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Understanding Data Products



Digital products that involve data have become a ubiquitous presence in our daily lives, some of which we may not even be aware of. Some tools use data to improve user experience, others use it to prioritize the development of new features, as well as provide advice or recommendations. Then there are products that facilitate an end goal by means of data. Such products are what are known as data products.


Characteristics of data products


Data products are self-adapting and are widely applicable economic mechanisms that derive their value from data. They are also capable of generating more data which can potentially alter human behavior or make inferences and predictions.


In this way, data products can be used in different areas, contexts, and industries, provided that they are designed to achieve a specific result, whether it is for increasing data accessibility, enabling business insights, democratizing access to data, conserving resources, etc. Thus, data products can provide raw data, transformed data, algorithms, predictions, decision support, or other forms of output that involve extracting value from the available data.


“Data Product” vs. “Data as a Product”


There is a common misconception that “data as a product” and “data product” mean the same thing. In reality, they are distinct from one another though they bear a relationship. In fact, “data as a product” (DaaP) is actually a subset of the data product. DaaP is actually a data product that has data, raw or derived, as the final deliverable of the solution. Some examples of DaaP would be the construction of a data warehouse, the development of an API that has the purpose of taking data from one environment to another, or even the export and import of transformed data to some file system.


Features of a good data product


Considering the data it carries, it is critical that a data product provides the right set of features that enables it to effectively accomplish what it was designed to do. We have listed down some of the features that make for a good data product:


  • It is capable of making inferences and predictions about the business to help users make sound decisions

  • It evolves with the result itself and as the number of users and data available increases

  • It has robust tools that can identify performance issues, especially if it is handling large amounts of data

  • It has security protections in place from potential vulnerabilities and attacks

  • It is compliant with existing laws and regulations on security and privacy

  • It is designed to handle increased amounts of data over time

  • It offers good discovery and planning which are critical to the success of any data product as this involves not only the business but also the data that the business has to offer to build the desired solution.


Data products are indispensable especially when we talk about business, as they can be the differential to take companies to another level. As such, good data products can be drivers that can help dismantle organizational silos and be utilized for optimization across departments.


For this, it is important that the data product not only needs to do its functions well but also be able to effectively deal with sensitive information and follow the standards in place in order to generate a positive impact for the business.

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