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Implementing an Enterprise Data Catalog

Ronan McQuillan
12 min read · Jun 18, 2024

Businesses today sit on larger volumes of data than ever before. The benefits of this, including for automation, digital transformation, better-informed decision-making, and even machine learning, are well known.

However, managing and administering complex data sets so that they can be leveraged to provide value to end users is incredibly challenging.

That’s where enterprise data catalogs come in.

Today, we’re diving deep into what data catalogs are, why they’re used, and the specific benefits they bring.

We’ll then check out the key challenges, considerations, and best practices for implementing a data catalog, before examining how Budibase offers best-in-class experiences for IT teams that need to deliver end-user services at pace.

Let’s kick things off with the basics.

What is an enterprise data catalog?

An enterprise data catalog is a centralized resource for documenting our internal assets, including what they contain, where they’re stored, the processes they relate to, their intended usage, and the rules and permissions that govern them.

A data asset could be a database, filtered view, document store, API endpoint, data lake/warehouse, spreadsheet, file, spreadsheet, or even an individual record.

In the first instance, the goal is to provide colleagues with a unified source of information about our data assets so that they can easily locate the appropriate data for their immediate needs without necessarily needing to go through IT.

On top of this, cataloging is central to our data governance workflows. For example, we can automatically grant access to certain data sources to different users, based on their roles or department.

We can then provide request/approval capabilities for accessing other data assets that fall outside of these default rules.

In turn, this also enables us to maintain clear records of how our data is being used and by whom.

However, a data catalog isn’t simply a massive repository of all of our organizational data. Rather, it’s used to store our data assets’ metadata.


What is metadata?

Metadata is data about data. It’s crucial to understand how this differs from the data itself. Say one of our assets was an employee information database. The actual asset here is the stored values, like our colleagues’ names, addresses, roles, etc.

By contrast, metadata is largely concerned with how our data set is managed, categorized, and used.

A huge part of this relates to how users can find our data. For instance, providing tagging and labeling so that we can search for data using business terms rather than IT nomenclature.

Metadata can also include information about data ownership and lineage. That is, where data comes from, which teams are responsible for maintaining it, and how it has changed over time.

Other types of metadata include governance rules, summaries, or even the schema of the database in question.

What does a data catalog do?

Now that we have a good grasp of the basic problem that enterprise data catalogs solve, we can move on to thinking about how we can implement this at a technical level.

The first challenge is actually documenting all of our data assets.

This can work in a few different ways. In most enterprises, the top-priority data sets will already be documented and loaded into ERP or data warehousing platforms. For other data sets, we’ll need either manual or automated discovery.

Beyond this, data catalogs generally provide the following capabilities to end users.

Data searching

Enterprise data catalogs must provide effective search tools to enable end users to locate the right data set for their needs.

Depending on their requirements and technical skills, they might want to do this using specific facets of the data set, keywords, business terms, or some other combination of search queries.

Detailed, strict metadata is crucial here, but so is implementing appropriate search logic, including ranking results by relevance to the particular user.

Data evaluation

Next, users need to evaluate individual data sets to determine if they’re the right ones for their needs. The challenge here is enabling colleagues to validate data sets without necessarily needing access to the whole thing.

There are a couple of strategies we can implement here. Naturally, this includes viewing all of the associated metadata, including curators’ notes or even reviews and comments from other internal users.

Even better, we can provide previews of the stored data. If a user requires approval to access the data set, we might display dummy values instead of real data.

Data access

Lastly, our data catalogs are critical for enabling users to access data assets. This is the trickiest part, as the access method can vary from one data set to the next. In very simple cases, users might simply be able to download a CSV.

Other times, an administrator might need to manually provide them with database credentials or logins for a specific tool.

Importantly, certain data sets will enable users to self-serve when it comes to access, subject to their role. Others will require request/approval workflows to ensure that more sensitive or mission-critical data can only be accessed by certain colleagues.

