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What is Reference Data?
Reference data is data that helps categorize/classify/label other data. It’s sounds abstract but it’s really simple. Think about that every time you have seen a dropdown, checkbox or a radio button. This is usually used for simple classification. Reference data is commonly known by other names - codes, lookups, lists of values, enums or domains. It’s a subset of Master Data and should also be managed for better data quality, integration and analytics.
Examples of reference data include: countries, accounts, currencies, units of measure, departments, types (e.g. document), statuses (e.g. order), calednar (e.g. quarters), and more.
Examples of reference data include: countries, accounts, currencies, units of measure, departments, types (e.g. document), statuses (e.g. order), calednar (e.g. quarters), and more.
Understand reference data (lookups, codes) with simple documentation
Define lookups and their values
Lookup is a collection of values/codes. Every database is full of lookups. Examples: currencies, country codes, document getTypes, order statuses and many more. Dataedo allows you to define those lookups and document their allowed values.
Explain codes/values
Allow everyone in your organization to understand reference data/lookup by explaining values with titles, descriptions and custom fields.
Extract values from database or define manually
Create a list of values manually or build lookups automatically from your data sources.
Link lookups to multiple columns
Define multiple instances of columns containing a particular lookup (think currency for example).
See value row count in each table/column
See popularity of particular values in specific columns to better understand your data and its data quality.
Link lookups glossary terms
Expand documentation of business terms by documenting it’s domain of values.
Improve data quality & reporting
All Reference data in one central repository
Document reference data from different columns, tables and data sources in a single place. Share complete data documentation with your team.
Understand data quality and define cleansing rules
Easily identify duplicates, wrong values and define cleasing rules for your source data.
Better reporting & analytics
Know what values are allowed for different columns. Identify mistakes in reports easily.
Use cases
Data Analytics
Enable accurate analytics and reporting with duplicate and mistake-free categorization of data such as countries statuses, currency codes and more.
Data Governance
Standarize values and their definitions within your organization to create a consistent understanding.
Data Quality
Identify duplicated and incorrect values easily and fix your data sources.
Data Warehousing
Simplify data integration between different systems by providing trusted sets of lookup values.
Why our customers love Dataedo?
Dataedo is a lightweight solution with great customer service and active product development (recently data quality). The ability to run SQL scripts on the repository brings additional flexibility."
We jump started all of our Data Governance efforts using the tool. We documented key databases quickly and easily and published the information to our analyst community."
Dataedo is an amazing tool that continues to grow and improve."
Datedo consistently improves while delivering exceptional support that is quick, competent, and highly reliable."
Dataedo is easy to use, offers great functionality, and provides excellent customer service that always listens to the customer."
Dataedo excels at data cataloging, and the support from the Dataedo team is top-notch."
Dataedo provides ease of use and covers so many areas from a Data Governance perspective. You really can put everythng in one place."
Dataedo is a fantastic tool, and I love working with it—especially with the continuous improvements being made and planned."
Join 1000+ Satisfied Customers Using Dataedo
Piotr Kononow
Founder
Start documenting your reference data today
Create a central documentation of reference data from all your data sources and distribute it across teams working with data in your organization.