Common Data Language: IT and Business

Technology has proven its worth when it has become mainstream and easy to use (intuitive with a common language). Today, the northstar for an enterprise is if every employee could use the data they need, without having to learn too many complex tools & data relationships. How do we enable the employees from various business units(domains) in the enterprise(from HR to sales to finance to R&D) to use their data assets? Does the IT team know what data the domain teams need and how they would need to arrange the data to be useful? What prescriptive and predictive insights would be useful to them?

It has never been more important to bring domain and IT together. Why is this the right time? It is now that we have massively scalable cloud platforms that are capable of storing data in the most optimal format or if we can call it “queriable” format. We also have the ability to use only as needed cloud services, keeping cost controlled. But like any technology, the impact would be felt only if all employees that need access to these platforms can understand how to use it.

Every enterprise has some common (horizontal) and some domain specific functions or business units. The team members of these business units are typically not savvy on Database design and concepts – one could ask why should they need to be? Each business unit today uses many applications to fulfill their job duties. For example, HR teams would use employee record creation, hire to retire software and more. Complexities start when they need to cross reference data from applications not necessarily in their daily use. And yes that is when a spreadsheet analysis is born – haven’t we all seen this? Let us walk through an example of a company offering IT Engineering Services:

An HR analyst needs to understand how many Java developers they need to hire in the next 6 months. This would be determined by some(not exhaustive) of the following data points:

o??Sales pipeline for projects that require Java developers - CRM

o??% closure confidence on these sales opportunities based on historical closures - CRM

o??Number of people available in the timeframe for the project being forecasted – CRM (This could be in the project/manpower planning tool/HRMS and/or CRM)

o??Number of employees having Java developer experience - HRMS

o??Historical data on how long it takes to hire a Java developer – output from HRMS data analysis

o??Pipeline for Java developers – HRMS

** HRMS, CRM could be one or more applications

In this case the model that would need to be developed to forecast number of Java developers needed in the next 6 months, would need to query the above data(ideally already in a Datalake), and then would need to be modeled into a defined schema specific to the business area in consideration. An element in the schema could be “Skill”. Value of the skill field could be Java/Python/PHP. Building the schema definition would need the HR and Data Engineering folks to collaborate. Now if the schema came embedded in an easy to use no code drag and drop interface platform, could the HR analyst independently build the mode in an accelerated fashion?

Making the implementation of each new use case simple by allowing the knowledge of domain to permeate into the Data Platform – would be key to introduce agility in unlocking value in an enterprise’s data assets

Having a common data model allows domain/business users and tech executives to speak a common language and derive most from their data.?Check how some enterprises are well into bridging the IT and domain gap, with the every growing/evolving Industry Data Models built into Azure Synapse for both Power and Citizen Users: Overview of Azure Synapse database templates - Azure Synapse Analytics | Microsoft Docs