The 5 key themes for a data-centric approach

Data is all around us. It is generated by people, machines, sensors, and processes. This data is stored, processed, analyzed, shared and used for a variety of purposes. Data is the fuel for innovation, competitive advantage, customer satisfaction and social impact.

Unfortunately, data also brings challenges. Think of risks, responsibilities, costs and increasing complexity. As an organization, how do you ensure a successful transition to a data-driven culture? In this blog post, we will discuss 5 crucial themes that you need to take into account in order to work successfully data-centric.

#1: Data is everywhere

The first important theme is that data is everywhere these days. Data is no longer limited to a central database or a specific department. It is created and collected from a variety of internal and external sources, such as social media, mobile devices, cloud services, the Internet of Things (IoT), and over-the-counter data.

In addition, data is spread across different locations, systems, formats, and quality levels. This means that data is no longer static and structured, but rather dynamic and diverse. While this offers new opportunities, it also brings challenges.

How do you integrate, manage and make data effectively accessible within your organization? How do you ensure that data remains consistent, reliable, up-to-date and relevant? And how do you guarantee data governance, data quality, data security and compliance with laws and regulations (data compliance)?

#2: Data threats

The second important theme is the threat posed by data-centric working. Data is valuable, but therefore also vulnerable. It can be accessed without permission, lost, stolen, manipulated or abused. Cyberattacks aimed at obtaining sensitive data can have serious consequences, such as reputational damage, legal problems, financial losses, and operational disruptions.

How do you protect data from unauthorized access, accidental changes, unwanted disclosure, or irreparable destruction? What are the steps to recover data after a cyberattack? How can you identify attacks aimed at data early and intervene before they escalate further? And how do you report a data breach or a successful cyber attack to the regulator?

#3: Data Loss

The third important theme is data loss, a growing problem for many organizations. While external cyberattacks often get the most attention, insider threats are equally significant. Employees with malicious intent or (unintentional) negligence can leak sensitive information, which can lead to significant financial and reputational damage.

In short: It is crucial for organizations to invest not only in external security measures, but also in monitoring suspicious actions by employees. Increase awareness among employees, set up access to data in a secure way, ensure proper management of data by cleaning, archiving or deleting it as soon as it is outdated, irrelevant or superfluous.

#4: Data Compliance

The fourth important theme is data compliance, which is essential for any organization that works with sensitive information. Organizations must comply with legal and regulatory requirements to protect data. A well-known example in the Netherlands is the General Data Protection Regulation (GDPR). This legislation requires companies to implement security measures to prevent unauthorized access, data breaches, and cyberattacks.

Compliance with data compliance not only helps to avoid fines and legal issues, but also strengthens the trust of customers and partners. In addition, the AI ACT, which went into effect on August 1, 2024, has significant data compliance implications for organizations that design or use AI systems.

#5: Data & AI

The fifth important theme is the close relationship between data and artificial intelligence (AI). Data is the foundation for AI, while AI enables the application of data. Data is used to train, test, improve and control AI systems. Conversely, AI can help generate, analyze, visualize, and activate data.

The combination of data and AI can lead to new insights, solutions, products and services. At the same time, they can also bring new questions, dilemmas, challenges and risks. How can you use data and AI in a responsible, ethical and human-centric way within your organization? What are the best practices for implementing data and AI in a reliable, robust, and secure way? And how do you use data and AI in a transparent, explainable and verifiable way to achieve your goals?

And now? 

Do you recognize the above questions and are you struggling with them? Don't worry, we are happy to help you. Data-centric working is a complex challenge that requires a strategic approach. It includes not only organizational changes and technological innovations, but also a culture change within the organization. Finding the right balance between the opportunities and challenges, advantages and disadvantages, and possibilities and limitations of data is essential. For example, ask Microsoft Copilot to list the 150 most commonly used terms around data. By following the following five themes, you can confidently get started and achieve success with your data-centric approach.

Are you looking for support or would you like to spar about this? Please feel free to contact us. In addition, keep an eye on our content, because in the coming period we will delve deeper into these topics and give you detailed answers.