Big Data Analytics

Employ the most effective big data technology

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What is big data?

Big Data is being generated at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it. Much of this data is coming to us in an unstructured form, making it difficult to put into structured tables with rows and columns. To extract insights from this complex data, Big Data projects often rely on cutting edge analytics involving data science and machine learning. Computers running sophisticated algorithms can help enhance the veracity of information by sifting through the noise created by Big Data's massive volume, variety, and velocity.

Volume - Scale of the data

The ability to process large amounts of data and what you do with that data.

Variety - Different forms of data

Making sense out of unstructured data by trying to capture all of the data that pertains to our decision-making process.

Velocity - Analysis of streaming data

The rate at which data arrives at the enterprise and the time that it takes the enterprise to process and understand that data.

Veracity - Uncertainty of the data

The quality or trustworthiness of the data. The quality or trustworthiness of the data. Tools that help handle big data’s veracity discard “noise” and transform the data into trustworthy insights.

Use Cases

Data Science Sandbox

Data Science is an interdisciplinary field that combines machine learning, statistics, advanced analysis, and programming. It is a new form of art that draws out hidden insights and puts data to work in the cognitive era.


Data Lake Analytics

A data lake is a shared data environment that comprises multiple repositories and capitalizes on big data technologies. It provides data to an organization for a variety of analytics processes.


Streaming Data / IOT Platform

Stream computing enables organizations to process data streams which are always on and never ceasing. Stream computing helps organizations spot opportunities and risks across all data.




One key capability is SQL querying and this is where IBM Big SQL comes in as a data virtualization tool that lets you access, query, and summarize data from any platform including databases, data warehouses, NoSQL databases, and more. Big SQL concurrently exploits Hive, HBase and Spark using a single database connection — even a single query.


IBM Analytics for Apache Spark

Increase your analytics agility with the power of open source Apache Spark. Process large data volumes at great speed in a hosted, managed, secure environment.


IBM Cloudant

Give your application uninterrupted data access, offline and online, anywhere in the world, with a fully managed NoSQL database service. Let IBM manage the database layer so you can build more, grow more and sleep more.


IBM Streams

Helps to capture and analyze streaming data, make decisions while events are happening. IBM Streams offers a complete solution with a development environment, runtime and analytics toolkits.


IBM Data Science Experience

Cloud-based, social workspace that helps data scientists consolidate their use of and collaborate across multiple open source tools such as R and Python.


IBM InfoSphere Big Match

Helps analyze big volumes of structured and unstructured data to provide complete and accurate customer information—without increasing risk of errors or data loss when moving data from source to source.


IBM BigIntegrate

A data integration solution that provides connectivity, transformation, and data delivery features that execute on the data nodes of a Hadoop cluster.


IBM BigQuality

Helps ensure information quality and provides the ability to quickly adapt to strategic business changes by stewardship and monitoring of data and application of data quality rules for your Hadoop data.


IBM Information Governance Catalog

Provides comprehensive information integration capabilities to help you understand and govern your information.



Data scientist

With connected devices and social media transforming the way people live, work and buy, today’s data is increasingly “born in the cloud.” Capturing the true value of data means acting fast with the latest analytic tools and spending less time managing your infrastructure.


Application developer

Use powerful, open source database technologies to power your apps—providing flexibility, scalability, and geospatial capabilities in a fully managed service. Make your web and mobile applications more scalable and available to users, wherever they are.


Enterprise architect

Modernize and extend your online transaction processing (OLTP) databases and data warehouses to a hybrid cloud architecture. Business users can gain valuable insights easily and more cost-effectively with the most complete and integrated set of data and analytics services.