Data. A huge asset to companies when gathered and analysed correctly. The importance of data continues to rise up businesses’ agendas as they see how it can be used to improve growth. Implementing an effective data product strategy is a sensible option for many, which is where the data product manager steps in. Suki Dhuphar, Head of EMEA at Tamr, explains what a data product manager is and their essential skills.
Data governance isn’t new, but it’s enjoying its moment in the spotlight. Why the sudden rise to prominence? One answer lies in the trend of businesses wanting to harness the power of their data, i.e., to make it more usable. Consequently, organisations are increasingly turning to data products to meet this need. However, effectively implementing a data product strategy requires the right skills. Enter the data product manager.
But what is the remit of this role and the key skills of a great data product manager?
Let’s start by defining a data product,
What is a data product?
Essentially, data products represent the best version of a company’s data. They are clean, curated and trustworthy datasets that make data tangible and accessible to everyone within the organisation, fostering more accurate insights for business decision-making.
We advise employing a data product manager to maximise the value derived from data products. Responsible for developing and delivering data products, a data product manager ensures data product implementation and, arguably even more crucially, that the data products provide tangible value.
The role of the data product manager
A data product manager’s role is multifaceted. Their primary responsibility is to oversee the development of a data platform, or a suite of specific data tools, designed to serve both internal and external customers.
However, they are not merely passive overseers. The data product manager is a problem-solver who wears many hats. They collaborate cross-functionally to pinpoint challenges, establish requirements, guide teams, eliminate obstacles and deliver products. With this expansive scope, they integrate seamlessly within the broader data team.
Bringing a new set of skills to the data team
The data product manager is a pivotal member of the data team, bringing a distinct skillset that differs from other professionals, such as data scientists or data engineers. For instance, while these roles demand the technical expertise to create AI/Machine Learning models and comprehend the software development process, data product managers aren’t primarily tasked with the technical aspects of developing data products. Instead, their role is rooted in people engagement and strategic planning.
Data product managers enhance the team by anchoring its client-facing functions. They adeptly pinpoint challenges, define requirements, clear obstacles and ensure the successful delivery of the data product. They excel in understanding the needs of business leaders across various functions and work collaboratively to address any challenges. The strength of a data product manager lies in their ability to discern customer needs, guide diverse teams effectively and roll out functional data products.
Essential skills of a great data product manager
Since data product managers are an emerging role, it’s important for chief data officers (CDOs) to understand what skills to look for when hiring.
- Understand data
While data product managers might not possess the technical prowess to craft data products directly, they must have a robust grasp on data to effectively manage its implementation. They should be aware of where data resides within an organisation and the means to access it. Further, since the bedrock of a data product hinges on data quality, these managers must be versed in data quality and data trustworthiness.
2. Grasp analytics
A firm understanding of analytics is pivotal for data product managers. They need to comprehend how business leaders utilise analytics for informed decision-making, especially since data consumers predominantly engage with data products through these analytics. Additionally, since good data products utilise Machine Learning models, it’s beneficial for these managers to have foundational knowledge of AI and Machine Learning to streamline the implementation of data products.
3. Measure value
Many organisations start by releasing a minimum viable data product when first implementing their data product strategy to demonstrate the value of data products within the organisation and bolster their adoption. Over time, the data product becomes normalised within the organisation, gaining more features and improving its value. Therefore, data product managers must know how to evaluate usage and value to show the benefits delivered by their data product.
An essential part of modern day businesses
The demand for data products is skyrocketing and rightfully so. They empower companies across industries to get the most out of their data. However, their successful integration into any data ecosystem requires a rethink of current data roles.
Data product managers are an essential part of a data team. Leaders who employ the right people with the right skills will be one step ahead in delivering high-quality data products to the business.