Maximizing Big Data: Booz Allen Shares 5 Tips for Federal Agencies

Maximizing Big Data: Booz Allen Shares 5 Tips for Federal Agencies

tweet me:
How can federal agencies maximize the #BigData they collect? @BoozAllen shares tips with @insideBigData http://bit.ly/2SkvHbd

Multimedia from this Release

David Cunningham, principal at Booz Allen

Christopher Brown, senior associate at Booz Allen

Friday, February 8, 2019 - 10:45am

CONTENT: Blog

From government spending figures to public health statistics to geospatial imagery, the federal government is gathering, storing, and sharing more data than ever. Agencies have started consolidating this information into big data platforms for analysis and decision-making. But often such a “data lake” threatens to become a “data swamp” that slows agencies’ growth and progress.

What’s holding agencies back? First of all, it’s hard to combine, work with, and analyze data that comes in various sources, formats, and types—especially given the strict security and privacy regulations federal agencies need to follow. People trained in data science are often in short supply and expensive to hire. Moreover, 60 percent of big data initiatives overall fail—often because organizations failed to first define the problem they were trying to solve.

In a recent issue of InsideBIGDATA magazine, Booz Allen Senior Associate Chris Brown and Principal David Cunningham provided five tips for moving from “data lakes” to actionable insight.  

  1. First identify the problem. What does your organization aim to do with its data lake? To what degree will it need to scale? The answers to these questions will guide data collection, security, cloud infrastructure, and more.
  2. Define and secure the data. To get diverse forms of data ready for analysis, you’ll need metatags for aggregating and processing and attributing authorization schemes for security.
  3. Make information easier to find. Agencies can catalogue and organize information into various zones: raw and trusted data (depending on whether it’s been quality-checked and tagged), data to be used for analysis, and data held in a “sandbox” for testing, prototyping, and exploration.
  4. “Democratize” data analytics. Data zones, self-service tools, and automation can help spread the analytics workload out to team members beyond highly skilled and specialized data scientists.
  5. Use Agile to accelerate progress. This methodology and culture can help organizations manage uncertainty, improve teamwork, and pivot quickly in big data projects.  

Read the full InsideBIGDATA article and learn more about how Booz Allen is using data science and analytics to help clients solve problems.