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Managing Data as a Product



While data has always been critical in managing a business, it has sometimes taken a backseat to other IT priorities. In recent years, data has again become top-of-mind as individuals and businesses have come to rely on data to gain business insights and facilitate ever faster and smarter decision-making. Data has become more valuable than ever.


It is with such considerations in mind that there are those who are looking to make the most of their data investments and utilize its full potential that will benefit the business in the long run. Unfortunately, such targets are easier said than done.

As the Harvard Business Review points out, the main problem lies in the fact that data investments must deliver near-term value and lay the groundwork for rapidly developing future uses at the same time. As data technologies evolve in unpredictable ways, new types of data emerge, and the volume of data keeps rising and that entails additional costs to the business that may exceed the value they project to gain in the first place.


Given these challenges, how can one maximize the value of data? The answer: treat data as a consumer product.


Why consider data as a product


Firstly, it must be said that while some businesses tend to consider data a commodity that can be “purchased” by third parties, this is not what “ treating data as a product” is about. On the contrary, it is more about treating data as a vital commodity just like any product or service of the organization that is being presented to clients and customers.


Data being managed like a consumer product has its advantages, namely:


Everything provided in one – Data as a product delivers a high-quality, ready-to-use set of data that people across an organization can easily access and apply to different business challenges.


Enables standard types of consumption – As a product, data incorporates the connections necessary for different business systems, such as digital apps or reporting systems, to “consume” the data as these systems usually do.


Improved speed and efficiency – Data as a product searches for specific data more efficiently, processing it into the right format, and building bespoke data sets and data pipelines, saving businesses significant time and resources.


Reduction of risk and data governance burden – Data can benefit from the stringent quality controls and reviews a product goes through before it is released to the market. This lessens the risk of faulty or error-prone data that could not be fully utilized.


Building the foundation of the data product


Similar to how the product development process goes, managing data like a product requires the right operating model with the following attributes that must be present:


Dedicated management and funding – There should be a dedicated product manager and a team consisting of data engineers, data architects, data modelers, data platform engineers, and site reliability engineers who are funded to build and continually improve the data product from which new ideas and process can spring out of.


Standards and best practices – From the beginning, there should be an established set of standards and best practices for building data products in order to ensure efficiency in resources and greater productivity.


Quality assurance – Because problems can arise at any point in the data product development process and any issues discovered by the end users, no matter how grave or trivial they may be, can erode the trust and retention placed on the business, it is very crucial that quality control and assurance oversee every step in the process and remedy issues on the onset before reaching the end-users.


Companies that manage their data like a product have a significant market edge in the coming years, thanks to the increases in speed and flexibility and the new opportunities that approach can unlock. Thus, having the foundations in place will help ensure the company’s growth in the future.

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