blog

Home / DeveloperSection / Blogs / 3 Pillars of the Data Economy

3 Pillars of the Data Economy

Simond Gear1419 12-Sep-2017


                                3 Pillars of the Data Economy


Our industry continues to see an ongoing upsurge in data volumes. This comes with the insatiable need by industry-leading companies to exploit existing data to foster business development and growth. We can see the data economy expanding as the many barriers that hinder and impede its progress are torn down.

In this article, I will discuss the trends that will drive the data product creation process. I will give a rundown of the considerations that will shape the data products of the future.

Customers’ problems come first

Most technically inclined users, such as data scientists, engineers, and architects, prefer to interact with the raw data, as they know how to import, transform, visualize, and combine it with other data sources. However, most customers do not have this capability. The data products presented to them may not be what they want. 

Read Also: how to avoid a data breach

In this regard, the best data products are the ones that the users need. This means that in the process of creating the product, the customers’ problems must be considered first before the data. Determining exactly what the customer’s problems are and how the data can solve these issues goes a long way in defining the foundation of the product. 

Simple data is best

Most users cannot consume all the data they have access to nor should they be given more than what they need. In this regard, industry leading companies will be using data to build a basic product that addresses a specific customer need. End users should be provided with usable data products that can solve their problem and not what the product creators want them to have. 

As technologists, we are quick to develop solutions, which we are uncertain will work. What leading companies in the data economy do is they break down the solution into smaller modules that they can use to build an MVP (Minimum Viable Product). They then determine what data they need to expand it. They do not think of all the possible data they can add to the solution, which end users don’t need, nor do they spend a lot of man hours working on the product before launching it. 

It is best to create a simple product that can grow more complex over time. Starting with a complex product can make it impossible to later modify and adjust it to the customers’ needs.

 Also Read: The Impact of Big Data on Social Media


Updated 21-Mar-2018

Leave Comment

Comments

Liked By