Why your data management strategy needs integrated analytics

 

Connecting state and local government leaders

Analytics embedded at the start of data management initiatives ensures analysis and insights are clear, relevant and actionable.

In June 2019, the Office of Management and Budget released the Federal Data Strategy, developed, along with other data management strategies, to help agencies more fully leverage their data as a strategic asset by supporting strong data governance and providing the protection and security that the American people, businesses and partners deserve.

Data analytics must be a core part of these strategies. When designed and governed correctly, data analytics enable agencies to rapidly sift through volumes of backup, archived and other “dark” data to find actionable intelligence they can use to lower storage expenses, streamline operations and improve how they deliver services to citizens.

Federal, state and local governments historically considered data analytics a “nice to have” part of their data management capability and often limited its use to the data collected for specific, authorizied use. Thanks to mass digitization and new technologies, agencies now realize that data analytics are no longer a luxury but instead must be a core aspect of their data management strategies. Without analytics, the ever-increasing volume, velocity and variety of data, coupled with increasing security, compliance and privacy regulations, would overwhelm organizations rather than improve their efficiency. With data analytics embedded into data management applications, agencies lay the foundation for actionable insights and greater efficiencies, rather than just overwhelming analysts with the tsunami of data available.

As agencies embark on IT infrastructure consolidation and cloud migration initiatives, embedded data analytics offer an opportunity to improve the speed and efficiency of these initiatives by discovering redundant or incorrect data that should be cleaned or deleted prior to migration. Data analytics can also identify personally identifiable information and data subject to privacy regulations that must be managed with greater controls and safeguards. Automating business rules, policies and procedures supporting the data analytics reduces the direct human intervention required to achieve compliance and efficiencies.

Look for data management solutions with built-in data analytics

Government agencies are turning to data management solutions to help them gain insights from their massive stores of data. These solutions are often closely linked to a specific data type and ensure the availability and recovery of the data. Data analytics embedded into a data management solution intrinsically delivers better analysis based on its deeper understanding of the type of data and its  context. Data analytics tools that have been bolted onto data management solutions add unnecessary complexity and require additional skills to manage. Often, attaching a separate data analytics capability increases the risk of configuration incompatibility as business processes change or scale. Additionally, a stand-alone data analytics tool might not be updated on the same schedule as the core data management solution, requiring work to reintegrate the tool with the solution when either is updated.

Use data analytics at the start of data management processes and initiatives

Data analytics should be a foundational aspect of an organization’s data management strategy. Integrating data analytics from the outset ensures that early lessons learned from collecting, migrating or otherwise managing the data are captured in an iterative manner, enabling agencies to gain actionable insight.

Cloud migration provides an excellent example of the value of embedded data analytics. By analyzing their data as part of the migration process, agencies can make decisions about data based on its age, the program or department it is tied to and the core organization process it relates to. Tags and indexes can capture each of these characteristics or elements, identifying data that can be deleted before the migration and categorizing the rest so it can be easily retrieved post-migration. Embedded data analytics also ensures the cloud service delivers the performance agency requires. Embedding the analytics up-front allows agencies to see how their data is likely to grow in the future so they can ensure their new cloud service will support this growth.

Make data analytics insights clear, relevant, and actionable

The best data analytics technology in the world is of no value if it is not providing clear, relevant and actionable insights to agency decision-makers. Real time use of data analytics gives decision-makers a continual feedback mechanism so they know they are analyzing appropriate data, in the right way. Insights from this analysis can easily be presented in a way decision-makers can quickly understand and act on. In some cases, this feedback will result in changes in the datasets being analyzed or changes in the insights requested.

As long as an agency’s data management solution offers analysis capabilities that are flexible and configurable, and decision-makers have decided how they will use analytics to generate and present insights, the agency will be able to make its data analytics resilient, providing valuable insights not just to decision-makers today, but also to tomorrow’s leaders facing different challenges and opportunities. 

By using data management solutions with embedded analytics, by bringing data analytics in at the start of all their data management initiatives and by working closely with decision makers to ensure data analysis insights are clear, relevant and actionable, agencies can set themselves up for success. Data analytics strengthens data management strategies in ways that help agencies better accomplish their missions.

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