The Basics of Data Management

by | Mar 8, 2019 | General

 | 4 min read

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The concept of data management tries to find a solution to a number of common problems. Problems that can occur when you work with user-related data. Data management also has no general definition. This also raises some questions, such as “What exactly is data management?”, “how can it be most efficiently applied to existing processes?”, and “where does data management begin and end?”
Every company or team handles data management differently. It depends on how they structure their data, what their goals are and what general work processes they have. When implementing a data management process in your team or organization, you should consider some generally accepted facts.

Start with data management

Companies discovered information as an important asset with the information society replacing the industrial society. With data becoming a valuable production factor the management of said data started to become a necessity. Today data can be gathered during nearly every step along the user journey and is even producible using for example surveys or user tests. But always collecting or generating more data doesn’t directly lead to benefit (which we also detailed here). On top of that, the Usage of data needs to find a balance between being ethical and being economical.

Data Management is concerned with the different steps that ensure a smooth flow of information. Planning, modeling, monitoring and regulating the information flow and communicating information inside of organizations in order to reach pre-defined strategic goals. Considering this, data management shares a number of characteristics with strategic communication management.

It is important to share information within teams and organizations. Let teams gather appropriate information from the existing data pool and let them communicate within and across teams as freely as possible. That way goal-oriented data processing, evaluation, and communication can happen in the most efficient way.

Managing data responsibly

As mentioned earlier, you don’t want to use data only in the most economical and efficient way. You should also consider how your users think about the use of their data and act ethically. On this basis, data management has four main tasks:

  1. Assess need for information: the first step is to identify which information is necessary to reach a pre-defined goal. If the corresponding data is available, the needed parts of its content, necessary presentation and time and context in which the information is need should be precisely defined.
  2. Collecting available information: You should identify and ideally summarize all available sources of data (internal and external) in one archive or repository.
  3. Access rights: after processing the data in a way that transforms it into useful information (e.g. transcribing audio files) you need to make it available to relevant interest groups. The distribution of access rights has to be considered from a technical as well as legal perspective.
  4. Maintenance of data: once the access rights to the appropriate information have been matched with divisions and teams the responsibility to maintain the data to keep it usable should be allocated.

Keeping the overview

Data management’s main goal is to put you in control of the user-related data that’s available to you. When done properly, it provides you with access to the appropriate set of data where and when you need it completely regardless of to location at which it is stored. As a consequence of this, it enables teams to avoid conflicts that arise from ambiguity and miscommunication.

In order for these benefits to take effect, everybody who works with a company’s data should adhere to the so-called data management practices. These are best practices regarding storage, backup, access to as well as the retirement of data within a company. As an end-to-end life-cycle, data management provides you with practices, procedures, and policies that manage every need within your data’s life-cycle in an appropriate way.

Enhanced security through data management

To improve marketing, decision-making, product classification, and sales, data management doesn’t only work with internal data but also uses external streams of information. Because of this, the safety of the gathered data is an important factor to consider. This doesn’t only comprise finding the safest possible way to store and distribute data but also certain rules and guides concerning the use of data that everybody who works with this information needs to adhere to.

The part of data management that deals with data protection, compliance and security is called data governance. There are three main areas of applications when it comes to data governance:

  • Data quality: making sure that all information that is needed to reach pre-defined goals has already been gathered, is up-to-date, structured in a way that makes it usable and processable and the needed access rights have been distributed.
  • Data maintenance: raw data can’t usually be used directly. It needs to be cleaned up by identifying and correcting or eliminating mistakes. Information should also be updated on a regular basis to avoid it becoming outdated.
  • Data compliance: the use of data is tightly connected to certain ethical and moral guidelines, laws as well as standards and guides that have been defined by the company. Data compliance ensures that everybody who works with the data adheres to these guidelines.

It is an ongoing process

These standards shouldn’t only be met to avoid being sued. Data governance ensures that the processes concerning access rights to data and the work with available data are clearly defined by a set of rules that aims to make the adherence to existing guidelines and laws easier for everybody working with data. As a part of data management, data governance is an ongoing process.

Data management ensures that data within companies is structured and of high quality. It also makes sure that everybody has possessed the access rights they need for their daily work. But most of all it helps to recognize risks that can arise while working with data and avoid them. An effective management process can help to use available information to its full potential. This despite the fact that it reduces storage costs and the time required to find a specific piece of information. As stated at the very beginning of this post: there isn’t one solution to manage your data. Every team or company will need an individual solution. The basics above should give you a general idea of what you need to do to start managing your data.

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Mara Weingardt

Mara is interested in all topics around user research, user testing, as well as usability and UX.
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