Part 1: System owners are key in data analytics projects

by | Jul 18, 2024

Part 1: System owners are key in data analytics projects

by | Jul 18, 2024 | Blog | 0 comments

Part 1: System owners are key in data analytics projects

Nathi Dube, Director, PBT Innovation at PBT Group

In data analytics initiatives, the primary focus often lies on business users who are the custodians of the data. Despite their familiarity with the data and its residing systems, business users typically lack an in-depth understanding of how data is stored and retrieved. This is where the expertise of source system owners becomes invaluable.

They provide specialised technical knowledge when it comes to the data models and organisational structure within the source systems. Their role is pivotal in the data value chain, ensuring that data is effectively managed and used.

Support provided

Source system owners influence several key areas of data analytics projects. It all begins during the development phase when it is common for source system owners to have a limited view of the business’ data needs. By integrating data requirements early in the project, source system owners can design systems where data is readily available and easily accessible.

The next step impacts the front end design. Being included at the data requirements stage will enable source system owners to influence the design of the source system’s front-end. This ensures that all necessary information is captured efficiently, facilitating smoother data extraction and usage down the line.

Another essential part is being able to reduce the complexity of queries. To aid data teams, especially in scenarios involving complex queries that require joining multiple entities or tables, source system owners can organise data in a way that minimises complexity.

Of course, these specialists are also instrumental in identifying potential data gaps in the new system early on. This proactive approach prevents issues from being discovered later in the project, which could otherwise lead to significant business impacts and costly system changes.

Occasionally, the required data might be available but not in the desired format. Clearly defined and communicated data requirements, addressed early in the project, enable source system owners to ensure that data is available in the right format and at the right time.

Having source system owners working closely with data teams can be immensely valuable. While improved data accuracy is a significant advantage, the overall efficiency in delivering data analytics projects also sees substantial improvement by having source system owners involved. This partnership ensures seamless information flow during the design and analysis phases, making the execution phase smoother and more efficient. Issues related to data mapping, transformation rules, and other source data matters are resolved quickly, fostering confidence in the process. Source teams are also available for reconciliations, maintaining high data quality throughout the development phase.

Being active

The success of data analytics projects hinges on the active participation of source system owners. Their technical expertise and collaboration with data teams ensure that data requirements are met, systems are designed efficiently, and data quality is maintained. The company’s leadership must also foster a collaborative environment between IT teams to support these efforts, enabling innovative data analytics solutions that drive business success.

Fundamentally, having a well-designed data analytics platform in place is fundamental for business growth in today’s digital age. Source system owners are central in this regard as they can optimise systems to unlock significant value from the underlying data.

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