Page 22 - GCN, August/September 2017

DATA ANALYTICS
BETTER ANALYTICS FOR BETTER OUTCOMES
The latest technologies can help agencies streamline their activities and
deliver greater value.
CHUCK YARBROUGH
VICE PRESIDENT,
SOLUTIONS MANAGEMENT AND MARKETING FOR PENTAHO DATA INTEGRATION AND ANALYTICS,
HITACHI
AGENCIES HAVE TONS of data, but they don’t necessarily know what to
do with all of it. Making data more actionable can improve agency leaders’ understanding, ultimately enabling them
to make more informed decisions and help achieve their agency’s mission.
Empower Non-Technical Users
Big data is complex, and many of the tools are IT-centric and complex as well. Fortunately, the technology is maturing and beginning to provide the tools that enable people to prepare data themselves for analytics.
Self-service analytics capabilities are now available to help users slice and dice data and create their own customized visualizations. Users can paint their own picture and create dashboards in exactly the format that makes the most sense for them—without requiring IT or data scientists to be involved. Machine learning capabilities are another way big data analytics solutions have evolved to help users find patterns in data and apply predictive algorithms that deliver more refined outcomes.
For example, take the former infantry soldier who is now a senior leader in the military trying to make sense of a mountain of logistics information. He understands the data, but doesn’t know how
to process/analyze it to make it actionable. These new tools make it easier for the user and the analyst to do just that.
Take a 360-Degree View
Data analytics can also help us get more out of existing assets. For example, IoT analytics, often times sourced from machine generated or sensor data, help monitor operations at a more effective level. By bringing together diverse data sources, a 360-degree view of a vehicle, aircraft, ship, or even military units is now possible. Leaders can then be confident that they have all the data they need to make important decisions and deliver the right outcomes.
It’s this complete view of data from connected devices that allows for accurate predictive analytics capabilities. For example, marine
fleets at sea are able to accurately analyze sensor data, identify patterns, and ultimately predict mechanical failures before they happen. If we can fine-tune the maintenance cycle for ships, planes, or even buildings, we can make repairs sooner and at a lower cost while extending the life expectancy of those major assets.
The return on investment for agencies implementing data analytics solutions can be measured via improving efficiency and saving taxpayer dollars. This is especially true when you consider a use case such as cybersecurity. By blending multiple data sets together and providing context to that data, agencies can reduce the amount of time it takes to detect an intrusion from months to hours, and in some cases, even minutes.
Solve Real-World Problems
Becoming a digital enterprise means being able to quickly capture and onboard data sources
at scale across a variety of locations. Once that data environment is in place, agencies can move toward advanced analytics, machine learning, and artificial intelligence to enable better business decisions, predict outcomes, and ensure they are delivering the most appropriate insight into operations.
In order to solve real-world problems, agencies must start by setting clear goals and build out a modern data architecture. From there, capturing, blending, and analyzing all data assets, including large data sets at scale, will enable organizations to gain a full picture of their operations, giving them the ability to predict outcomes that help deliver on mission goals.
Chuck Yarbrough is vice president of solutions management and marketing for Pentaho data integration and analytics at Hitachi.
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