Part 2: System owners are key in data analytics projects
Nathi Dube, Director, PBT Innovation at PBT Group
In my previous blog, I discussed the critical role source system owners play in data analytics projects. They are essential in the data value chain, ensuring that data is effectively managed and used. This month, I turn my focus to the benefits that collaboration between these system owners and data teams can provide organisations.
An important thing to remember is that the relationship between data analytics systems and data sources is bi-directional. Trust between source system owners and data teams is therefore essential if analytic projects are to deliver the best possible return.
Consequences of non-collaboration
If there is no collaboration between these important stakeholders, data projects can fail negating any investment a company has made in data analytics platforms.
When source system owners are excluded, the overall quality of data can suffer, causing a chain reaction that affects various data-driven initiatives. This can include the implementation of Artificial Intelligence (AI) and machine learning services. Additionally, customer service may be compromised if companies do not have accurate and current information available.
Some source system owners use reference tables to store configuration information such as account statuses and customer types. These are often represented by numbers that must be decoded and mapped to the appropriate labels and descriptions. Simple details, like knowing if monetary amounts include tax or if ‘1’ signifies ‘Yes’ and ‘0’ signifies ‘No’ in the database, are crucial for accurate data interpretation and usage.
When source system owners and data teams operate in isolation, the likelihood of failing to meet the business’ data requirements increases. This can occur either because the necessary data is missing or because data teams lack the expertise to correctly extract the required data. Such gaps can significantly impact the business, especially concerning critical data and reports.
A partnership for success
The advantages of having source system owners and data teams working closely together are significant. Beyond enhancing data accuracy, this collaboration boosts overall efficiency in delivering data analytics projects. It does so by facilitating smooth information flow, particularly during the design and analysis phases.
This teamwork also streamlines and optimises the execution phase, as questions regarding data mapping, transformation rules, and other source data issues are resolved faster and more effectively.
When any concerns around the quality and correctness of data are eliminated, the resultant increased confidence can result in more successful projects. For their part, the source teams are available to assist with any necessary reconciliations, ensuring high data quality throughout the development phase.
Being involved
Having source system owners and data teams working together is the key to any successful data analytics project. It does not matter whether the source system is managed internally or externally, data teams require the support of these owners to ensure project success.
This means organisations should design their IT departments to promote a close working relationship especially when it comes to data teams and source system owners. Actively collaborating on data analytics projects has become imperative in today’s connected business environment.
