Big data is a bright spot in a tough market, and security, infrastructure and management are three keys to helping your customers succeed.
Big data and analytics are becoming increasingly important in federal IT spending. With reduced budgets and staff, government agencies have to rely more heavily on data analytics to help them accomplish their missions.
As a result, big data is one of the few bright spots in federal IT spending. An average of $2.3 billion a year is spent by agencies in gathering, processing, and disseminating data, according to the Department of Commerce Economics and Statistics Administration. The market intelligence team at immixGroup estimates a 5.85 percent compound annual growth rate (CAGR) for big data and analytics from fiscal 2014 to fiscal 2017.
This all translates to opportunities for commercial technology vendors – not just for analytics tools, but also for all of the accompanying services and technology that underpin big data.
SECURITY, INFRASTRUCTURE AND MANAGEMENT: BIG DATA’s BIG 3
Let’s take a closer look at three areas government agencies need to consider when implementing big data programs.
Security. With cybersecurity making the list of most government agencies’ top IT priorities, this is a perfect example of government agencies relying more heavily on data to accomplish their missions with less money. COTS vendors can help with big data projects that help agencies discover who can access their networks, and look at users’ behavior.
They can look at patterns in data to predict where and when access issues and insider threats may appear, and be proactive about protecting their networks. Networks are better defended with this type of situational awareness and predictive analysis.
Infrastructure and Storage. Because of dispersed storage infrastructures, government agencies often struggle with managing information on the scale required by big data. Early systems also may have been stovepiped, making database and systems integration difficult. To overcome storage limitations, agencies need converged or unified infrastructures and cloud solutions. COTS vendors have an opportunity to provide products that integrate this stovepiped information and offer the bandwidth, data access, and cost savings needed to properly implement big data.
Data Management. The government needs big data solutions to make data accessible over various databases, to create metadata and to use tagging to simplify data analysis. Data quality is also important. Agencies need to know they’re using the right data sets, which means being able to sort data to either keep and classify it or dispose of it.
Unfortunately, data cleansing is time-consuming and expensive. The government needs analysts to focus on analysis, not data management. COTS products for data management can help analysts spend more time on analysis and less time on cleanup. Those are just some of the key opportunities for big data sales and services. Of course, having the right products and services does not guarantee agencies’ success in big data implementations.
PLANNING FOR BIG DATA SUCCESS
Because this type of sale includes considerable consultation, it’s important to convey to government customers what they need to do to ensure their big data projects yield the intended results. Here are some basic steps for big data success.
Define project parameters. Big data projects need to be well-defined. Planning is really the essential element to a successful big data initiative. This means determining what big data can and cannot do for a project. Understanding those possibilities helps determine the scope of the project, and prevents mission creep during execution.
Examine current policies. Are outdated policies keeping an agency from using the right kinds of technologies? Since many of the challenges associated with big data projects in the government are cultural, agencies can combat resistance by pro-actively planning where data and information sharing will be an issue. This may mean adjusting long-established ways of doing things. In the long run, though, it allows wary groups to be better educated and engaged, which will make buy-in easier.
Get buy-in early. Getting buy-in from all involved groups and their leadership is critical to project success. That means regular communication with these groups as early in the process as is practical (as early as establishing policy, as we’ve seen above). It also means regular updates as the project is executed. That level of communication helps with cultural issues that may create adoption challenges, and ensures the project stays on track.
Track results, expected and real. It may seem obvious, but any successful big data project must have trackable performance measures. A project must have some idea of anticipated results, against which actual performance results can be compared. That’s the only real way to determine whether the project was a success, and to demonstrate that success to stakeholders.