How much do you trust the data on which you base your decisions? How often have you wasted time and energy searching for information in various documents and systems? Not uncommonly, such a search ends with more than one result, with an unclear result or without any result at all.
SSOT – Short explanation and key advantages
The solution is a single, data-consistent source for all relevant information. A Single Source of Truth (SSOT). The goal of an SSOT is to improve data integrity and quality and to reduce the risk of errors in the management of data. An SSOT enables organisations to better organise and maintain data by guaranteeing that only one source exists for each type of information. Duplication of effort, redundant information and inconsistencies between different data sets can be avoided. An SSOT makes it easier to scale systems by making it easier to add new data sources and update existing data. This also makes it easier to grow your business and adapt to changing business needs. Better decision making and problem solving also become possible as information is available in real time, providing an accurate basis for analysis and reporting. For digital innovation, an SSOT is an important and, in parts, necessary enabler. Eliminating conflicting or outdated data in different data sources improves the consistency and accuracy of data, speeds up data flow and minimises the frequency of errors or misunderstandings. Finding, updating and deleting data is also simplified and accelerated. The reduced complexity enables targeted and rapid maintenance of data assets. Since there is only one source for the relevant data and it does not have to be duplicated several times in different systems, processes and workflows within the system can be designed more efficiently. If implemented correctly, this increases productivity and at the same time reduces operating costs.
However, an SSOT is not a plug-and-play tool. It is a data management concept that requires expert knowledge to implement and maintain. The SSOT concept is usually supported by data management tools and technologies that ensure that all data come from a single source and are accurate and consistent. Such a data source can be, for example, a database or data warehouse where all relevant data for your business is stored.
Implementation of a SSOT
It is important to note that implementing an SSOT can be a time-consuming process that requires collaboration and coordination between different departments and teams. A successful implementation also requires an understanding of the business processes and requirements so that the SSOT meets the needs of your organisation.
Once the project team is in place, it is best to start with an as-is analysis. Identify and prioritise the data sources that need to be brought together from different systems and departments. Once the data sources are identified, they need to be modelled to ensure a consistent structure and terminology. A data model will help to understand and visualise the relationships between data sources. Data modelling should also take into account user requirements, the complexity of the data and the type of information to be stored. The data must be stored in a database or data warehouse in order to manage it centrally. The database structure should reflect the relationships defined in the data modelling.
A data access layer is required to provide access to the database and ensure that data is consistent across applications. This layer can use APIs or other technologies to facilitate access to the database. Select an appropriate method to migrate the data. This may vary depending on the data source and destination. There are different migration methods, such as manual migration, ETL (Extract, Transform, Load) or data integration tools. Test whether the data has been migrated correctly. Check the data for accuracy and completeness and ensure that it is presented consistently in the SSOT.
As the first content becomes available with the start of the data migration, training of future users can already begin during this phase and the parallel tests.
Always monitor the performance of the database to ensure that the data is always correct and up-to-date. Implement a procedure to constantly review the data sources and structure of the SSOT so that it always meets the requirements and business processes. Requirements for future systems, tools, applications and interfaces must be clearly defined to maintain maximum compatibility.
Common challenges
The implementation of an SSOT can be very complex. Challenges can be expected especially if the company already uses many data sources and formats. The quality of the data is a crucial factor for the success of SSOT. It is important to ensure that all data is accurate, up-to-date and complete so that the system is effective. If data is inconsistent or incomplete, this can lead to errors and cause lasting damage to trust in the system. Access to data must be clearly defined, logged and controlled. This is the only way to prevent unauthorised changes, deletions and extractions. Fundamentally, an SSOT can be more vulnerable to cyber-attacks as there is only one source for hackers to target. It is important to take appropriate security measures to prevent this. Certainly, the introduction of an SSOT also involves changes in the way of working. By its very nature, this may be met with resistance. If this leads to a lack of cooperation and support, the implementation is made much more difficult. The SSOT concept usually scales well, but care must be taken to ensure that the system is based on the appropriate technologies and tools and can handle the growing number of users and data requirements. In most cases, implementing SSOT requires integrating numerous systems and updating existing databases and applications right at the start. Without clean communication and project management, implementation takes longer than necessary, increasing implementation costs. Yes, implementing an SSOT can be expensive. The more data sources there are, the higher the cost of integrating and consolidating that data into the SSOT. The type of data to be stored in the SSOT can also affect the cost. For example, if the data is large or unstructured, the cost may be higher because additional hardware or software may be required. Another cost factor is integration with other systems, as smooth operation may require adjustments to existing systems.
Conclusion
All in all, an SSOT is a worthwhile investment for companies working with many data sources and at the same time an indispensable basis for contemporary data analyses. If you want to keep track of rapidly growing data volumes, make data-driven decisions and use innovative tools, you should opt for a single source of truth sooner rather than later.
Stefan Reissing – Consultant
junokai