Data Self-Service

Self-Service and Data Enrichment are mostly confused with each other where data enrichment is just one part of one of the types of self-services.

Self-Service is about empowering business users and decision makers to conduct activities by themselves to shorten the end-to-end delivery time. At the same time, it’s too risky to allow people to go and make changes if they don’t understand data. So, I would say, Data Democratization is a pre-requisite for any type of Self-Service. There are many types, but we will only discuss below.

Types

• Data Self-Service: In this kind of self-service capability, data friendly environment is made available for users, where users are trained on data, users are allowed to question data accuracy and integrity, users are allowed to manipulate and extend the context of data via Data Enrichment process where first-hand data is enriched with second-hand and third-party datasets for better decision making.
• Analytics Self-Service (data citizen): This self-service mostly involves machine learning, data modelling or in other word data science related activities. Data Citizen are major users of this self-service where they run data science or data mining models using low or no code tools. Data Enrichment can also be done using this self-service capability.
• BI Self-Service: As the name explains itself, the users are allowed to connect to any source systems either internal or external, of course based on the access level, and create reports and dashboards on their own. This is majorly to reduce the dependency on IT to create reports for business users. In this era, the paradigm of reports and dashboards creation has moved from IT to Business users.