6 benefits of data cataloging

Next, we can start to think about some of the concrete business-level benefits that we can expect when we implement an enterprise data catalog.

Here are the six most important benefits.

De-siloing data

The key impetus for most organizations implementing a data catalog is eliminating data silos. Data silos occur when internal teams each store their own data assets with little or no coordination.

This is problematic for several reasons. Firstly, one team doesn’t know what data another has. Therefore, it’s very difficult to communicate, collaborate, or coordinate around our data.

We might even see duplication across teams in terms of the data they store and process, without any controls or agreement on which data sets constitute an organization-wide source of truth.

Similarly, there’s no centralized oversight from IT, making it tricky to ensure security protocols and best practices are followed effectively.

Enhancing data efficiency

We can think of data efficiency as how successful we are at furnishing colleagues with effective data assets. Of course, this is a complex issue, but for now, we can think about it at a couple of core levels.

The first, which we’ve alluded to already, is our processes for accessing data. The key thing here is eliminating barriers to leveraging data, using the search, validation, and access strategies that we saw above.

The second is efficiency at the level of data operations. Data cataloging helps us to reduce barriers to integration and transformation by boosting accuracy, compatibility, availability, integrity, and interoperability across our data assets.

Providing data context

Data catalogs are also critical for providing context to end users about what our data means and what it’s intended for.

This includes where the data comes from, the other processes it relates to, who uses it currently, and how it sits in our wider business.

This leads to a range of benefits, including facilitating collaboration, innovation, and holistic decision-making.

Error reduction

Centralized, de-siloed data is key to reducing errors across our data operations. More specifically, providing a centralized, detailed record of the rules and processes surrounding our data is anathema to human or systematic errors.

In the first instance, we can see huge improvements here from simply eliminating improper usage.

Data cataloging also empowers us to respond to errors and incidents by providing a clear record of our data lineage and access, giving a clear path to correcting issues.

Driving data utility

Data utility is the value that we derive from our data assets. In other words, this is how useful our data is to end users or how we leverage it to drive efficiency across our organization.

Ultimately, the goal of a data catalog is to provide users with an easy way to access the data resources they need to perform the task at hand.

Therefore, when we implement this successfully, we’re also facilitating an enormous range of other areas of improvement, including analysis, process improvement, data-driven decision-making, digital transformation, and solutions development.

Maximizing security

Lastly, data catalogs are a crucial part of our wider security, governance, and compliance frameworks. Even the basic first steps of centralizing our data has a huge impact by reducing shadow IT and ungoverned data sources.

In turn, this also provides our IT team with effective control over how and when all enterprise data assets are used.

This minimizes the risk of data loss, leaks, or breaches by ensuring that we can tightly control and monitor how our data assets are stored, accessed, managed, and utilized across the entire organization.

Challenges, considerations, and best practices

Of course, actually shipping a data catalog to end users can be much more complex in the real world. In fact, there are a range of technical, process-level, and even human factors that can easily stand in our way.

As such, we’ll need a clear picture of what these blockers are and the strategies that are available to us for overcoming them.

Some of the key challenges that present themselves in terms of creating an enterprise data catalog include:

  • Data discovery - Initially identifying, locating, and documenting data sources across your entire organization.
  • Privacy and security - As we make our data more searchable and accessible, it becomes even more important to have the appropriate security controls in place to govern this.
  • Data quality - Ensuring that our data is up to standard in terms of accuracy and consistency, both in the first instance and over its lifecycle within our enterprise data catalog.
  • Data maintenance - Putting measures in place to keep our data catalog up to date with changes to data sources themselves, as well as related processes, governance rules, and technology.
  • User adoption - Convincing our users of the rationale and benefits behind implementing a data catalog.
  • Scalability - Planning for our future data catalog needs in terms of both horizontal and vertical scalability.
  • Solutions design - Designing and implementing appropriate solutions in terms of data modeling, automation capabilities, and user experiences.
  • Process adherence - Once our data catalog is in place, ensuring that users don’t circumvent the underlying business rules.

