Businesses are in need of better tools to collaborate with various data sources. The data catalogs with new machine learning capabilities will help you to tap your useful data. Turning big data into actionable insights is one popular goal of businesses. Data catalog tools will help the organizations to achieve this goal in the right way. The purpose of the data catalog is to support any business to find, learn, and maintain the current data assets. This process of creating the data catalog will lead several businesses to identify the data assets they were earlier not aware of.
What’s Data Catalog?
A data catalog helps to maintain the range of data assets through description, discovery, as well as the organization of datasets. This catalog offers context to allow data scientists, data analysts, and other consumers to understand and find the relevant dataset for purpose of extracting the business value.
The data catalog is an important part of the data governance discipline. This automates the metadata management as well as makes it collaborative. Getting a data catalog helps businesses to manage and discover their data at the right level. This allows companies to track down the data assets with the business mindset whereas supporting the advanced visualization and search.
What Does Data Catalog Do?
The new data catalog tools include several functions and features that depend upon the core capability of data cataloging —collecting metadata, which describes and identifies an inventory of the shareable data. It’s impractical to try cataloging as a manual effort. The automated discovery of the datasets, for an initial catalog build & ongoing discovery of the new datasets, is very important. The use of machine learning and AI for semantic inference, metadata collection, and tagging, will be very important to get high value from the automation and reduce any manual effort.
How to Build Data Catalog for Your Business?
Building a data catalog process will be separated in three ways:
- Indexing: First data catalog indexes metadata of the organizations’ files, data tables & databases.
- Organizing: It adds descriptions of files and tables and makes your data understandable for the data consumers.
- Tracking: The data catalogs are used for tracking the organization’s data assets. The methods include analyzing the origins of data, graph analytics algorithms, and destination, and informative summaries that include various statistics.
When it is done manually, it will be a time-consuming process. Luckily, the modern data catalog tools have a wide range of powerful capabilities like relationship discovery, pattern detection, pervasive profiling, classification, and automatic harvesting so that you will highlight the data quality issues rather easily and begin applying the right actions.
Advantages of the Data Catalog
The data catalog is important to the business users as it synthesizes all details about the organization’s data assets over various dictionaries just by organizing them in the simple to digest setting. This data catalog offers complete clarity in data definitions, and important business attributes so that all the users understand & leverage the data as an asset. It identifies the data owners or subject matter experts, thus business users will know where they must go whenever they have any important data questions—allowing simple collaboration between various departments.
- Higher data context
- Increased data efficiency
- Higher data analysis
- Decreased risk of error
The powerful data catalog will help you:
- Enable users to access metadata with the data itself
- Make a repository for your data, which includes quality, structure, definitions as well as stats on the data usage
- Ensure data consistency & accuracy just by updating it automatically, whereas allowing a person to edit & stay in a loop
- Simplify data compliance and governance by offering a graphical representation of the lineage of data assets—and tracing this over the lifecycle.
- View & understand the data lineage —that includes source, transformations applied, and one using it
Conclusion
The data catalog must be a cornerstone of all your data processes and strategies. Suppose you want to take complete control of the data, avoid polluting the data lake, build a place of the trusted data in a most collaborative way, begin using the right data strategy and act on the privacy regulations, you need a data catalog. When you choose the right platform it allows you to manage and catalog your enterprise data in one single environment.