Playing Defense with Data Science and the Business Data Lake


John McKinney

September 11, 2015

The immense value of using a Business Data Lake proactively to enable business transformation has been well documented.  There are plenty of success stories, which highlight how data science and data lakes have been used to drive revenue, enhance operational efficiencies, or create new products and services, thereby driving business value. Using an American football analogy, this could be termed as “offense”.

But should data lakes and data science also be used for “defense”, to protect corporate assets?

In football, defense is the action to prevent an opponent from scoring. In business also, we must leverage technology to build a “defense” to protect information assets and protect ourselves against attack. We cannot escape the endless reports of the latest security breaches that result in immense damage. Every industry is at risk to criminals and state sponsored cyber attack –  think Target, Office of Personnel Management, and Ashley Madison to name a few. By putting all of your data in a single data substrate, you will be creating an enticing target for those who seek it. We have to develop new capabilities to defend against would be attackers, whether they are outside or inside threats.

Although we strive to make data lakes as productive as possible for users with self-service access and comprehensive metadata, we should also secure them using new Data Science techniques. Along with traditional security tools like access controls, intrusion detection, and encryption solutions to safeguard data against external threats, we must also protect the data from the inside out. This can be done by leveraging the same Data Science tools we use to create value. Data thieves act differently than real business users. Building real-time, predictive analytics to detect anomalous behaviors and take preventative actions can help strengthen our defense.

Anomalous Behavior Detection solutions apply advanced mathematical algorithms and machine learning to large data volumes to address IT security threats quickly, in real-time. The solution works to determine the difference between normal and suspicious behavior. It identifies anomalies and categorizes and prioritizes risks for further investigation. If needed, it will send real time alerts to highlight threats before they become critical. This rapid response will minimize exposure and loss of data. The Capgemini Anomalous Behavior Detection solution has helped a number of Fortune Global 1000 companies and Governments speed the deployment of these critical capabilities. This comprehensive protection focuses primarily on risks using advanced analytics capabilities that can be leveraged for the Business Data Lake as well as across all of your digital assets.
The value of Business Data Lakes continues to grow as they are used as an enabler of digital transformations. In many industries, in fact, building these new data substrates has become an imperative to stay competitive. Along with building great offensive capabilities – to drive revenue and enhance efficiencies – we must also build a great defense using the same techniques. The power of a data lake and data science should be used to fortify it and other digital assets. In this current hostile environment, an effective anomalous behavior detection system is an essential component of any big data strategy. Applying real-time, predictive analytics techniques enables us to shield the data lake from inside out, strengthening our “defense”.

This article was written by John McKinney from CapGemini: Insights & Data Blog and was legally licensed through the NewsCred publisher network.

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