Data catalogs can be a fantastic tool for data-driven businesses, but they don’t just materialize out of nowhere. Creating a quality data catalog requires several steps to ensure you get the right platform and can maximize the potential of the features the data catalog offers. Also, you want to avoid mistakes when implementing your data catalog so you can get right to using it and ensure consistent performance. In this blog, we’ll be taking a look at some of the most common mistakes companies make when creating a data catalog so you can avoid them.

An introduction to data catalogs

Before taking a look at the common mistakes of creating a data catalog, let’s talk about what a data catalog can do for your business.

Put simply, a data catalog is a powerful tool for organizing and managing the data an organization collects and generates. It acts as a central repository for this data, allowing businesses to get a full overview of their data asset. They typically come with various features that enable enhanced data discovery, improved data governance and much more.

Common mistakes businesses make:

So, what are the common mistakes businesses make when implementing a data catalog? Let’s dive in.

1. Lack of clear objectives

Many businesses neglect to lay out clear goals when they create a data catalog. By clearly outlining the objectives and goals you have in mind, you can give purpose and direction to your implementation. Take the time to define what you want your data catalog to do for your business. For instance, you may want to improve data accessibility or make it easier to enforce data governance policies. This will help guide implementation and ensure you choose the best possible data catalog for your needs.

2. Neglecting data quality

One of the biggest mistakes a company can make when creating a data catalog is neglecting data quality. When you migrate your data to your new data catalog, it’s best to start fresh by doing a data audit and only transferring over relevant, quality data. When your data catalogs start with accurate and complete data, it’ll be easier to maintain those standards from that point forward.

You can avoid making this mistake by conducting a data audit and cleansing and validating data before migrating it over. This may take some time, but it will save you much more time than trying to fix things after the fact. You should also make sure to keep these standards up by establishing data quality guidelines and conducting regular data audits.

3. Inadequate metadata management

Businesses should make sure they have metadata management processes in place. Metadata is essential for understanding and organizing data, so it can confuse if metadata is inaccurate, incomplete or inconsistent. Make sure to have clear metadata standards and implement a robust system for metadata management. Remember to regularly review and update your metadata and metadata processes to maximize the usability of your data catalog.

4. Poor data security measures

Poor data security can have severe consequences for businesses even outside of the data catalog implementation process. Without proper data security, a business can open itself up to data breaches and unauthorized access. This can lead to hefty regulatory penalties and loss of reputation from customers. When creating your data catalog, make sure to implement access controls and conduct regular security audits. It can also help to educate your team on best practices and make sure they’re complying with industry regulations.

5. Failing to update regularly

Once you implement your data catalog, your job isn’t done. It’s important to regularly update your data catalog to prevent the technology and the data from becoming outdated or irrelevant. If you neglect regular updates, it can affect the usability and reliability of your data catalog. You can avoid this mistake by having a consistent schedule in place for regular updates. Some catalogs can even send automated updates when documentation is out of date.

6. Not training users

Having a shiny new data catalog in place can be extremely beneficial for a business — unless your team can’t use it. It’s important to take the time to train users on the ins and outs of your data catalog and its various features. Doing this will help your team make the most of your data catalog and start using it effectively right away. To train users, you can use tutorials, workshops or even one-on-one sessions to get everyone ready to use it.

7. Overcomplicating the catalog

One of the primary uses of a data catalog is improving data accessibility and discoverability for your team. This means it’s best to keep things on the simpler side to mitigate the chance of misunderstandings or errors. Avoid cluttering your catalog with an overly complex UI or unnecessary features. The fewer points of failure you have, the easier it will be for your team to leverage your data catalog’s true potential. You can avoid mistakes like these by implementing a clean and straightforward UI with features that are intuitive and easy to use.

8. Ignoring user engagement

Finally, ignoring user engagement can be a major mistake when creating a data catalog. If you build a data catalog, they won’t necessarily come. It’s up to management to involve users in the process and help integrate it into their daily processes. It can help to seek feedback, encourage user participation and take steps to implement their input to show you’re listening. Prioritizing user engagement will ensure your platform is user-friendly and that it becomes an indispensable tool for your team rather than something they ignore.

Best practices to follow

So, now you know some of the biggest mistakes that companies make when creating a data catalog. With those mistakes in mind, let’s also take a brief look at some best practices to help kick off your data catalog implementation process:

• Communicate throughout — Make sure to regularly communicate with stakeholders to ensure their opinions are heard and that your catalog aligns with their needs.
• Prioritize data quality — Never let data quality fall by the wayside. Conduct full data audits regularly and establish data quality standards that your team can adhere to.
• Pay attention to metadata — Don’t forget to implement comprehensive metadata management practices. The accuracy of metadata is essential for data accessibility and discoverability.
• Create your data governance policies — Make sure you have clear and comprehensive data governance policies in place to ensure data security and compliance.
• Monitor and update your data catalog — Regularly update your data catalog and monitor the needs of your users. This ensures your data catalog stays accurate and relevant.
• Provide training materials — Ensure your users have access to training materials and tutorials for using the data catalog and making the most of its features.‍
• Choose a data catalog solution — Creating a data catalog can be difficult, but implementing a data catalog platform like Secoda can make the process much simpler. With platforms like Secoda, you get easy implementation of all the features you could need for data management and organization.

Try Secoda for free

Secoda is a comprehensive AI-powered data catalog solution. With Secoda, your users get a centralized data repository with features for data cataloging, data discovery, data lineage, data governance and much more. Try Secoda for free today to see how it can help your business.

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