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Data Management/Governance Assessment and Roadmap

Many companies invest in technology only to find they are not getting the results they hoped for. Often this is because the holistic picture of data management/governance organization, processes and people have not been established to fully support those results. Sometimes the technology needs to be refined or upgraded to meet the business needs of the company/institution. Our assessment brings a holistic approach, grounded in the business goals that are dependent upon enriched, good quality data fit for purpose to be achieved. Our “Data Governance Light” approach guides us to focus on only those elements across the board that will make the most positive impact once addressed. From this assessment we build a prioritized roadmap that balances quick wins with important, measurable improvements.

AI Governance Assessment and Roadmap

You have assembled your data science teams and they are focused on targeted programming to build AI models. How do you ensure the data they are building with is trusted, vetted, matching standards for quality? How do you prevent the burning of these valuable resources in data wrangling that can take 50% of their time? How do you build integrity into their models that reflects your company’s principles of guarding against prejudicial outcomes? Governance for AI applies some of the same principles found in our DM/DG Assessment and Roadmap with special emphasis on supporting effective data science operations.

Data Governance and Stewardship Implementation

Guided by the roadmap we created in the first offering, we help stand up data governance and stewardship operations. Driven by our holistic approach, we help define and fill needed roles based on the style and scope of the first phase of these operations, then we aid in building education/training and with early operations. We finish the engagement when the company has become self-sustaining in the ongoing growth and maturity of these programs.

Data Management Technology Evaluation, Selection, and Implementation

Data management operations can be expensive if technology is not applied to aid in automating activities and processes. Coming out of the roadmap, if desired, we can build an evaluation process and aid our client companies in technology selection. Once selected we can aid in the oversight of implementation.

Setting Up Data Quality Operations

Once governance has been stood up, one of the first results can be to select and set standards for data important to prioritized domains and/or business processes. Once standards are established, the data in the enterprise can be evaluated for quality, and a plan to address important data quality gaps can be established. If the scale of the issues merit it, people, process and technology can be deployed to remediate data issues. This becomes an operation in its own right and is an extension of the data governance and stewardship, often with technology programmed to accomplish much of the remediation and stewards used to address exceptions and to check the quality of the remediation work. As in our other offerings, we help stand these operations up until they become self-sustaining.

Data Privacy Assessment and Roadmap

Data privacy regulations have been proliferating, impacting data management in U.S. and global operations. Sixteen states each have regulations that govern data of companies and institutions that have employees or customers in those states. More recently regulations concerning employee data have been implemented and are being assessed. This means that it is important to understand where this data is located and how it is protected is critical to avoid heavy fines, litigation and negative impact to the brand and reputation of the enterprise. We offer the ability to assess each company’s operations to understand where greatest risks exist and create a roadmap of interventions to remedy and manage each risk.