A data catalog organizes your company’s information assets so it’s easy for people to find what they’re looking for. Libraries use catalogs to help readers find all of the books available in each of their branches. Readers can search on genre, reviews, and popularity; learn more about the book they want to check out; read the librarian’s reviews of the book; and then find that book in one of the library’s branches.
A data catalog is similar. A data catalog lets data analysts find all the data available in each database or application maintained by their company. Business analysts can search on data type, reviews, and popularity; preview the data; see what others say about it; better understand its quality; and then download the data asset for their project and analyse it.
On top of that, data catalogs which are tightly integrated with a governance platform, help your business comply with changing regulations and policies and help provide your data citizens access to governed data. After classification of data assets, rules can be created that anonymize or restrict access to certain data, so data personally-identifying information does not end up in the wrong hands.
2.7M$
In Savings Due To Shortened Data Discovery Time
585K$
In Savings Due To Business User Productivity Improvements
50%
On-Boarding Time For New Analysts
Master Data vs Meta Data
Data catalogs are often described as being critical to the management of both master data and metadata. While often confused, they are distinct yet at the same time critically supportive of each other.
Master Data
Also called reference data, master data is any information that is considered to play a key role in the core operation of a business. Master data may include data about clients and customers, employees, inventory, suppliers, analytics and more. Master data is typically shared by multiple users and groups across an organisation and stored on different systems.
Metadata
Essentially, data about data. Metadata describes how and when and by whom a particular set of data was collected, how the data is formatted, the relationships between some sets of data and other sets. Metadata is essential for understanding information stored in data warehouses, and is key to helping ensure compliant access and usage. Metadata is also a critical input to machine learning systems, and so acts as a foundational capability for both Big Data and Artificial Intelligence solutions.
Master data is broader than metadata and denotes a bigger set of values than the former, but though distinct, there are closely aligned. Data catalogs are the mechanism though which master and metadata can be synergistically managed.
Key Values of a Data Catalog
Speed and self-service. Rather than submitting requests to an IT group for data that will meet analysts’ business needs, Analysts simply search through a data catalog themselves. This frees up more time for the IT group and means that the analyst wouldn’t need to wait for them to get back to him or her. It provides self-service access to data to data citizens.
Comprehensive search and access to relevant data. You don’t know what you don’t know. An analyst will not know if they’re missing relevant data or the most up to date asset unless they can search across all available data assets. They might find something they would not have been able to find before which can augment their analysis and provide better insights.
Meaningful context. When an analyst finds a data asset that would be useful to them, they can read a description, view business metadata and business term definitions, and read comments provided by others about the data. That way, the analyst can put each column in a data asset in the context of their business.
Improves trust and confidence in data. By previewing the data and profiling it, an analyst can very quickly see if certain fields have null or incorrect values. This makes cleansing the data even easier. The quality scores and social recommendations on the data asset help improve the confidence in data for an analyst to use.
Protects data while ensuring compliance. Instead of an IT professional masking each column, data rules automatically run based on automatic classification of data. So companies never have to worry about the wrong data getting into the wrong hands.
The SmarTek21 Data Catalog
The SmarTek21 Data Catalog is an integral component of our Digital Business Platform. Powered by machine learning, it provides all necessary catalog features while providing seamless integration with all of our solution accelerators and solution.
Key Features
Interoperability
In your digital transformation journey, providing an optimized experience to your customer may be your top priority. But protecting your customer’s data is equally important. The SmarTek21 Data Catalog can inventory and protect your data assets by applying the relevant policies to govern them against misuse (whether intentional or not) all the while ensuring there is data integrity as information is shared throughout the enterprise.
For those organisations that have already implemented a data catalog, SmarTek21 can ensure interoperability throughout API service mesh, allowing you to take full advantage of your legacy infrastructure.