Data management is the practice of collecting, storing and using data efficiently, securely and cost-effectively. It is important for any organisation that wants to use data as a raw material for processes to achieve organisational goals. However, data management is not an easy task. It involves many challenges and complexities that you can by no means solve with tooling alone.
It is therefore important to consider three important aspects when considering data management: tooling, processes and people. These are three components that make up the data management ecosystem, and collectively determine its success. In this article, we want to dwell on this, and also why it affects the choice of a partner to support you in this regard. First, let’s look at why these three aspects are so important.
Tools
Tools are the software and hardware solutions you use for data management. Tools help you automate, streamline and optimise data management. Think of data ingestion, data transformation, storage, security, quality, governance, analytics and reporting. Finding the right tools for data management is important because they influence the performance, scalability, reliability and usability of your data.
Things to consider when selecting tools include:
- what kind of data you want to manage (type, volume, etc.);
- the available budget and the business case;
- compatibility and interoperability with existing systems;
- ease of use and management;
- security and laws and regulations.
What you also need to think about is how the data management solution will support your organisation (use case), and, conversely, how your organisation will support the data management and tooling (management and adoption). They are inextricably linked because data is ultimately one of the key raw materials for insight into, and value for, your business strategy. This collaboration manifests itself in the processes. Data management itself is ultimately a business process that can support and optimise other business processes. By thinking about your business processes, you can better align your data management with your organisational goals and needs.
Processes
Business processes and data management processes are both important for the success of your organisation, but they have different goals and characteristics. Business processes are the tasks and activities your organisation performs to achieve specific business objectives, such as delivering your product or service to the customer. Data management processes are the policies and procedures your organisation applies to manage the data needed as raw material in business processes, from input to archiving or disposal, throughout the organisation.
Business processes aim to improve the efficiency and effectiveness of the organisation, while data management processes aim to improve the quality, reliability, and visibility of the data. Business processes and data management processes are closely linked because the data feeds and supports the business processes, and the business processes in turn generate the data to use it again after the data management process.
Data management processes
Data management processes are the methods and procedures that determine how data management activities are carried out. These processes help establish the methods, best practices, and guidelines for your data management, ensuring the consistency, accuracy, and reliability of your data. Designing and implementing effective data management processes is thus crucial because they affect the quality, usability and value of your data.
Some examples of data management processes include:
- managing the data lifecycle, which includes the phases of creating, acquiring, storing, using and decommissioning data;
- managing data quality, which involves the assessment, improvement and monitoring of data quality dimensions, such as completeness, validity, accuracy, consistency and timeliness;
- data governance, which provides the framework and structure for data management, including data ownership, stewardship, roles, responsibilities, policies and rules
Data management processes therefore align your data management solution with the needs and goals of your organisation, and improve the quality, reliability and visibility of your data. What you need to explicitly consider when developing these processes are the roles and responsibilities of the stakeholders in these processes. This brings us to perhaps the most important aspect of successfully applying data management: people.
People
Perhaps even more than processes, data management comes together with the people in your organisation. People are important for effective data management in an organisation because they understand, use and improve your data.
Data management in your organisation depends on the involvement and expertise of people from different departments, not just the IT department. This is because the deep understanding of data, how it is being used, and what requirements it has is spread throughout the organisation. The entire organisation also ensures that the data is clean, structured, secure and accessible for analysis.
Therefore, it is important to involve people from all relevant organisational units in, for example, describing the data in a data catalogue, and in establishing standards, processes and policies to ensure data governance. Ultimately, it is also the people who use your data to generate valuable insights and achieve organisational goals.
Involving people in data management is crucial because they influence the culture, collaboration and handling of data.
Some factors to consider when involving people are:
- the existing skills and competences of data management professionals and business users;
- the incentives and rewards for data management performance and contributions;
- the focus on feedback, evaluation and satisfaction with data management;
- the collaboration and structural consultation of data management teams and stakeholders in, for example, ‘the business’.
Some examples of data management roles are:
- data owners: the departments or colleagues who have the authority and responsibility for certain data;
- data stewards: the data specialists who take care of data quality, governance and usability;
- data analysts: the data professionals who perform data analysis and reporting to generate insights and recommendations.
A data management partner
When dealing with a complex issue like data management, it is important to understand from which direction you can, or should, seek support. First of all, you will have to deal with the supplier of your tooling.
Although they initially have the appearance of being a partner (they always want to sell their product to you), you can indeed expect an attitude as a partner. At a minimum, what you should expect from the vendor is that:
- they help you understand what the requirements are and how the technology fits in.
- they have a good theoretical and practical knowledge of the entire data management field (e.g. DAMA certification).
- they have a broad IT knowledge and experience in order to think along with you on a broader level.
- they can support you locally with implementation and support, in your native language, and during your office hours.
Data management is a complex and challenging undertaking that requires careful consideration of tools, processes and people. By choosing the right tools, designing effective processes and empowering and engaging people, you can achieve successful data management that delivers value and insights for your organisation.
Choose a partner who can look beyond data management. Who knows all aspects of data management, and who can implement
