Every company today knows they need to be built on data if they want to beat the competition, delight customers, and create meaningful growth. As companies race to gather massive data volumes, take advantage of data marketplaces and third party data, and bring new digital touchpoints with partners and customers online, there’s a new issue at hand.
Facing this growing data deluge, there’s a real risk of losing sight of what data matters, is available, and how different datasets relate to each other. Luckily, by using technologies such as a data catalog, organizations can address this issue head on.
A data catalog is an organized collection of metadata that describes the content and structure of data sources. It is a critical component of any data governance strategy, providing users with easy access to a centralized repository of information about their organization’s valuable data assets. It’s especially important for organizations who rely heavily on data as a core element of their business, or who want to leverage data-driven decision making across different teams and departments.
Often, simply knowing what data can be utilized presents a challenge, particularly for large organizations or data dense businesses. The primary purpose of a data catalog is to provide visibility into all of the data that is available within a company. You can think of it as a comprehensive directory of all the data sources, complete with descriptions and definitions, that enable users to quickly identify which datasets are most relevant to their needs or use case. The catalog also documents important information about each dataset such as ownership and accuracy. When incorporated correctly into a data governance strategy, they often include usage restrictions that can be used to ensure compliance, increase security, and mitigate risk.
Once the data catalog has been implemented, users can query the metadata and find specific datasets. It also provides the ability to quickly discover relationships between different pieces of data, giving users an overview of their entire data landscape. Many data catalogs also offer additional features such as machine learning-based recommendations, customizable dashboards, integrations with business intelligence tools, and automated security checks.
By providing an organized, easy-to-use repository of data sources and related information, a data catalog makes it possible for companies to better control - and leverage - their data assets. As such, a well-designed data catalog can significantly improve the effectiveness of any organization’s data governance strategy.
Too often in the world of data, users get stuck before they can even get started, simply because they don’t know what information or data is available. A data catalog addresses these challenges by giving users a comprehensive directory of all their organization’s datasets. With this information, analytics engineers, data scientists, data analysts, and even business users can quickly identify the ones that are most pertinent to their needs.
When users don’t know where the data is coming from, they often won’t rely on the output insights gleaned from business analytics. This is particularly damaging for organizations who want to leverage self service analytics because, once business users lose trust in an insight, winning it back and driving adoption becomes far more challenging. The catalog helps address this by providing important information about each dataset, allowing users to ensure that they are using the correct data for their applications.
By providing visibility into all of the datasets that an organization can utilize,, a data catalog helps businesses take control and ownership over all these valuable data assets. The catalog also documents important information such as usage restrictions, enabling users to ensure compliance with corporate governance policies.
A data catalog allows users to quickly identify relationships between different pieces of data, giving them an overview of their entire data landscape. It also offers features such as machine learning-based recommendations, allowing users to quickly find new datasets that may be relevant to their needs. When paired with the right analytics solution, this reduces the time to value tremendously for data projects.
Many data catalogs offer automated security checks which can help ensure that users are only accessing datasets for which they have the proper permissions. This helps to ensure that corporate governance policies are being followed and reduces the risk of unauthorized access to sensitive information, such as PII.
A well-designed data catalog makes it easier for users to find the right datasets and build and launch new use cases. It also helps quickly identify areas for improvement in their data management strategy. This helps organizations to make better use of their data assets and get more value out of their investments.
Data catalogs and metadata management are two different concepts that are often confused. Data catalogs serve as a repository of information about data sources, while metadata management is the process of managing and organizing data related to the data sources in the catalog.
Think of data catalogs like an inventory cheat sheet, highlighting all available data assets within an organization, detailing what data is available, and where it can be accessed. In addition to providing a centralized repository of data, they also include other important information such as the data source’s location, format, quality score, ownership metrics, tags, and more. This makes data catalogs a great resource for quickly finding and accessing the right data for any given task or project.
Metadata management, on the other hand, is the process of collecting, organizing, and maintaining data related to an organization's data sources. Metadata helps describe and classify data so that it can be used more effectively. It includes information such as meanings, relationships, definitions, and properties of a particular dataset.
In short, data catalogs provide a repository of information about available data sources, while metadata management is the process of managing and organizing data related to these sources. Together, they provide organizations with valuable insights into their existing datasets, helping them make smarter decisions.
Data catalogs are evolving quickly, especially those in the modern data stack. New use cases and capabilities are being developed all the time. As organizations continue to embrace data-driven strategies, data catalogs will become even more important for helping them manage and leverage their data assets. There are several different use cases for data catalogs. Here are five of the most common:
Organizations can use data catalogs to improve data governance by creating a centralized repository for all their data assets, enabling them to monitor and manage access and usage. This helps ensure compliance with regulations and internal policies, reducing risk while also providing insight into data quality and security.
A data catalog provides visibility into the quality of datasets, allowing users to gauge the accuracy and freshness of their data. This helps to ensure that datasets are reliable and up-to-date, minimizing errors and maximizing the value of data.
A data catalog can be used to facilitate machine learning development by providing easy access to relevant datasets for training models. It also makes it easier to manage the deployment of models, providing an index of all available models and their associated performance metrics.
By tracking access and usage information, a data catalog can help organizations keep their data secure. It can also be used to monitor for unauthorized access or suspicious activity, helping to ensure that sensitive data remains safe and secure.
Organizing and structuring your data in a data catalog on its own won’t drive business value, but when paired with self service business intelligence, companies can rapidly drive adoption of analytics programs. Users can find the data they need, quickly interrogate it with search, create interactive data visualizations, and then use these insights to take action, all with confidence in the data they are using.
Data catalogs are a powerful tool for managing and accessing data in an organization. With the right setup, it can be used to quickly identify and access relevant data, making it possible to dramatically increase the value of investments in data assets. However, in order to maximize the value of a data catalog, there are certain requirements that need to be met.
First, it is important to have a comprehensive understanding of the data that will be stored in the data catalog. This includes having an accurate inventory of all data sources, such as databases and files, along with details on each source’s structure and content. Knowing what data exists, where it is located and how it can be used is essential for successful data cataloging.
In addition, it is important to have a clear set of definitions for the data being included in the data catalog. This includes labeling the data into categories and subcategories, using consistent terms and labels, and defining any data formats or other characteristics that need to be considered for search purposes. Having a well-defined data structure allows users to quickly identify the relevant data they need and access it in an efficient manner.
Next, data catalogs should be regularly updated with new and existing data sources, as well as changes to existing data sets. This is especially important when working with large amounts of data or in rapidly changing environments. Keeping the data catalog up-to-date ensures that all users have access to the most current and accurate data.
Last, make sure you are exposing the data catalog to users, especially business users and their analytics counterparts. Often, this requires an intuitive user experience on the front end that makes it possible for people to engage with the underlying datasets. Doing so is essential to driving tangible business value and maximizing ROI of investments in the data catalog.
By following these four steps, organizations can ensure they are making full use of their data catalogs and unlocking maximum value from their data. With a comprehensive understanding of the data sources, clear definitions for each data set, and regular maintenance, data catalogs can become an invaluable resource for businesses.
A data catalog can bring tremendous value to your organization by helping you surface data that would otherwise be siloed or inaccessible. But to turn this data into real business impact, you need to make it accessible and actionable for a variety of users.