The traps to avoid for a successful data catalog project – Data Culture

Metadata management is an important component in a data management project and it requires more than just the data catalog solution, however connected it may be.

A data catalog tool will of course reduce the workload but won’t in and of itself guarantee the success of the project.

In this series of articles, discover the pitfalls and preconceived ideas that should be avoided when rolling out an enterprise-wide data catalog project. The traps described in this are articulated around 4 central themes that are crucial to the success of the initiative:

1. Data culture within the organization
2. Internal project sponsorship
3. Project leadership
4. Technical integration of the Data Catalog

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Organizations with data as the sole product are very rare. While data is everywhere, it is often only a byproduct of the company’s activities. It is therefore not surprising to find that some collaborators are not as aware of its importance. Indeed, data culture isn’t innate and a lack of awareness of the importance of data can become a major obstacle to a successful data catalog deployment.

Let’s illustrate this with a few common preconceptions. 

Not all collaborators are sensitive to what is at stake with metadata management

The first obstacle is probably the lack of a global understanding of the initiative. Emphasizing the importance of metadata management to colleagues who still misunderstand the crucial role the actual data can play in an organization is doomed to fail.

It’s quite likely that a larger program that includes an awareness initiative emphasizing the stakes around enterprise data management will have to be set up. The most important element to inculcate is probably the fact that data is a common good, meaning that the owners of a dataset have the duty to make it visible and understandable to all stakeholders and colleagues.

Indeed, one of the most common obstacles in a metadata management initiative is
the resistance to the effort needed to produce and maintain documentation. This is all the more of an issue when it is felt that the potential users targeted are limited to a small group of people who already fully understand the subject. When it is understood that the target group is in fact much larger (the entire organization and potentially all staff), it becomes obvious that this knowledge has to be recorded in a “scalable” manner. 

A data catalog doesn’t do everything

A data culture-related issue can also affect those in charge of the project, although this is less common. An inaccurate understanding of the tools and their use can lead to mistakes and cause suboptimal, even detrimental, choices. The data catalog is a central software component for metadata management but it’s likely not the only tool used. It is therefore not advisable to try and do everything just with this tool. This may sound obvious but in practice, it can be difficult to identify the limits beyond which it is necessary to bring a more specialized solution into the mix.

The data catalog is the keystone to documentation and has to be the entry point for any collaborator with questions related to a concept linked to data. However, this doesn’t make it “the solution” in which everything has to be found. This nuance is important because referencing or synthesizing information doesn’t necessarily mean carrying this information wholesale.

Indeed, there are many subjects that come up during the preparation phases of a metadata management project: technical or functional modeling, data habilitation management, workflows for access requests, etc. All these topics are important, carry value, and are linked to data. However, they are not specifically destined to be managed by the solution that documents your assets.

It is therefore important to begin by identifying these requirements, defining a response strategy, and then integrating this tooling in an ecosystem larger than just the data catalog.