBM z13 SIMD unit and the IBM z/OS XL C/C++ compiler to add parallelism to your C/C++ programs

The IBM z13 hardware provides a new SIMD unit. Learn how to use the IBM z/OS XL C/C++ language to take advantage of the new processor and exploit the enhanced parallelism it offers.

Predictive analytics

Develop a predictive analytics model

Gain a richer understanding of the analytics services in dashDB while exploring a Kaggle data mining competition.