Mar 08

The Basics of Data Management

The concept of data management tries to give a solution to a number of common problems that arise during the work with (user-related) data. Data management also doesn’t have one generally accepted which leads to questions such as what exactly is data management, how can it be applied to existing processes in the most efficient way and where does data management start and end? Different companies and teams will probably handle data management different depending on the way their data is structured, their goals and general work processes. Still, there is a certain basis of commonly accepted facts that should be kept in mind when you want to implement a data management process in your team or company.

Getting started 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 [Managing insights within companies]). 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.

Data management makes sure information is shared in a sensible way.

To share information within teams and organizations it’s important to find a way to 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 briefly above you don’t only want to use data in the most economical and efficient way without considering anything else. You should also make sure to consider how your users feel about you using their data and accordingly act in an ethical way. Based on this, data management has four main responsibilities:

  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: all available sources of data-internal as well as external-have to be identified and should ideally be summarized 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-best practices regarding storage, backup, access to as well as the retirement of data within a company. As an end-to-end life-cycle starting at the creation of data and ending with its retirement, data management provides you with practices, procedures, and policies that manage every need within you 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.

Data security is one of the main concerns of data governance.

The part of data management that is concerned with privacy, compliance and security is called data governance. Data governance has three main areas of application:

  • 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.

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 is 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 doesn’t only ensure that data within companies is structured, of high quality and everybody has possessed the access rights they need for their daily work but also 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 while lowing storage costs and time needed to find a certain piece of information. As stated in the very beginning of this post: there isn’t one solution to manage your data since every team or company will need an individual solution but the basics above should give you a general idea of what you need to do to start managing your data.

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About The Author

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