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Data Terms Glossary

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Data Agility

What is Data Agility?

Data agility is an organization’s ability to move, manage and manipulate its data in order to meet the business demands of the moment. This agility must permeate all levels of data handling, as any bottleneck will stop up data movement and management everywhere downstream. 

Data agility must therefore include:

  • Agile data management
  • Agile data governance
  • Agile data modeling

What is agile data management?

Agile data management is when the processes and tools involved in collecting, storing and processing data enable flexibility and specificity in the way that different data assets are managed. 

If your data comes in different formats, is accessed at different intervals and for different use cases, then your methods of storing and processing it should not be “one-size-fits-all,” or you will be wasting resources and possibly confounding your data management and use.

Requirements for agile data management include:

  • Scalable, flexible data storage (cloud-based storage systems are the most natural option for this)
  • Fast, high-performance data access methods

What is agile data governance?

Agile data governance is a way for organizations to quickly adapt their data management and access controls to changing business situations and needs, while still maintaining data integrity and security.

These quick, focused adaptations necessitate collaboration and feedback from all involved parties, as well as a system that is flexible enough to initiate changes quickly. Also necessary is a balance of security checks and policies that will prevent inappropriate data exposure without causing bottlenecks in the data workflow.

In agile data governance, all governance policies are not seen as set in stone, but rather as “useful until proven otherwise,” welcoming critique, iteration and improvement. 

Requirements for agile data governance:

  • Collaboration between cross-functional teams to design policies and processes
  • A feedback and communication system that works effectively in all directions
  • An easy, intuitive way of tracking the journey of any data asset
  • A governance policy management system that can be modified

What is agile data modeling?

Agile data modeling is a practical approach to data modeling that democratizes data products and data analysis. Instead of making business users dependent on IT or data engineers for data products, the end-users are actively involved in the data product design process. Successful agile data modeling leads to more relevant business insights derived faster, by the people who need them and can (hopefully) put them into action.

Prerequisites for agile data modeling:

  • Focus on and understanding of underlying business processes
  • A data environment that can act as a shared workspace 
  • A culture of collaboration and cooperation
  • Intuitive self-service tools

Why is data agility particularly important today?

Business moves at a much faster pace today than it did decades – or even years – ago. Being able to accurately identify trends and changes and adapt to them is crucial for business success and longevity. 

The data that will reveal these critical trends and changes is likely lying within an organization’s data stores, but the ability to utilize it depends on the organization’s speed and accuracy in:

  • Locating the relevant data
  • Creating models that reflect accurate realities
  • Analysis that points to helpful conclusions
  • Pivoting the business to act on those conclusions

The organization that excels in this is the one that will stay the course, even in a tumultuous global business environment.

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