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TDWI Upside - Where Data Means Business

Modernization and Government Analytics

If the MGT Act becomes law early next year, the focus on modernization could provide benefits for analytics across sectors.

The Federal Managing Government Technology (MGT) Act recently passed in the U.S. Senate and moved to committee for final adjustments. It was incorporated into the National Defense Authorization Act, finally bringing an initiative that began with the previous administration into the last stage of implementation.

The MGT Act is important because it provides funding and incentives as well as a mandate to modernize government systems -- which today cost about $52 billion per year, with 71 percent classified as legacy spending. The government sector is huge and its efforts are likely to drive interest in IT modernization across the country. The size of the systems will also create opportunities to improve modernization processes and bring legacy systems into a more secure and interactive operating state.

For Further Reading:

Why Data Warehouse Modernization Must be Coordinated with Other Modernization Projects

Cross-Border Data Restrictions and Your Cloud Strategy

Big Data and Analytics Spending Projected to Soar

Although the MGT Act does not address data analytics and data warehousing directly, it does focus on moving government solutions to the cloud and prioritizing the most critical modernization projects in government. Agencies will be required to create lists of high-value targets that can be achieved within a reasonable time and at a reasonable cost. With a security focus and cloud-based targeting, early projects are likely to include movement of data centers to the cloud and consolidation. Analytics modernization can yield important results at a relatively low cost compared to complete conversion of transaction systems.

Analytics modernization has been proceeding across sectors for some years, particularly under pressure from big data trends, the need to incorporate new types of data (such as unstructured social media), the need to incorporate new data storage techniques (such as Hadoop), and the growth of nonstandard database systems (such as NoSQL). Such initiatives could be among the low-hanging fruit federal departments undertake to improve operational efficiency and address security and accessibility issues, particularly by promoting interoperability among disparate federal IT data systems.

Analytics Modernization

The virtues of analytics modernization have been addressed in previous TDWI materials including last year's Best Practices Report, Data Warehouse Modernization in the Age of Big Data Analytics. A survey in the report concluded that the vast majority of respondents (91 percent) recognized the importance of modernizing data warehouses, with 58 percent feeling that modernization is "extremely important," and an additional 33 percent viewing it as "moderately important."

The federal government maintains extremely large data stores that are increasingly required to provide more real-time and interactive access as well as to coordinate with other data storage and data warehousing systems across the government. To date such interoperability has been problematic, but the MGT Act and initiatives such as the upcoming Report to the President on Federal IT Modernization could provide an opportunity to move forward in creating a more robust and efficient government data management system.

Of particular note: although the MGT Act involves only the U.S. federal government, all the states have IT initiatives that are likely to follow any trends in modernization that occur at the federal level.

The MGT Time Frame

If the MGT Act becomes law early next year, the focus on modernization could provide benefits for government analytics systems by increasing their responsiveness, increasing their efficiency, improving cybersecurity, and bringing new technologies to bear upon analytics problems. Increasing use of big data and real-time processing are priorities in the movement toward artificial intelligence and machine learning.

Ultimately, the velocity with which data can be entered into the system and analyzed is dependent upon architecture. Data systems will need to accommodate much faster processing of requests, more real-time data, and much larger stores of both structured and unstructured data. This will affect the underlying supplier structure of federal government systems and will bring new players, such as Amazon, into greater use in solutions that have previously been supplied in large part by systems integrators.

Modernization also means that critical legacy software must be revitalized and recast as more interactive and interoperable systems. Code conversion or movement to new software will require extensive planning and will come at a cost. Infrastructure change, though large in scale, is likely to have fewer contingencies and an easier focus as a starting point for modernization efforts. Analytics modernization could become a priority in the government effort. The net result will be to create greater visibility for analytics modernization efforts in general, due to the scale of government systems, as well as to build a body of best practices for these types of conversions.

About the Author

Brian J. Dooley is an author, analyst, and journalist with more than 30 years' experience in analyzing and writing about trends in IT. He has written six books, numerous user manuals, hundreds of reports, and more than 1,000 magazine features. You can contact the author at [email protected].

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