Productization of data is the process of treating data as a product; more specifically, the process involves translating insights gained from exploratory analysis into scalable models that can power data products. As such, productizing data can help integrate data science across all enterprise products and normalize its applications by making it accessible to even non-technical business users as clients can plug into a hosted cloud to access sophisticated data. This will be particularly useful for Bhutan considering the apprehensive nature towards technology adoption. Data productization can also increase business value through the use of data products to boost sales, deliver personalized experiences and improve products.
One of the biggest advantages of productizing data science is the utilization of scarce data resources to carry out niche data science work, freeing companies from mundane or repetitive tasks.
The other advantage of productizing data science is scale. Institutionalization of data products can help organizations take advantage of scale. For example, market mix models that are built for general merchandising can be leveraged for online grocery shopping and across different geographies if turned into a product. Such institutionalization of products can enhance efficiency and reduce redundancy. Data science productization can generate cost savings for the organizations by reducing duplication of efforts and facilitating reuse by using machine learning models as well as production systems for diversified applications.
For Bhutan, data productization will be seen with the Integrated Data Platform project which will leverage data to gain insights that can be used for the creation of effective solutions and applications.