Building and Managing a Data Catalog: Best Practices

Discover the best practices for building and managing a modern data catalog, enhancing data organization, collaboration, and decision-making.

Building and Managing a Data Catalog: Best Practices

Struggling to keep track of all the data within your organization? Looking for a tool to help you find and understand your data? A data catalog may be what you need.

A data catalog can help everyone on your team feel more confident in accessing the right data at the right time. In order to make it work, it’s important to have a plan and commit to implementing it – from choosing the best data catalog to making it work for your business needs to driving usage and adoption.

In this blog, we will guide you through the process of building a data catalog. The ultimate goal is to help you understand the opportunities and the challenges that you may face to make the process as smooth as possible. 

We’ll also make sure we share our data catalog best practices to help you feel more confident with the use of data.

Importance of data catalogs 

Today, it is essential for organizations to have the right tools and systems in place to find, understand, and use their data effectively. 

A data catalog is a collection of metadata, search, and management tools that helps organizations centralize their available data to make smarter business decisions. Think of it as your GPS for data that helps everyone in your team navigate the data landscape. A modern data catalog makes it easier to discover, analyze, and organize inventories of your data to serve as the single source of truth for all the data touchpoints. 

What makes data catalogs important? Here are a few ways they can help your business.

  • Improve business efficiency. Did you know that data-driven companies are 58% more likely to beat revenue goals than those who are not focused on data? In order to be data-driven, it’s crucial to have a centralized system of finding and analyzing all the available data. A modern data catalog can reduce the time it takes for everyone to locate and use data. Tools like Castor are catering to both data teams and data consumers to ensure that everyone feels more efficient.
  • Cut down on unnecessary spending. Granted, there will be a cost to building a data catalog at the start. However, the cost would be higher if you had to manually manage data on your own. A data catalog improves the data team’s productivity, while it also makes it easier to locate unused and bloated assets and identify costly queries. You can visualize and analyze query metrics to explore optimization suggestions to remove bottlenecks and help everyone in the business make more data-driven decisions.
  • Surfacing data quality. A data catalog allows you to view data quality results alongside data documentation to surface your data’s health and reduce errors and costs. It makes it easier to identify new opportunities and make informed decisions by ensuring the data is healthy.
  • Compliance with regulations. Data privacy laws are expected to be tighter by 2024. Data catalogs can help you with data management to ensure regulatory compliance. For example, you can use metadata tagging in a data catalog to automatically classify sensitive information and control who has access to all available data. You can also get compliance officers to work closely with the data team to ensure that your business adheres to the latest regulations.

Once you establish the benefits of having a data catalog for your business, it’s time to define your goals and how you want to use the tool. Scoping the process and confirming the outcome will help you be clear on what you want to achieve while it will also make it easier for everyone to understand its use.

The first step is for the data team and the key stakeholders to map out the objectives. Right after confirming them, it’s time to communicate the goals with different teams to ensure that they are aligned with the broader business objectives. 

Steps for building a data catalog 

Building a data catalog doesn’t have to be overwhelming. All you need is a plan to organize the process in a number of key steps. 

1. Identifying and inventorying data sources

Before you start building your data catalog, it’s important to define the scope and the objectives of the project. Map out what you want to improve with the use of a data catalog and plan the necessary steps. 

Once you confirm the scope and the objectives, it’s time to identify and inventory your available data sources. The more time you spend on this step to trace all the data, the easier it becomes later on for everyone to access all data using a data catalog.

It can be a manual process to trace all data sources. There may be multiple different tools or databases to review. Make sure you talk to all different teams to ensure you review all available data. Right after identifying all data, make sure you document its location, owner, and format to keep data management as consistent as possible. 

2. Establishing data catalog taxonomy

You’ve done the prep, now it’s time to organize your data assets in the data catalog. Having a structured taxonomy makes it easier to organize all your data.

Start by creating a hierarchy of categories and subcategories for your data in a way that makes sense for your organization. Be clear with the data types, the sources, and the owners of each data set. 

Decide on a naming structure and be consistent with how you organize all your data. Document the process and make sure that everyone understands it to maintain high data quality. It can be useful to ask for feedback after the initial taxonomy to confirm everyone understands the new structure.

3. Implementing metadata management

Now it’s time to enhance the visibility of your data stack.

Modern data catalogs can transform metadata by automating painful documentation tasks. Tools like Castor help you add context and understand all tables, columns, or dashboards you are pulling the metadata for.

They can also add intelligence to transform metadata management with data lineage links, tags, owners, popularity, or auto tag personal information (PII).

This is the step to test auto-documentation to explore how it can support your business needs.

4. Ensuring data quality and lineage

Last but definitely not least, it’s time to focus on data governance and quality. The data catalog you choose should have built-in compliance and access management to improve security and performance.

It should be able to surface data quality tests to identify key data assets and suggest refactoring or migrations when needed.

It should also make everyone feel confident in the data they are using with cross-system data lineage that visualizes the flow of your data infrastructure. Having a clear view of where all data comes from makes it easier to know where PII flows while it’s easier to be GDPR-compliant when knowing what everyone has access to.

By following these four steps, you are ready to use your new data catalog. Need more details? Here are 10 tips to prepare your data catalog.

If you are still on the hunt for the best tool for your needs, we’re here to help. Try Castor today and explore our highly-rated features that simplify the process of improving your data experience.

Typical challenges 

Just like any new tool you add to your tech stack, there may be a few obstacles to overcome when building and managing a data catalog. Let’s look at four common challenges and how to overcome them. 

