Pro Tips for Using Data Analytics
Here are some tips from our GovLoop community about incorporating data analytics into your agency operations
Here are some tips from our GovLoop community about incorporating data analytics into your agency operations
“The way forward for developing modern analytics capabilities in the cloud requires an agile approach,” said Michael Kennedy, Director of Public Sector Cloud Strategy at Catapult. “While there are times when it is necessary to build big to accommodate massive amounts of information, that is the exception, not the norm.”
Based on feedback from our data analytics survey, several agencies are developing capabilities in-house. Others are using cloud-based, open source and custom-built tools. So what’s the best option for your agency?
In order to create metrics that serve the organizational programs that ultimately serve the business, keep these tips in mind.
Don’t get too bogged down by the ways of the past, but don’t try to start all over when implementing a sustainable mindset in your community. It really is all about balance, and using the tools that are out there to improve your city’s capabilities.
Commerce rolled out a pilot program in spring 2016 to help educate and empower its employees to make data-driven decisions.
Whether it’s business intelligence or data warehousing, the cloud allows organizations to shift away from managing their infrastructure to put more of their time and resources into their core missions.
Although they’re not an entirely new undertaking in government, many program offices, sub-agencies and even larger departments are still working through strategies to fully embrace analytics.
By now most local governments are familiar with and are working towards implementing smart cities programs. However, some cities are taking it one step further and are transforming their community in a sustainable way. Check out how you can utilize sustainable innovation in your local government.
A variety of market drivers have brought government to the tipping point of needing critically improved data analytics.