How organized is your firm’s data? Dealing with unorganized raw data can impact your company’s efficiency, productivity, and ability to make informed decisions. A better approach is to organize your data in a centralized data catalog and ensure you’re working with high-quality, easy-to-access information.
- A data catalog is an organized collection of data assets
- A data catalog standardizes and organizes assets from multiple data sources
- Using a data catalog improves efficiency, productivity, context, and data quality
- A data catalog also improves data governance and security and reduces noncompliance
What Is a Data Catalog?
A data catalog is an organized inventory of an organization’s data assets. Like a library collects and organizes books to help readers find specific information, a data catalog collects and organizes data to help users find specific information.
Like a librarian identifies and curates the books in a library, data managers discover and organize the data in a data catalog. Data can come from many different sources of varying types, quantity, and quality. Dealing with that raw, unorganized data can quickly become overwhelming. The data must be examined, verified, cleaned, and organized to be useful for others in the organization.
A well-organized data catalog is of use to many different users in an organization, from data scientists and data engineers to managers and regular users just trying to gain insight from specific information. For data to offer value to all these types of users, it must be accurate, reliable, and easy to access.
How are the contents of a data catalog organized? It’s all about the metadata attached to each file. Metadata describes a file’s contents, using common keywords of value to an organization. You can organize data by keywords, and users can use keywords to search the catalog for matching data.
Of course, for a data catalog to be truly useful, it has to be reliable. The quality of data ingested from various disparate sources is typically variable—but needs to meet a set standard of excellence. Data managers use data monitoring tools like FirstEigen’s DataBuck to clean, validate, and standardize data before it enters the data library. This ensures that all the information in the data library is accurate, complete, timely, and correctly formatted.
A well-organized data library is more useful when it includes robust yet easy-to-use search tools. All that data has no value if employees can’t access what they need. Searching metadata by keyword helps users find specific data and put that data to use within the organization.
6 Top Benefits of a Data Catalog
Most organizations find that creating a data catalog creates immense value. With that in mind, here are the six most important benefits that most organizations derive from data catalogs.
Improved Efficiency and Productivity
Experts say that data scientists spend 79% of their time collecting, cleaning, and organizing data. That leaves just 21% of their valuable time to use and gain insights from that data. Why is that?
According to Deloitte, the typical company has to deal with 25 different data sources just to generate customer insights. Manually sorting through each data source is highly inefficient and often overlooks the most appropriate data.
This is where a data catalog lends tremendous value. By cleaning and organizing data from many sources, a data catalog makes it easier for users to find the information they need. Users spend less time managing data and more time using it. This dramatically improves an organization’s efficiency and productivity.
Without the data catalog process, users have to retrieve and evaluate data piece by piece. In a data catalog, that evaluation occurs before users access the data, cutting that time-consuming step out of the process. In other words, a data catalog removes from data consumers the burden of evaluating data. This frees up a considerable amount of time users can spend analyzing and gaining insight from that data.
Another problem when dealing with multiple large sources of data is determining which are the best data sources. Users can only determine the best source by examining the context of each piece of data, which can come from connecting data to its metadata or by manual input from data analysts.
Data becomes more usable and valuable when it is enriched with context. A data catalog provides that context and helps users of all types better understand what they’re dealing with.
Improved and Consistent Data Quality
Part of ingesting data into a data catalog is cleaning that data to correct or remove errors, duplicates, bad formatting, and other errors. It’s imperative that the data in a data catalog—the data employees and senior management use alike—be extremely high quality. Low-quality data can lead to inefficient operations and uninformed strategic decisions.
Data quality is measured by six key metrics:
- Accuracy, which tracks how error-free the data is
- Completeness, which ensures that there are no missing fields in data records
- Consistency, which ensures that data from multiple sources are in sync
- Timeliness, which measures how old the data is
- Uniqueness, which looks for unnecessary duplicates
- Validity, which examines how well data conforms to your internal data standards
Ensuring high data quality requires monitoring and validating all data before it enters a data library. You can do this best with automated information monitoring software, such as DataBuck, which can examine and validate thousands of data sets in seconds.
Improved Data Governance and Security
Who has access to your organization’s data? If you’re dealing with a variety of data sources feeding into multiple departmental or location-based data silos, you simply don’t have control over access to that data. Centralizing your organization’s data into a single data catalog makes that data easy to find and access and lets you tightly control data access. Tighter data access also improves data security, which is important in this age of rampant ransomware and cyberattacks.
Improved Regulatory Compliance
Consumers and governments are increasing their focus on data privacy, resulting in more stringent regulations on data use and security. Unmanaged or unmanageable data silos make it almost impossible to comply with current data privacy regulations because you don’t have full control or knowledge of who is accessing what data.
Creating a centralized data catalog makes it much easier to ensure that your organization complies with all applicable industry and governmental regulations. Noncompliance isn’t an option, making establishing a data catalog a necessity.
Let DataBuck Improve Your Organization’s Data Quality
Your organization needs to centralize and organize its data in a data catalog. To ensure the quality of your catalog’s data, turn to the data quality experts at FirstEigen. Our DataBuck software is an autonomous data quality management solution that automates more than 70% of the data monitoring process. Use DataBuck to create a data catalog with high-quality, accurate, and up-to-date data.
Contact FirstEigen today to learn more about data quality and data catalogs.
Check out these articles on Data Trustability, Observability, and Data Quality.
- 6 Key Data Quality Metrics You Should Be Tracking (https://firsteigen.com/blog/6-key-data-quality-metrics-you-should-be-tracking/)
- How to Scale Your Data Quality Operations with AI and ML (https://firsteigen.com/blog/how-to-scale-your-data-quality-operations-with-ai-and-ml/)
- 12 Things You Can Do to Improve Data Quality (https://firsteigen.com/blog/12-things-you-can-do-to-improve-data-quality/)
- How to Ensure Data Integrity During Cloud Migrations (https://firsteigen.com/blog/how-to-ensure-data-integrity-during-cloud-migrations/)