August 02, 2023
9 min.
Insights

Data Catalog for Metadata Management: 5 Key Success Factors

In most enterprise settings, two worlds face each other when it comes to data: IT/Data departments, who work with data and have a hands-on, operational relationship with it; and business, whose strategic outlook leverages data to better inform their decision-making. These worlds are, at times, worlds apart.

Why and How to manage Data about Data

In order to act as a data-driven company, you need a common understanding and knowledge-sharing between both areas of expertise, so that business purposefully can enhance data management, and IT can advance ideas and goals based on business-needs and in a targeted manner.

Why should anyone care about Metadata?

Here is where Metadata comes in handy. Metadata is data about data, from which certain information can be drawn: information on

  • the content of a dataset,
  • on its source,
  • its usage,
  • and what rules apply to it.

Starting from this, it is possible to build up shared knowledge about data and its purpose, as well as enable easy access to and availability of the data.

Why should companies use a Data Catalog?

The usual tool to manage data about your data is a data catalog. Having a data catalog can build the urgently needed bridge to a common understanding between IT and business. Like a library, a data catalog keeps track of a company’s data. It helps to find the right data quickly and easily; it can help to understand and to use the data effectively and therefore increases not only the data literacy within your company, but also collaboration and knowledge-sharing.

On top of it, ramping up data literacy can reduce costs by optimizing operational efficiency. With a vast amount of data available, being able to understand and use data effectively can give companies a significant competitive advantage.

What are the benefits of implementing a Data Catalog for Metadata Management?

Data catalogs have additional advantages:

  • You will be able to enhance data quality through improved data governance. A high data quality is indispensable for machine learning and AI contexts as well as the trustworthiness of your data.
  • Decisions based on data are only as good and trustworthy as the data itself. If you want to avoid garbage-in-garbage-out, you can improve both data quality and governance via a well-designed catalog.
  • Data catalog supports your future initiatives for data-driven digital transformation. You can integrate data from different sources, ensure that everyone is using the same definitions and standards, and keep your data safe by ensuring that everyone is following the rules and regulations related to data privacy and security. For instance, if you need to connect new data (let’s say in an ESG context) to existing structures, a data catalog can do wonders for you.

It is important to notice that the advantages of a data catalog are usually indirect. However, there are several areas where a data catalog can provide return of investment, including, but not limited to: improved productivity, reduced risk, cost savings, enhanced transparency, improved decision making and increased revenue. A data catalog pays off, in many ways.

Intrigued and want to know more? If so, read on to find out how our team would suggest how to go about implementing a data catalog!

How to implement a Data Catalog?

Now, if you are intrigued, but don’t know where to start or what to focus on, the following sections provide an overview of five key factors for implementing a data catalog.

1. Get the right people invested in the project – and keep them

The first key factor in implementing a data catalog is finding the right people for the initiative. Of course, you will need the support of your company’s operational employees, but first, you definitely need the support of the executive level and its commitment to structural change. To get their support, it is key to make them understand why you need a data catalog and why it will make sense for your business.

Quote

Without the necessary capacities and prioritization, it is likely that there won’t be any progress or that key people are lost on the way.

Dr Dorothee Wielenberg Data Strategy Consultant

Not only does a data catalog initiative take the commitment of the executive level; it also needs their sponsorship. Data catalogs can be expensive and getting sponsorship isn’t easy. The benefits are huge, but their impact is often indirect and not always immediately visible. Get their buy in by clarifying and showing the extent to which the company could benefit.

When you got the sponsorship of the executive level, one of the first steps is building the right team. You want all levels represented in such a team, from business stakeholders to operations. Make sure to include and involve at least one of your main stakeholders regularly. If the responsible people are involved, it becomes much less likely that they lose commitment or that you create misalignment on the way, and it is easier for them to see your progress.

You need people who are accountable and responsible for:

  • the data quality of data sets;
  • the criteria of the data quality;
  • the data governance framework;
  • creating data according to the criteria;
  • maintaining the data on IT systems according to business requirements.

To do so, select subject matter experts from the various fields of data management and make sure that the people can prioritize the initiative. Without the necessary capacities and prioritization, it is likely that there won’t be any progress or that key people are lost on the way.

2. Get the Data ready

Getting the data ready is a second key factor in implementing a data catalog. You need to consider how quickly the relevant data landscape could change to find a suitable and effective data management style. In most cases this will mean that you cannot just map the data and stick with it.