Data silos and fragmentation

Data silos and fragmentation are common challenges when building a data catalog. For many organizations, data is scattered across different teams, or tools and metrics may have different definitions across different teams. There may be silos from one department to the other or challenges with collaboration that question the accuracy of your existing data. There could also be data stored in different locations which makes it challenging to consolidate. 

How to address the challenge: It’s important to take a holistic approach to data management to prioritize data integration and consolidation. This is the time to break down data silos and create a centralized source of truth for all your data. 

Start by creating a standardized data schema that everyone in the organization can use. Make sure you create clear guidelines to improve the processes in data collaboration. Use data integration tools to bring data together from different sources to address fragmentation and improve data accuracy. And assign ownership to data assets to ensure accountability for accurate, up-to-date documentation.

Scalability and performance

As your data volume grows, it can take a lot of work to provide quick access to data or maintain documentation quality. 

All the available metadata and data lineage can make your data catalog look overwhelming. It could even slow down the process of finding the information you need and raise concerns if the catalog is up-to-date.

How to address the challenge: This is a challenge that can easily be addressed by choosing the right data catalog tool from the start. It’s essential to use a data catalog that has the infrastructure to allow scalability without affecting its performance. A cloud-based solution, for example, allows you to scale your data without slowing the search or load times. Catalogs with automation features also solve many scalability concerns.

When choosing your data catalog, find a tool with strong data lineage, metadata indexing, and search features to ensure that performance won’t be affected while you scale. Once you pick the right tool, you should also regularly monitor the performance of the data catalog to be proactive as your data volumes increase.

Data security and privacy

It’s essential for every organization to prioritize data security and privacy. Still, not knowing who has access to data or where it flows creates a risk of compliance. Moreover, your data catalog can include sensitive information that needs to be protected from unauthorized use. 

On top of all these, there is always the external risk of data breaches and cyber attacks that could have serious implications.

How to address the challenge: A modern catalog allows you to classify and protect sensitive data to improve your compliance strategy. It makes it easier to have an overview of your data infrastructure and manage access controls.

You can also build a log of high-risk queries to protect your privacy and security. Most of all, a data catalog helps you streamline your data governance with a series of automated tasks that simplify the process while maintaining data security.

All organizations should implement robust security and privacy measures to protect sensitive data and only provide access to authorized users. It’s crucial to train all employees on data security and its best practices to reduce the risk of data breaches. Additionally, conducting regular audits helps you be more proactive in identifying potential security threats before it’s too late. 

User adoption and collaboration

You can’t make the most of a data catalog if your team doesn’t understand its benefits and actually use it. A low adoption rate can affect your data documentation completeness and consistency. It could also impact collaboration and lead to more silos.

Still, it’s important to acknowledge the fact that there will always be team members who are more resistant to change. How do you address this challenge?

How to address the challenge: The first step is to educate everyone in the company about the benefits of using a data catalog. Make it specific to their needs and how they can use it. It’s also important to choose a data catalog tool that has an easy-to-use UX, and syncs back to the tools they’re used to using every day, such as dbt, snowflake, looker, or big query.

You can even involve them in the stage of setting it up to ensure their needs are met. Training sessions will be useful at different stages of the process to confirm that everyone is happy with the way they’ll be accessing and using data. It’s all about building a data-driven culture that relies on transparency and collaboration. 

Best practices for managing data catalogs 

Once your data catalog is built, it’s time to ensure it helps everyone find, access, and understand data within your organization. Here are the data cataloging best practices you need to know.

Prioritize user experience and accessibility

Designing a data catalog with user experience and accessibility in mind can improve user adoption. In order to achieve this, you want to choose a data catalog that is easy to use with an interface where everyone can access the information they need.

You also want to use a data catalog that makes it easy to connect tools that people use every day like Slack or Gmail to eliminate the need for switching between different tools and teams.

Think of the data catalog as your centralized command center for data infrastructure.

Automate metadata extraction and data lineage tracking

Both metadata extraction and data lineage tracking are essential but it’s important to have an automated process that eliminates the errors from manual entry while facilitating data discovery.

Automating metadata extraction can save you time while ensuring that your data assets are still accurate and trustworthy. Having a data catalog that allows you to automate the process helps you build a robust data strategy that is efficient without being time-consuming. 

Automating data lineage tracking is helping data catalog managers find the source of data, which enhances data governance and compliance.

By automating both of the processes, your company can feel more confident in making data-driven decisions that are based on reliable data.

Monitor and maintain data catalog health

You can’t aim for data quality without maintaining the data catalog’s health. Monitoring your data catalog can help you identify issues that could impact your data usage. It also makes it easier to keep your data up-to-date and maintain a good user experience. 

Start by defining your benchmarks regarding your data catalog’s performance. Set up a monitoring process in place to regularly review the performance and the overall data catalog health. Make sure you also have a schedule in place to audit metadata to keep your data accurate.

Benefits of Using Castor for Data Cataloging and Getting Started 

You must be convinced by now of the benefits of having a data catalog. You should also know how to build it and manage it to make the most of it.

If you’re ready to use a data catalog, we have a good option for you.

Castor is a modern data catalog that simplifies the process of finding, using, and understanding data. What makes it stand out?

  • Streamlined data catalog creation process
  • Comprehensive metadata management and data lineage capabilities
  • Advanced search and discovery features
  • Robust security and privacy measures
  • Seamless integration with existing systems

Most importantly, it’s highly rated by G2 users in key categories such as Ease of Use (9.9/10!) Quality of Support (9.8/10), and Ease of Setup (9.6/10).

Ready to give it a go? Try Castor today with a 14-day free trial and enhance your data experience.

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