What Is Data Enrichment? A Guide for Non-Engineers.
In today’s data driven world, organizations are generating tremendous amounts of data on a daily basis. However, this data alone is not enough to make better and more intelligent business decisions. Therefore, businesses require enriched data that is helpful and relevant so that organizations can extract actionable insights from it. This is where Data Enrichment plays a major role
In this blog, we will be looking at the concept of Data Enrichment by understanding how Discovery & Business Metadata helps in enriching data in simple terms.
What is Data Enrichment?
Data enrichment is the process of enhancing the value of a given data set. It involves the addition of relevant additional information or context to help improve the quality of existing data. The resulting enriched data set can then be used to achieve specific business objectives.
Discovery: Finding Your Data Assets
Discovery is the process of finding and identifying all the sources of data in the organization. These sources can include databases, spreadsheets, data in clouds, and apps.
- Discovery helps in finding all the data sources that one has.
- The data sources are scanned and listed in a great detail so that one has total clarity on where exactly their data resides.
- This step is essential since one will not be able to enrich data they do not know about.
Business Metadata: Adding Meaning to Data
Business Metadata can be described as the kinds of data about your data that explain what it is and how it should be used for your business.
- Such metadata examples include data definitions, business terms, ownership, usage, and data quality.
- It is better to think of Business Metadata as tags or annotations that answer the questions “What is it?” and “Who is responsible for it?”
- This approach helps business users understand the meaning and importance of the data.
How Discovery and Business Metadata Work Together for Data Enrichment?
By combining the Discovery and Business Metadata, one can get data enrichment:
- Discovery finds and identifies the data.
- Business Metadata tags it with information necessary for its proper understanding and use.
- Together, they allow getting data enriched and simplified in terms of being found, understood, and applied.
Why Is Data Enrichment Important?
- Improved Decision Making: Better decision making process by providing more informative results
- Increased Trust: Establishment of trust and confidence through providing more data transparency and understanding.
- Better Collaboration: Better collaboration by establishing a common language and shared ownership.
- Time Savings: Overall reduction of time spent researching and guessing about the data.
Real-Life Example 1
Imagine that you work in the marketing team and need to analyze the information about the customers to see what they buy most often:
- Discovery enables you to find all the customer data hosted in the company’s different departments.
- With the help of Business Metadata, you are able to learn more about the data fields (e.g., “Customer ID,” “Purchase Date”), their definitions, owners, and data quality.
- Having this information, you can build reports and marketing strategies.
Real-Life Example 2
Imagine you own a small bakery:
- Discovery finds all your sales, ingredients, and customer contacts stored in various places (notebooks, spreadsheets, apps).
- Business Metadata labels them as Daily sales, Baking supplies, and Loyal customers.
- Enriched data helps you respond to the amount of bread sold yesterday, the ingredients you need to purchase, and who to offer discounts to.
Conclusion
Data enrichment through discovery and business metadata can be compared to tagging your photos or files so that everything is organized and easy to navigate. It can help companies save time, prevent errors, and ensure that they are making the right decisions.
In order to ensure that the company has the most out of their data, it is important that they begin with discovery and add structure with business metadata.