  1. This means you need to update the landscape constantly. An agile mindset and ambiguity tolerance are key for your team members to push through.
  2. Then you need to think about the quality of your metadata. A pre-defined metadata process is necessary to systematically improve the quality of your metadata. Also, check whether your data is structured enough, properly maintained, up-to-date and trustworthy.
  3. Finally, for the proof-of-concept phase of the implementation it will take a consistent, reliable, and statistically representative sample of test data. Keep in mind that not all data is of equal importance. To identify the critical data elements, it is necessary to conduct a data importance analysis.

3. Know your needs and requirements

Ask yourself these 2 questions:

  1. What do you want to achieve with a data catalog?
  2. Which challenges do you want to face with it?

Having a clear answer to these questions will help you to not lose sight and to not introduce the tool as an end in itself. Keep your pain points and goals in mind. Based on these, think about how you plan to improve on your situation through the possible features of the tool.

You should discuss and align your needs and requirements between Business and IT, so that everyone is on the same page as to why the data catalog is needed. There is a possibility that not everything that can be done must be done, and vice versa. For this reason, use cases are important to really understand what to prioritize. Use cases will throw a spotlight on your actual needs and gaps. They should be ready and clearly documented before you select the tool. Also, keep in mind that the scope of the requirements should not be too broad nor too specific: Find a pragmatic middle-ground.

4. Get the right tool

Nowadays, most data catalog vendors offer different sorts of demo versions, so you can get an idea of everyday operational processes in the tool. Test this up front, if possible. Still, choosing the right tool means knowing that there is no one-size-fits-all solution. There is no such thing as the ‘best data catalog tool’. In fact, most data catalogs specialize in one or more of various capabilities.

Identifying the criteria for the right tool, a tool that really fits your present needs, situation, and future is crucial, but sometimes can be difficult due to complex, organically grown IT and data landscapes in your organization. It might be advisable to get the right support for the identification process. Having said that, the following questions and pointers are intended to give a rough idea of what to look out for:

  • Is a tool (easily) connectible to existing systems? Think not only of your typical systems in place, but also about the more challenging aspects of connectivity: Are there sources with critical connectivity limitations, such as secluded geolocations or older machinery with legacy sensors?
  • What are the different advantages and disadvantages of on-premise hosting and Software-as-a-Service? Take into account that some businesses require on-premise solutions or that you might already have a cloud provider that already provides a compatible catalog tool.
  • Remember: What problems should the tool solve? What should be achieved with the implementation of the tool? And therefore: Which requirements does the tool have to meet?
  • Lastly, think about how your business does plan to evolve within the next three, five or ten years. Will the tool scale accordingly? What and how will the data catalog have to perform then?

5. Communicate!

“A data catalog is a social network” (Olesen-Bagneux, Ole (2023)). Therefore, communication is inherent and inevitable for its success. Transparent communication with the involved people in- and outside your organization is vital to align goals, gather requirements, engage stakeholder, manage expectations, ensure user adoption, resolve issues, and facilitate change management. It creates a collaborative environment and increases the likelihood of a successful implementation and adoption of the data catalog.

The more complex your organizational structure, the harder the resistance to change will be. Should you want to facilitate change in difficult environments, we recommend you to consider leveraging a network of change ambassadors!

Conclusion

In our exploration of the complex relationship between IT and business, we’ve come to recognize the indispensable role of data. This article has been a journey into the world of Metadata and the essential function a Data Catalog serves in bridging the often disparate worlds of IT and business.

Here’s what we’ve gleaned from our deep dive into this subject:

  1. Investing in the Right People is Key: From securing executive sponsorship to assembling a dedicated team, the human element is vital.
  2. Data Must Be Prepared with Care: Ensuring quality, proper maintenance, and utilizing a representative sample of test data are foundational.
  3. Understanding Our Needs and Requirements is Crucial: We must have clarity in our goals and alignment between Business and IT to ensure that the tool serves a purpose beyond itself.
  4. Choosing the Right Tool Requires Thoughtful Consideration: Selecting a tool that fits our current needs and future evolution is a complex but necessary task.
  5. Communication Cannot Be Overlooked: Transparent and continuous communication is essential for collaboration and change management.

Managing data is more than a technical task; it’s a strategic approach that can lead to tangible benefits like improved productivity, reduced risk, cost savings, and increased revenue. Implementing a data catalog is not just about technology; it’s a transformative process that requires the right blend of people, tools, and communication.