Data Catalog Vs. Data Dictionary Vs. Business Glossary

Technology - Data Catalog Vs. Data Dictionary Vs. Business Glossary

The differences between a data catalog and a data dictionary are vast, and the choices of a single database can be overwhelming. The data dictionary depends on the data that is stored in the database. As a result, changes in data are likely to affect the dictionary as well. However, a data catalog will always be the most accessible reference point when the business glossary is not available. These differences are crucial in determining whether or not a business glossary is appropriate for a specific situation.


An Alation Data Catalog is a powerful metadata organization tool that scours the organization’s various data repositories and imports metadata and artifacts. It creates a knowledge base about the organization’s data assets through a combination of machine learning, language modeling, and metadata tagging. It can also model data lineage, map relationships between users and data assets, and learn the meaning of common abbreviations and acronyms.

With its powerful Behavioral Analysis Engine, open interfaces, and collaboration capabilities, Alation’s data catalog provides relevant information on every table. Its powerful analytics engine has been credited with delivering a 364% ROI to Pfizer, an industry leader in data science. It allows users to execute queries and share results with others in the organization. Alation has pioneered the data catalog space and is now leading the evolution into a data intelligence platform.

Business glossaries are difficult to build manually. It may take a group of people to debate and agree on a new term. But Alation’s Auto-Suggested Terms feature automatically finds and presents data objects that are associated with these terms. As a result, you won’t have to spend time generating the glossary and rewriting it every time you need to add a new term.

A data dictionary helps the business understand the business requirements that are guiding the development of its business glossary. It helps to improve master data management, ensure the quality of data across the organization, and integrate data from multiple sources more efficiently. It also simplifies the process of developing a data catalog. This dictionary allows developers to enter new definitions once and reuse them in many applications. It is a vital part of an organization’s data strategy.

While data catalogs and business glossaries are both essential to business, they serve different purposes. A business glossary helps to keep employees in the loop with internal definitions. Without context, executive teams might not trust the reports that are created for them. Additionally, a business glossary helps to promote self-service, efficiency, and productivity. So which of these data management tools should you use?


If you are confused by the differences between a data dictionary and a data catalog, consider how Octopai can help. The Octopai platform allows users to easily identify metadata across different systems, including databases and business glossaries. It is cloud-based and works with Microsoft’s Power BI to provide an end-to-end column lineage and profound visibility of metadata.

A data dictionary is an effective way to identify and understand the meaning of information. It includes data attributes, data fields, and other data properties. A data dictionary should serve as a one-stop shop for IT system analysts, developers, and designers. The business glossary, on the other hand, can be generated using the BI metadata. In addition to a data dictionary, a business glossary can also help companies define and use new terms in their business.

The difference between a data dictionary and a business glossary is that the latter requires a governance strategy. A governance strategy should be established to ensure that it is used by business users and is supported by a governance committee. A business glossary can be built using a tool, such as Alteryx or Qlik. A business glossary can be built into the data integration process, allowing the right people to collaborate.

While the data dictionary is a tool to identify and understand data, a data catalog is a resource that organizes and enables users to perform data searches. A data dictionary will also help users understand metadata and lineage. Data catalogs are the foundation of regulatory compliance and provide fast access to data. So, which is better? What are the advantages of each? Read on to find out!

Using a Data Dictionary is an excellent way to standardize terms and terminology across a silo system. But, implementing them can be time consuming. So, if you need a data dictionary for your business, you should look for a software that combines these two. It’s much more efficient and reliable to use a data dictionary in tandem with a business glossary than to implement a separate system.


In an Enterprise Information Map (EIM), you might be interested in defining the relationship between certain data sources and a single database. In a data catalog, you can map generalized entities to specific manifestations, as well as create submodels and perform lineage analysis. The ER/Studio data dictionary is also an enterprise governance and architecture tool. It allows data modelers and architects to share models, provide extensive model change management, and incorporate true enterprise data dictionaries. You can also choose to catalog data sources with ER/Studio’s Business Definitions feature.

When it comes to metadata management, the two are similar in many ways. The former stores data and metadata related to the file system. The latter provides context for data users, and both can help them understand complex databases. The data dictionary also allows users to check for null values, which saves a great deal of time and effort. When used in conjunction with the data dictionary, they can provide a holistic view of the data and the underlying database.

A data dictionary is helpful in detecting credibility issues within your data. Poor object naming or table organization can limit the usability of your data. Incomplete data definitions can render otherwise stellar data useless. If you fail to update your data dictionary, it suggests a lack of data stewardship. Developing good data design habits will benefit everyone involved in using your data. And it will pay off in the long run!

While ER/Studio data dictionary is an excellent free tool, it cannot replace a comprehensive database. It can also be useful for custom metadata, such as column descriptions, and is free to use. You can also use spreadsheets to create a data dictionary. When it comes to data dictionary and data catalog, both are useful. But which is better for your data? A good data dictionary will help you avoid the need to manually write a data description document.

ER/Studio data catalog has the advantage of tying business terms to their underlying data assets. It also includes capabilities that make organizational data easy to find and understand. A good business definition is of limited use if it doesn’t relate to the underlying data. Without data, users of the terms have to hunt down the associated data. BI teams must spend significant time and energy mitigating the barriers between users and data.

Technical metadata

A data dictionary provides a description of data assets, including the attributes and columns, the relationship between them and the corresponding business definition. It is used to define data assets and improve master data management across the organization. In addition to providing information about data assets, a data dictionary also provides the business definition and transformation rules necessary to properly analyze the data. Its definition is usually based on the business context and can be used across multiple applications.

A business glossary does not require new technology to create, but it should be implemented with a governance strategy. Definitions should be approved by cross-functional stakeholders and documented properly. It is acceptable for two departments to have different definitions of the same term if they have verified them. Ultimately, the goal is to ensure consistency across the three types of metadata. And while the goal of a business glossary is to facilitate cross-functional collaboration, a properly implemented data glossary should be a powerful tool for your organization.

Whether you choose a data dictionary or data catalog for your organization, it is essential to understand how each tool can benefit your organization. If your business glossary is too large, the chances are that it will create more than one version of the same data. Data dictionaries often contain a set of business terms that may not be ambiguous. While this approach is acceptable for most organizations, it can lead to multiple truths.

While the data dictionary is an excellent way to make organizational data available to everyone, it cannot stand alone. A data catalog ties together business terms with their corresponding data assets. While data dictionaries are great for BI and technical teams, they only get you so far. Without a data dictionary, users must hunt for the data they need to make informed decisions. There are other ways to achieve a similar result.

A business glossary is a collection of clear language that describes the various aspects of data. Usually created as an artifact of a data governance initiative, a business glossary is controlled by the business itself. The business glossary promotes data visibility and context and collaboration within an organization. It can also break down organizational silos and improve trust across departments and organizational units.

The Business Glossary, Data Dictionary, Data Catalog

Denodo Data Catalog References

Denodo > User Manuals > Data Catalog Guide

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