9 Data Segmentation Challenges: Have You Faced Them?

It's common to face various challenges during data segmentation that test our resilience and complicate the process completion.

The icaria Technology team has confronted numerous challenges throughout the many data segmentation projects they have developed.

Some of these data segmentation challenges are quite common, others are more complex, and some might not seem like a challenge at first glance.

In this article, you'll find those challenges you should be aware of and how to address them.

Let's get started!

Data Segmentation Challenges

Data segmentation challenges can be classified into 3 different types:

  • Technical Challenges.
  • Execution Challenges.
  • Infrastructure Challenges.

What are the challenges that most test your team's capacity for work?

Regardless of the type, we will address all of them to be capable of having the necessary information to confront them.

Technical Challenges of Data Segmentation

These are the challenges we generally encounter at the beginning of a segmentation process, mainly relating to the discovery, configuration, and preparation part of segmentation.

Within the technical challenges, we can primarily differentiate three:

  • Identification of Relationships in Data Segmentation: This challenge is not only about locating physical relationships defined in the model but also logical ones, which are usually not documented.
  • Many Systems, Variety of Database Technologies: That is, the interoperability of different systems within the same structure allows actions within the same movement in varied systems. For example: Oracle, DB2, flat files, hierarchical databases, DLI, VSAM, SAP, etc.
  • The Role of Information in Data Segmentation: It's not only about identifying the different types of data and their location but also distinguishing the structures these data belong to and the role they play within them.

Execution Challenges of Data Segmentation

Execution challenges are those that appear during the effective period of data movement. We can differentiate the following challenges in this area:

  • Execution Times: Adapting delivery time to the needs of the client is one of the great challenges of segmentation. This includes the correct use of indices, having an architecture adequate for this purpose, or dedicating a few days of the project to study and improve the overall segmentation process.
  • Optimizing Access to Information: Managing, identifying, and requesting the appropriate indices for the structures to be extracted so that execution times are contained. Additionally, the use of database resources should be adjusted to the hardware limitation that usually exists in non-productive environments.
  • Clean and Collect: Data Erasure in the Target Environment: Given the mentioned hardware limitation of the target environments, it is advisable to be organized and execute periodic cleanings of such environments. Thanks to this, we will only maintain the trace of those data that are truly necessary.

Infrastructure Challenges of Data Segmentation

Last but not least, are the infrastructure challenges. These are problems or circumstances that we find in environments, whether database, middleware systems, batch processes, connection management, among others.

And, just like in the previous classifications, three main challenges stand out:

  • Translation and Coherence in Sequences: The integration of icaria with the software running in the target environments requires proper management of the sequences found in the different databases. This is so that collisions between the delivered data and the data generated by the applications do not occur.
  • Alignment of Environments, Achieving Equivalent Environments: It is most common to find a lack of alignment in pre-productive environments. The reasons for this are various: poor management of deliveries, deficient maintenance, or simply that there was no need to carry out this action until the time of segmentation. For a satisfactory delivery of a structure, it is necessary that the main entities at the catalog level related to the data to be delivered exist in the destination system. Otherwise, alternatives such as translation to default values can be considered.
  • What if the Destination Has Real Data?: The existence of real data at the destination causes multiple problems in delivery, such as: duplicate indices or management of the deletion of structures. The segmentation process must take into account the possibility that there are data that were not created by the tool, even some that at some point were recovered from production. Therefore, such data must be managed in such a way that they do not conflict with those being delivered. Nevertheless, the recommendation will be to explore the deletion of this information or the execution of massive disassociations before starting the segmentation process.

The importance of knowing these challenges lies in the fact that it is common to find that those who are going to implement a segmentation tool for the first time underestimate the difficulties that we face in the day-to-day of a project.

It is important to know them so that the effort to overcome these challenges is evaluated and valued with the aim of ensuring that the project goes forward in a timely and proper manner.

Need help addressing the strategy for enterprise management software testing? Contact icaria Technology now and start improving the quality of test data management software.

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