• René Koets, Partner |
  • Evgenia Rüdisüli, Director |

With the abundance of collectable information in today’s business environment, Big Data analytics, Artificial Intelligence and hybrid- or multi-cloud architecture are some of the hot topics in 2021. Data-driven businesses are said to offer greater transparency, cost efficiency and customer focus.

However, amongst this trend, data saturation is also becoming an increasing discussion point. Many organizations appear to store data without a clear understanding and purpose, which in fact acts as a barrier to both internal and external transparency.

Data management as a data driver

To overcome this challenge, it is important to consider the role of data management as a driving force in these data-driven trends. In fact, it is expected that these topics will become increasingly dependent on one another in the future.

On the one hand, the implementation of cloud-based components and predictive analytics technologies, for example, will be highly ineffective if the quality, accuracy and reliability of the underlying data is inadequate. On the other hand, such technologies offer significant improvement opportunities in terms of data management efficiency and capacity.

For that reason, this blog article will list several points on data management that will enhance the quality of your data-driven solutions. Additionally, it will cover some ways in which you can consider your data-driven solutions to improve the effectiveness of your data management processes.

  • Know your data.
    Due to the large volume and different structures that data-driven companies are often working with, one of the first critical points involves understanding your data sources. Identifying the data you are working with, how it is used and who controls it is key to laying the foundation of your data management strategies.

  • Govern your data.
    With a good overview of the different data structures and flows in place, it is then time to focus on clear data governance procedures and policies. By developing company-wide data glossaries and mapping key users to your data, you can ensure that each data segment is properly covered and managed. This will ultimately enhance the level of your data quality and security.

  • Streamline your data.
    In addition to aligning on data management strategies from an organizational perspective, you may also consider (re-)evaluating the ways in which your data is maintained from a technical perspective. Based on the nature of your business, certain storage and analytics processes could be (partially) outsourced or are best kept internally.

  • Guarantee your data.
    To ensure data is available for anyone at any point in time, cloud-related designs are often one of the first solutions that come to mind. The cloud acts as a central storage system that can be accessed immediately and from any desired location. As it is also considered a highly secure way to store data, it is becoming an increasingly important part of the data management strategy.

  • Automate your data.
    Solutions involving Machine Learning and Artificial Intelligence can offer similar benefits. Whereas cloud solutions improve efficiency through its flexibility and scalability, for instance, Artificial Intelligence enhances efficiency through process optimization and automation.

    In practice, Machine Learning has been used to improve database processing queries and automatically prepare datasets. Similarly, Artificial intelligence can be implemented to support with automatic security updates. The corresponding reduction of human error and increased security are only some points that highlight the value of such technologies in your data management strategies.


In conclusion, data-driven solutions are growing in popularity as businesses progress into the 2020s. Without well-integrated data management strategies, nevertheless, data saturation is becoming an increasingly faced challenge that will ultimately hinder business performance. As a result, this blog has explored the relationship between data management and data-driven solutions by highlighting some key actions to focus on. If you want to have more information on the topic – do not hesitate to contact us.

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