In today’s data-driven world, businesses face major challenges in adapting to Big Data, as traditional tools struggle to meet modern needs. This article discusses the evolution of data management, from siloed systems to the growing complexity of Cloud infrastructures, and the urgent need for fresh, integrated approaches to data governance.
Today, everyone is well aware of the importance of data.
Or, to put it another way, not worrying about it means living outside our time, with all the consequences that implies.
And yet, how difficult it is for companies to enter OUR time.
Let's sum up the situation in 5 points:
1. Business teams have always used data to achieve their objectives.
2. For 30 years,data has been used in relational database management systems (DBMS) to meet user expectations.
3. It has always been the responsibility of the information systems department to provide access to data for all company employees.
4. The volume and variety of data has increased dramatically over the past 20 years.
5. The market offers siloed solutions to companies in such a way as to confuse them.
Interested? Then let's go into the detailed explanation:
1. On "data serves business teams
It's clear that data is the key business tool for all companies in all sectors.
Over the last 30 years, a number of software packages have been created by technology publishers to meet the specific needs of businesses, giving them easy access to all the available data they need to do their jobs.
So, accounting software, CRM software, logistics software, cash register software, etc., have all emerged from the ground. Sometimes they're software packages, sometimes they're software programs, but in any case, their scope of functionality is always clearly defined. These software packages "speak" to the business because they embody the processes that users need to go through to carry out their day-to-day activities. Today, these processes are referred to as "use cases", or in other words, data processing scenarios that reflect the work processes of the business.
These software programs are easy for future users to evaluate, as they can immediately project their daily lives into the tool.
For the past 30 years, our professions have been "educated" on use case models. This makes it very difficult, and sometimes impossible, for them to project themselves in any other way.
The world we live in now is the world of BIG DATA, and neither software, software packages nor RDBMS are designed to address the technological problems of Big Data.
2. On "the use of RDBMS - relational database management systems".
These programs were designed at a time when the volume and variety of data were totally under control.
Nor was there any difficulty in accessing the data, which was systematically hosted in the same place, either on the company's premises (on premise) or at a dedicated hosting provider.
¾ of the applications ran on several DBMS, but most of the time they were relational database engines only.
This meant that the IT department had very little difficulty in deploying the software and then giving users access to it.
There were challenges, of course, but they were within everyone's reach and were addressed in silos by the techno market.
The world we live in now is one of public cloud, private cloud and on Prem.
Companies are navigating between their legacy on Prem and their various new infrastructures deployed in different Clouds.
Obviously, data is everywhere.
Of course, getting data to communicate across these different infrastructures is anything but trivial.
Obviously, in the age of BIG DATA, data no longer runs on relational DBMS.
And of course, it's crucial for today's businesses to have access to all this data even faster and more easily than 30 years ago.
3. On "the enterprise IS is a supplier at the service of a company's business departments".
The CTOs of the time - still known as CIOs - were still quite technologically savvy, and had a good grasp of the technologies on the market.
There has always been a gap in understanding and communication between IT and business teams.
This gap should have narrowed with the advance of BIG DATA technologies, but it has widened.
Technological difficulties have multiplied, making access to data more complex and less obvious for businesses ina world that has become ultra-connected for everyone - what a paradox!
4. On "increasing data volume
According to a McKinsey study in 2022, the volume of data will increase by 40% a year.
As a result, companies have no choice but to be able to absorb and exploit this annual growth, or risk suffocating.
What's more, according to the study, only companies that are able to use at least 60% of their data can build a solid future.
At present, companies use only 3 to 5% of their available data.
It's clear to you, I suppose, that decisions are not the same when accessing 3% of the company's data or 30%.
5. On "market siloing of solutions
In order not to make things easier for anyone, business or IT, the market has sought to respond to the challenges of BIG DATA without changing the paradigm and by maintaining the classic approaches:
- We're going to continue to talk about "use cases" in the trades, even though we've known how to make pie charts for over 30 years .... So that's not the problem at all.
- We're going to continue to talk about technology in silos, so it's easier to understand, whereas the problems lie in data flows and accessibility.
- Come on, you can't be serious!
New context, new constraints, new way of thinking.
Change is so hard for the human race!
