The power of data-centric working

What does it mean to work data-centric? How many companies are already doing this? Which concepts are essential for a practical data-centric approach? And what are the five key themes that organizations should look out for if they want to put data at the center? In this blog, we will look for answers to these questions and take you through the importance of a data-centric approach.  

In today's digital world, organizations view data as a strategic asset whose value and potential must be maximized. It is often not about the data itself, but about the targeted use of data to be more efficient, effective and innovative than others.  

A data-centric organization focuses on all aspects of data: from collecting and analyzing it to sharing, managing, protecting and optimizing it. 

How many organizations are data-centric? 

It is difficult to determine exactly how many organizations are already working fully data-centric, as there is no clear definition or measure for this. Nevertheless, various studies give us a good indication. According to a recent IDC survey of 2,000 European organizations, 22% have a data-centric culture, while 55% aspire to do so. In the United States, 92% of large companies consider data a strategic asset, but only 31% see themselves as fully data-driven. 

The challenges of data-centric working 

But what exactly do these figures say? That although there is a great interest and ambition to work data-centric, organizations still see many challenges and obstacles to actually realize this. These can be technical in nature, such as integrating, cleaning and standardizing data from different sources and systems. In addition, there are organizational and cultural challenges, such as changing mindsets, promoting collaboration, increasing skills, and ensuring privacy. A data-centric approach is therefore not something that can be arranged overnight. It is a process that requires time, effort and dedication from everyone involved.  

Data protection and complexity 

A crucial aspect of data-centric working is the protection of data against internal and external threats. This is complex, but necessary to ensure the availability, integrity and confidentiality of data throughout its lifecycle.  

But how complex and large is this really? Just ask Microsoft365 Copilot to provide the 150 most commonly used words around the concept of data. You will undoubtedly recognize many terms, but it can also be a bit dizzy, especially if you do not work in this field on a daily basis. The results provided by Microsoft 365 Copilot illustrate the complexity and breadth of the subject.  

It's about more than just data 

It is clear that data is the fuel for strategic decisions within more and more organizations (who want to work data-centric). But data alone is no longer enough. Data must be created, organized, managed, processed, and protected in the right way to continue to support organizations' goals. For a practical interpretation, various frameworks, methods and techniques are known around data-centric working. Think of concepts such as data governance, threat protection, data security, data quality, data retention and data volume. Data-centric working is not only about the quantity, but also about the quality and diversity of the data. Important concepts that emphasize the complexity and diversity within data-centric works are explained below:  

• Data variety 

Data comes in different forms and formats. Think of data in the form of texts, tables, photos and videos. But data can also come from different internal and external sources. This so-called 'data variety' provides richer and more complete datasets and at the same time creates challenges to integrate and harmonize the data.  

• Data velocity

Data can also be created and processed at different rates, depending on the need and urgency of the organization. This 'data velocity' ensures a faster and more up-to-date data flow, but also requires a high degree of scalability and a lot of computing power from your data systems. 

• Data Veracity 

In addition, data can vary in reliability and accuracy, depending on the quality and integrity of the source and processing. This 'data veracity' creates a higher or lower value and potential of the data, but also requires a greater need to verify, validate and clean the data. 

• Data Value 

In addition, data contributes to the organization's goals to varying degrees, depending on the analysis, insight, action, and evaluation of the data. This 'data value' ensures a greater or lesser impact and result of the data, but also a greater need to measure, assess and optimize the data. 

Five key themes for a data-centric strategy 

At Wortell, we distinguish five essential main themes with which we can help organizations protect and make optimal use of their data. By understanding these five key themes and integrating them into your data strategy, you can take control of your data and use it to take your organization to the next level, including good data protection and compliance.  

In a future blog, I will take a closer look at these five main themes and how they can help your organization gain control over data and use it effectively for success. 

Conclusion 

Data-centric working therefore offers enormous advantages, but it requires a well-thought-out and integrated approach. By implementing the right strategies and techniques, organizations can not only increase their efficiency and innovation capacity, but also protect and leverage their data to the fullest. Keep up with developments and invest in a data-centric culture to take your organization to the next level.