Want To Be Data-Driven? Treat Data as a Product




Wissen Team


July 7, 2023

Every organization today wants to become data-driven. Yet, most have their data stored in siloed systems, with just a handful of business analysts and data scientists accessing and processing this data for business decision-making. Such an approach to data, unfortunately, won’t take them far.

As new tools emerge and as data sets get increasingly complex, organizations need to have a clearer understanding of data’s full potential, for which they need to adopt a new paradigm - treating data as a product.

Why Data Needs to Be Treated as a Product

Ever since data became the new fuel, organizations have been employing different types of approaches to data. But most of these predominant methodologies have been largely unsuccessful. Whether individual teams piece together the data and technologies they need or centralized teams extract, cleanse, and aggregate data – the challenges plaguing data managers are many, even if not the same.

Bespoke technology architectures are costly to build, manage, and maintain and often do not align with specific business use cases – therefore failing miserably to support end-user needs. These ad-hoc approaches to data processing and management also lack the necessary level of governance and quality, causing several compliance challenges while restricting businesses from deriving sustainable value from data.

In today’s data-obsessed era, treating data as you would treat your consumer products can help you realize true value from your investments.

Approaching data as a product means you:

  • Have all the data you need on one entity, and different teams can easily access a single product and use it to solve different business problems - instead of using different tools and different methodologies that aren’t in sync.
  • Rely on a standard framework for different apps and systems across your business to consume data – regardless of how different teams and departments want to store, process, and manage data.
  • Save time collecting data from different sources, converting it into the right format, and creating bespoke data sets and pipelines – thus minimizing the chances of creating an architectural mess.
  • Make accurate and timely decisions across different use cases without worrying about security or governance.
  • Cut down on the total cost of ownership via reduced expenditure on development and maintenance costs.

How You Can Treat Data as a Product

Today’s data teams are tasked with delivering high-quality data insights to different departments at scale. But this is easier said than done. Apart from the many technical obstacles, numerous human-related challenges must be dealt with.

Treating data as a product eliminates many of the problems teams face in searching for data, processing it, and then using the insights to guide business decisions. However, shifting to this new paradigm requires many boxes to be ticked. Let’s look at the different things you need to get started with data products:

  • Get executive support: Just like a software development project would require dedicated management and funding, your data products also need support from your leaders and executives. Such support also ensures that your strategies are robust and that the tools, skills, and insights you use align with your broader business goals.
  • Build a skilled team of data professionals: In addition to executive funding, successful data products need to have a focused product manager and a skilled team consisting of data engineers, architects, and modelers, as well as subject-matter experts, legal experts, and operational staff who can provide much-needed oversight into continually improving the product and enabling new use cases.
  • Establish the right standards and best practices: Treating data as a product is new to everyone. Therefore, to tread on the right part, it is critical you establish the right standards and best practices. Crafting a data center of excellence can help in defining the rules across data collection and analysis, as well as in ensuring quality and governance via frequent audits.
  • Track and monitor metrics: Ensuring your data products meet end-user needs requires you to constantly track and monitor metrics. Such continuous efforts can go a long way in improving the quality and accuracy of your data products while ensuring you achieve the highest return on investments across different use cases.
  • Educate users: Regardless of the efforts you put into transitioning to this new approach, unless your users are made aware of it, you won’t achieve the intended results. Therefore, as you embark on this journey, you need to educate the users about the need to treat data as a product and the benefits of using a standardized approach to data-driven decision-making.

Build a Successful Data Culture

It’s an exciting time to be working with data. Given how crucial data has become to the basic functioning of any business, the opportunities for data teams to make an impact are many. With more tools at their disposal and exciting technology hitting the market each day, there are a lot of ways they can drive value.

But building and managing a robust data capability is an enormous challenge. If you want to uncover maximum benefits from growing volumes of data and transform into a data-driven organization, you can no longer depend on ad-hoc approaches and siloed tools.

Instead, you need to start treating data as a product and build a successful data culture that is backed by the management, supported by standards, and sustained by continuous monitoring. Let us help you navigate this unchartered landscape of technology and data management and help you build robust and scalable data products. Connect with us today to learn more.