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Enabling Big Data with Data-Level Security:The Cloud Analytics Reference Architecture


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; Booz Allen’s data lake approach enables agencies to embed security controls within each individual piece of data to reinforce existing layers of security and dramatically reduce risk. Government agencies – including military and intelligence agencies – are using this proven security approach to secure data and fully capitalize on the promise of big data and the cloud.

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Enabling Big Data with Data-Level Security:The Cloud Analytics Reference Architecture

  1. 1. The revolution in big data and cloud computing has ignited a “gold rush” to extract value from the mountains of digital information collected and stored by government and industry. The benefit to agencies and competitive advantage for business will be substantial. A significant challenge is that current data storage systems and processes were not archi- tected for the new cloud environment. In particular, conventional approaches make it difficult to bring together and analyze large data sets efficiently or securely. Moreover, as data stores get larger and more diverse, the challenges to integrating and protecting data will become even greater. Booz Allen Can Help You with Secure Cloud Solutions To help organizations overcome these challenges, Booz Allen Hamilton, a leading strategy and technology consulting firm, has pioneered an entirely new approach for implementing big data. Known as the Cloud Analytics Reference Architecture, this approach removes the conventional constraints and enables systems to accommodate petabytes of data and run analytics at previously unattainable scales—all securely, efficiently, and reasonably fast. This innovative approach allows machines to do the bulk of the work, freeing people to do the creative analysis. The Cloud Analytics Reference Architecture is built on the foundation of a “data lake” that facilitates both the unencumbered mixing of diverse data sets and rigorous data-level ­security. Unlike conventional approaches, which typically store information in rigid, regi- mented data structures, the Cloud Analytics Architecture ingests all data—such as struc- tured, unstructured, streaming, batch, classified, unclassified—into a common storage pool: the data lake. Using this construct, analysts can direct every inquiry to the entire data lake. Embedding Security within the Data The data lake not only facilitates more powerful analytic inquiries, it also enables the high levels of security required for storing and mixing data in cloud environments. As data enters the data lake, each piece of data is tagged with a range of security information—security metadata—that embeds security within the data. About Booz Allen Booz Allen Hamilton is a leading provider of management and technology consulting services to the US government in defense, intelligence, and civil markets, and to major corporations, institutions, and not-for-profit organizations. Booz Allen is headquartered in McLean, Virginia, employs approximately 25,000 people, and had revenue of $5.86 billion for the 12 months ended March 31, 2012. (NYSE: BAH) For more information contact Jason Escaravage Principal 703-902-5635 Peter Guerra Senior Associate 301-497-6754 S T R A T E G Y & O R G A N I Z A T I O N | T E C H N O L O G Y | E N G I N E E R I N G & O P E R A T I O N S | A N A L Y T I C S Enabling Big Data with Data-Level Security The Cloud Analytics Reference Architecture
  2. 2. The metadata tags can control or prescribe every aspect of security. And the number of tags is virtually limitless. The metadata tags can control (or prescribe) who can access the data, when they access the data, what networks and devices can access the data, and the regulations, standards, and legal restrictions that apply. Organizations can also use the security tags to define other parameters and restrictions. For example, the tags could contain the dimension of time, thus helping organizations maintain the integrity of the data and record changes over time. Similarly, the tags could allow certain people access to all historical data while limiting others to just the most recent data; or the tags could embed an expiration date on the data. The security tags work in concert with—and reinforce— cyber defenses already in place in areas such as identity management, configuration manage- ment, and compliance. By tagging data with security controls as it enters the data lake, organizations can implement an unprecedented level of data security within the cloud. The security resides within and moves with the data, whether the data is in motion or at rest. As a result, organizations can confidently mix multiple data sets and provide analysts with fast and efficient access to the data, knowing the security tags will remain permanently attached to the data. In the data lake, security becomes an “enabler” of big data analytics to power insights and ­solutions addressing our nation’s most pressing social, political, and economic challenges. See our ideas in action at 12.032.12N Streaming Indexes Human Insights and Actions Enabled by customizable interfaces and visualizations of the data Analytics and Services Your tools for analysis, modeling, testing, and simulations Data Management The single, secure repository for all of your valuable data Infrastructure The technology platform for storing and managing your data Services (SOA) Analytics and Discovery Views and Indexes Data Lake Metadata Tagging Data Sources Infrastructure/ Management Visualization, Reporting, Dash-boards, and Query Interface Reference Architecture