Data Modernization and Business Intelligence are key if you want to be successful in the cloud. Frederik Vandeputte and Frederik Bogaerts of Kohera are happy to explain the most important do's and don'ts when migrating data to the cloud.
When a company approaches us to bring its data to the cloud, we invariably start with a modernization assessment. Here we look at what the client has in terms of data and data-based services. Often we see that the company itself does not know how many servers it has, let alone what is connected to them. On the basis of the assessment report, we then draw up the roadmap to the cloud.
The decision to renew the hardware or modernize the databases usually comes from IT, namely when the current hardware is end-of-life or when contracts need to be renewed. On the Business Intelligence side, it's the other way around: the business defines the needs and the way they want to do the reporting. In the middle, IT and BI come together.
The technical advantages of a move to the cloud are well known, but the advantages of a BI migration require some explanation. Of course, the modernization of data and BI go hand in hand, but we also see that the cloud offers some components that didn't exist on-premises and allows to process larger data volumes and do it faster and more efficiently than before.
Taking it a step further, we come to what is known as Self-Service BI. Self what? The formula is as simple as it is to the point: V > V, where V stands for velocity. The speed at which a business changes is greater than the speed at which IT can evolve. In the past, IT was often the stick in the BI wheel. First the demand for new reporting had to be analyzed, followed by the development and testing phase and only after that the realization phase: by then the initial demand was often no longer relevant. Self-Service BI is a principle for quickly analyzing and implementing BI questions.
However, Self-Service BI alone does not work, you need to take a number of steps first. First, you need a corporate BI environment that is built from IT and is robust and performant with solid, daily reporting. Second step is that you give people access to the data warehouses and permission to start building ad-hoc reports themselves. Then you teach them a data culture in which they start combining other data from within the company with data from the data warehouse. Finally, the pinnacle of Self-Service BI is that you succeed as a company in creating a culture in which you also let people use data that they find on their own outside the data warehouse.
Doesn't that high empowerment set the door ajar for shadow IT? That risk always exists of course but if IT sets up a good reporting environment that answers the questions from the business quickly and well, people will choose the easiest way and use the data warehouse.
The data world is not standing still. The next big thing is everything moving around the Azure Arc data services and the rise of the hybrid model. There is a growing awareness, also at Microsoft, that not everything has to be "cloud only". It's an and-and story: you can divide your data between the Microsoft cloud, on-premises and at other large cloud providers and easily combine everything under one umbrella.
Also in terms of SQL Server services, after all the heart of the data platform, we are seeing more and more systems that are 'self tuning'. These systems optimize queries as they come in based on AI. In other words, the system adapts itself.
Another trend we see is the democratization of data. A database used to be a well kept and guarded secret but today we are increasingly going to share our data and figures and use them as a democratic asset. For example, look at the corona figures that are shared with us every day.
Finally, we would like to give one more message to the data community. Our dream is that "we will empower every profession to make the best data-driven decisions" and thanks to the tools Microsoft provides us with, we are getting closer to that dream every day.