One of the goals of our Data Office is to create data products that support our business. These can be simple dashboards, AI-driven models, or recommendation engines. If you are new to data products and wondering how to best start, which people you need to involve, and what steps to take, you’ve come to the right place. In this blog we’ll walk you through our creation process in the context of a data product we recently deployed for our colleagues.
Identify the ask from the business
Define the data product owner
Iterate the prototype, evolve the requirements
Create the data product
A data product is built to addresses a particular type of a problem and it enables an end goal through the use of data. It is not just about analyzing and delivering data, it is a product that delivers results based on data. Most of the services we are all familiar with are big data products or big groups of many data products- such as Google, Netflix, LinkedIn and Facebook. Indeed, LinkedIn’s People `You May Know` function is a data product viewed by millions of customers, and it’s based on the complex interactions of the customers themselves
A good data product needs to be a solution of a specific problem. Therefore the first step is to pinpoint your or your customer`s need and identify how you can solve this problem. Find out where you need more information to perform your job better and look for the insights and unique solutions that will lead you to make better decisions. With an objective and focus, you will have a definite foundation of your data product
You need to reach data deeply, from each individual source to find correlations that weren`t visible before
Your data has to have appearance across an entire segment or industry etc.
It is very important for you to be able to compound data from different sources across industries
The visual representations that reveal patterns have to make sense, be understandable, readable and be presentable