Overcoming these kinds of issues is critical to our success.

Here are some of the best practices we can adhere to to sure up our data cataloging efforts.

  • Documenting ownership and responsibilities - Putting in place clear, agreed-upon rules for which teams or individual colleagues are responsible for maintaining specific data assets.
  • Implementing role-based and attribute-based access controls - Granting permissions based on a combination of users’ roles within our data catalog solution, as well as more specific attributes like their team and job title.
  • Keeping catalogs up to date - Putting measures in place, including regular audits, reviews, and automated ETL flows, to ensure that our data catalog is kept up to date.
  • Maintaining data quality - Taking steps to ensure the validity, accuracy, and consistency of our data across its entire lifecycle.
  • Standardizing metadata - Creating data dictionaries to standardize metadata within our catalogs so that users are able to use the appropriate terminology while searching and maintaining assets.
  • Fostering collaboration - Including providing tools such as user reviews or integration with external platforms like instant messaging, project management tools, or ticketing systems.
  • Measuring success - Having clear, measurable KPIs and benchmarks for assessing the impact of our enterprise data catalog.
  • Integrating request/approval workflows - Building our data catalog around key internal processes, including providing users with the ability to request access to specific assets from directly within the solution.

You might also like our round-up of the top enterprise survey software .

Budibase for data cataloging and governance

Budibase is the open-source, low-code platform that empowers IT teams to turn data into action.

Data professionals, IT managers, systems engineers, solutions architects, and other technical colleagues in large organizations choose Budibase to output advanced solutions in a fraction of the time.

Here’s what our platform offers for data cataloging and governance.

Connect to any data source

We’re proud to lead the low-code space for external data support. Budibase acts as a proxy to query and manipulate your existing business data without ever storing it. Alternatively, you can use our built-in database to create tables from scratch, with spreadsheet-like experiences.

Budibase offers dedicated data connectors with CRUD actions and custom queries for a huge range of APIs, RDBMSs, and NoSQL tools, as well as Google Sheets, Snowflake, S3, Elasticsearch, and more.

Whether you need to integrate existing databases, third-party SaaS tools, spreadsheets, or enterprise data warehouses, Budibase is the ideal solution for building custom internal tools on top of any data source.

Enterprise Data Catalog

Build professional UIs in minutes

Our design philosophy is simplicity by default; extensibility when you need it. Our visual design tools offer autogenerated UIs for connected data tables, as well as a huge library of built-in components, a drag-and-drop editor, custom conditionality rules, and more.

Budibase makes it easier than ever to build advanced front-ends for managing our data, with user-defined and dynamic filtering, powerful table UIs, customizable searchability, optional front-end JavaScript, and more.

We also offer custom components, CSS editing, and a range of other tools for creating powerful interfaces in a fraction of the time.


Manage any workflow

Budibase is the ideal solution for busy IT teams that need to output advanced workflow tools at pace. With role-based access control, extensive data support, and sleek developer experiences, our platform is fully optimized for building approval apps, data management tools, dashboards, and more.

We also offer a flexible, low-code automation builder. Use in-app actions, webhooks, database events, API connections, or chron-rules to trigger rules based on our library of nestable, configurable automation actions.

Budibase integrates seamlessly with your existing tech stack, including native integrations with a range of business, hosting, and authentication services, as well as our platform API, REST connector, and custom data sources.

Ship solutions at pace

With Budibase, you’re in control of how and where you deploy your tools. Start building apps in seconds with our cloud platform or self-host Budibase using Kubernetes, Docker, Digital Ocean, and a range of other platforms.

Budibase also makes managing users and applications a breeze with SCIM support, air-gapped deployments, custom branding, free SSO, and much more.

Check out our features overview to learn more.