Defining self-service data

23 Feb 2024 | AgileData Way of Working, Blog, Food Analogy, What is


Everybody wants self-service data, but what do they really mean when they say that.

If we gave them access to a set of highly nested JSON data, and say “help yourself”, would that be what they expect?

Or do they expect self-service to be able to get information without asking a person to get it for them.

Or are they expecting something in between.

I ask them which of the five simple self-service patterns they want to find, which form of self-service they are after.

Shane Gibson -

A number of the key success measures for any new data way of working, new data capability or new data platform are always founded on the concept of self-service enablement.

We live in a self-service age

Individuals are now enabled to search for information via Google, book their own travel, scan their own groceries, and check out bank balances on smartphones.

New technology has made it easier than ever to rent out their homes, prepare their financial accounts, and follow the exploits of their friends in near real-time from anywhere around the world.

Human intermediaries have been replaced with technological ones, giving greater control and convenience at a lower cost.

Consumers expect self-service data and information 

New self-service data and analytics technologies introduced in the past decade enable business users to explore and generate insights without the need for a human intermediary.

They can find the dashboards that might answer their questions, find the data they need and export it to Excel, drag and drop data around, write data queries in multiple languages.

But there needs to be guardrails 

But its not just a case of exposing raw data to business users and let them dive deep.

There needs to be adequate guardrails in terms of principles, policies and patterns that enable the users to do the data work they want to, but keep them and the data safe from unintended consequence of the democratisation of the data.

Silver Service vs Self-Service

But not every business user wants to work in data day in and day out, some need data to inform the next action they will take and then move on to taking that action.  They don’t want to spend their time learning new tools and wrangling messy data to do their daily work.

With silver service we treat data and information like fine dining, we present curated, accurate and timely information to a user which they can consume in a single click.

With self-service we provide a buffet of data that can be consumed in many different ways, but it does leave open the risk that somebody will put pork vindaloo on top of their vanilla ice cream.

Consumers expect self-service data and information  

In a data and analytics context there are five initial use cases where a self-service paradigm would improve users time to market to gain access to data, improve their ability to interact and explore this data and improve their ability to share the insights from this data with their peers.

These use cases are:

  • Find
    Finding what data exists, where it lives and understanding its fit for purpose.
  • Connect
    Connecting data together to see patterns across multiple datasets.
  • Explore
    Exploring data to help inform decision making.
  • Share
    Sharing the insights of that exploration.
  • Access
    Accessing the results of insights quickly, without waiting on another individual.

So if you need to provide self-service to your business users, the first step I recommend is asking them which of these five uses cases they are talking about.


Keep making data simply magical

Like all solutions, AgileData is magical at delivering some use cases, and ok at delivering others.

We focus on making all five of these uses cases magical.

While we provide a curated buffet of data, we don’t provide the knives and forks to consume it, we rely on last mile tools to do that bit.


    Do more with less

    We remove the need to build a large dedicated team of expensive data experts, by reducing the effort to do the data work and by doing the data work with you

    Without AgileData

    No Data Engineers

    With AgileData

    AgileData Team-left-small_v4