Data Catalog Strategy

Operationalizing data governance for a successful data-driven transformation

To remain competitive on today’s market, the availability and quality of corporate data is a business-critical resource. That is why most organizations have already launched a large-scale transformation strategy on the way to becoming their vision of what it means to be a data-driven company. The success of this endeavor ultimately depends on each company’s ability to affect change in its existing data management, value creation, governance, culture, and IT architecture. As an enterprise-wide and therefore highly complex undertaking, your transformation needs tangible and measurable quick wins right from the start to keep stakeholders involved, motivated, and engaged.

Operationalize data governance to put quick wins on the scoreboard

Data governance is a good place to start in any data-driven transformation. After all, there is no way to get your data strategy and use cases off the ground without the right mindset and the right technology. And yet, many data governance initiatives never make it past the conceptual phase, much less deliver valuable contributions to the broader transformation goals. Operationalizing your data governance model will give you an opportunity to establish fully functional governance structures and processes.

Standardized software for metadata management, widely known as a data catalog, has the key features you need to embed data governance within your organization. A data catalog is the single point of truth for managing and retrieving enterprise data assets, which will foster data literacy and enable data democratization throughout the enterprise. 

Deloitte has the right data catalog strategy for your requirements and goals

Many enterprises find it extremely challenging to introduce a data catalog as part of their transformation project. With vastly different requirements and data governance models in each individual transformation context, scoping, selecting, and preparing a data catalog solution can be a complex undertaking. Add to that the massive number of data catalog models you must build to meet your organization’s needs, and the process becomes even more daunting. These models range from standalone spreadsheet-based catalogs for specific business contexts to highly integrated systems at enterprise scale. 

It isn’t easy to get it right when you operationalize a data governance model. In the end, choosing the right or the wrong data catalog could make or break the process. Using a holistic data catalog strategy with all the details and specifics of your broader data-driven transformation program will enrich and align your operationalization endeavor and make both transformation and data governance a success.

Find out more on "Data Catalogue Strategy" in our Whitepaper.

Approach to identify your data governance objectives

The first step is to identify your data governance goals and requirements and then align them with your broader corporate and IT strategy. The ultimate goal is to find effective ways to operationalize data governance and put some quick wins on your transformation scoreboard. A robust data catalog strategy involves selecting the right vendor products, preparing for implementation, embedding the solution within the enterprise, and setting up a roadmap for metadata management. This will ensure your data catalog solution has the features you need, can be successfully implemented, and delivers benefits for business stakeholders. 

To find the data catalog solution that is right for your transformation requirements, we recommend a four-phase strategy:

  1. Screening: Gain a clear understanding of your transformation and data governance goals and identify which use cases are most critical for your enterprise. It is good practice to involve relevant stakeholders at this early stage to assess their data governance maturity and better understand the kind of metadata management support they need.
  2. Scoping: Define a vision and mission for your data catalog solution and conduct a fit-gap analysis to discover the metadata management features you need, before starting to identify different data catalog models, prioritize critical use cases, and create a target architec-ture blueprint.
  3. Sourcing: Conduct a utility-benefit analysis, test products in proof-of-concept sessions and use a business case evaluation to select the data catalog products that best meet your transformation requirements and close any functionality gaps that remain.
  4. Setting: Draft a comprehensive data catalog roadmap and create an initial product backlog in preparation for the implementation of your target solution’s functionality and features. Finally, document the main features of your chosen model to ensure all participating stakeholders can make the most of every interaction.

Start creating value for your data-driven transformation today

Adding a data catalog to your transformation can make everything significantly more complex, so it is in every company’s interest to come up with a viable strategy early on. However, with different business agendas, scarce resources, and varying levels of maturity, no two companies will have the same transformation priorities. That is why it is so important to choose a data catalog strategy that is aligned with the status and the maturity level of your particular transformation program.

Value-add for the data-driven enterprise

With the right strategy in place, you can make sure your data catalog solution is closely aligned with the transformation program and its data governance design. These are the key advantages you can expect with our data catalog strategy:

  • Business value: A robust data catalog strategy identifies high-quality use cases that meet your company's needs and ultimately provides a metadata management solution that adds value today and in the future. While each transformation and governance model will have its own key use cases, we offer a generic yet valuable set of use case templates to support every context.
  • Financial advantage: To minimize costs and maximize returns, you need to choose the right data catalog solution as soon as possible. Deloitte's approach helps you identify the solution that best meets your enterprise’s needs, saves time and money, and reduces technical debt over the long term.
  • Organizational success: Our strategy aligns your targeted data catalog solution closely with your corporate goals to ensure its utility. The solution’s strategic roadmap and service operating model ensure that it can be efficiently embedded within the organization and effectively used as you evolve into a more data-driven enterprise.

Value-add for corporate leaders

Data-driven transformation impacts those corporate leaders in particular who are responsible for the effective management and utilization of enterprise data as an asset. A coherent data catalog strategy can give them the support they need to reach their transformation goals. C-suite and data governance leaders can expect the following benefits:

  • Chief information officer (CIO): Gain a comprehensive overview of the success of your IT strategy that enables you to draft a roadmap for the evolving IT architecture and landscape, optimize existing IT processes and assess how available IT and data assets will im-pact the business environment.
  • Chief data officer (CDO): Achieve data-driven transformation at scale, embed data governance within the organization and set up a data marketplace to monetize corporate data as-sets and add measurable value. 
  • Chief information security officer (CISO): Ensure your data strategy complies with all regulations and introduce a resource-based data security strategy that protects enterprise data assets and safeguards your company’s reputation by mitigating data breaches and security threats.
  • Chief technology officer (CTO): Assess different catalog solutions for state-of-the-art data infrastructure and identify features as well as synergies for using and reusing metadata to avoid excessive infrastructure spending and technical debt over the long term.
  • Head of data governance: Develop governance expertise through holistic metadata management and rely on data literacy, data democratization, and self-service access to make data governance more visible and impactful within the transformation process.

We make sure you have the ideal data catalog strategy for the subsequent execution and delivery phases when you implement the target solution as required. By maintaining strong partnerships with major data catalog vendors and providing a team with the necessary skills to deliver the solution you need, Deloitte is your one-stop shop for building and implementing a data catalog solution of any size and scope.

Download the whitepaper and find out more about Deloitte’s data catalog strategy.

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