Data Strategy Consulting

Data privacy is paramount. There has always been an ethical duty to protect your customers’ data. Now, these ethics are enforced through a cadre of regulations attached to penalties.​

Some of the most common violations of data privacy occur through exposure of data within your organization. Mitigating this risk requires thoughtful design of your security through role-based access control (RBAC) and row-level security.​​

Your data strategy will recommend an approach to securing your data and controlling its distribution across the enterprise.

If the data strategy’s connection to the overarching business strategy is not clear, then it likely does not exist. The data team may be viewed as a cost center and little more.​

Data can be more than a supporting pillar for the business. Process automation can drive cost out of operations. Artificial intelligence can improve business outcomes. Decision support can bolster performance of your workforce.​

Your data strategy should consider how to generate profit, create market advantage and reduce operating costs.

Does your IT backlog for data and reports span into months? This scenario may result from an inefficient architecture where all data requests must go through a data warehouse. Other times, this can be caused by insufficient reporting team bandwidth. Every organization faces a unique set of challenges when it comes to IT and data.  ​

Your data strategy will help you optimize your IT operations and you may be surprised at how modern technology can change the game. We bring a unique perspective on how modern organizations are democratizing data accessibility.

Mastering the terminology of your organization is a crucial step that touches reporting and analytics. Linguistic clarity makes a difference because communication between departments is critical. This is the foundation of good data governance.​

Your data strategy will identify how data governance greases the skids to increase value obtained from data. Data governance maturity is a long journey, but one that can quickly pay dividends when correctly approached.​

You probably know the risks: stakeholders often do not understand how to join and filter data; business rules may need to be applied to data to make it accurate and useful; and everyone is prone to generate different answers to the same question.​

Modern data organizations have addressed this problem with data catalogs, data governance, data lakes and master data management. Your data strategy will tie these pieces together, allowing you to broadly and securely share data throughout the enterprise.

Accuracy of reported data is a concern shared among all organizations. Accuracy must first be clearly defined, and after that, the data must work to produce accurate results from base data sets. All of this requires clear data governance and clear expectations of definition.​

Your data strategy will address the method for ensuring that data accuracy is sustained even after code is deployed to production. This requires a robust testing strategy for ETL, data transformations and reports. By adopting modern data testing practices, you will be in an elite group.

Data Strategy is about getting the people, process, and tools around data aligned and structured to help your organization meet its business goals.

This starts with understanding what you want to accomplish with your business. Then learning what you can currently do with your data and technology architecture to support those goals.
We work with you to identify needed skills and skill growth opportunities for your team and then align, prioritize, and plan recommended initiatives to achieve your goals.

Data initiatives are often complimented by elements of Modern Software Delivery, People and Change, and Business Process Improvement.

The best way to start your data governance initiative is to apply a data maturity model.

This model acts as a benchmark upon which you can review your current IT landscape and how well you manage your data against your people, processes, and technology — or all three combined.

The idea is to compare your current state to the desired state, which is predicated on your company goals and mission.

Once you understand where you are today, you will have a clearer picture of the policies you must implement to become a more data-driven company.