Data and AI Supermarket Architecture
Last year we published a paper where we introduced the Data and AI Supermarket Architecture
Using this approach you can boost your Data and Artificial Intelligence Strategy.
Text extracted from our paper:
Our purpose in this new framework is to add the Data Supermarket, a place to commercialize the data products generated by the insight generation process to other consumers exchanging them for a monetary value [33]. A typical insight generation process is developed by a multidisciplinary data scientist team, where raw data is converted into insights and data products. Our proposed contribution is to define the Data Supermarket as a key element in the Big Data monetisation strategy where data products created by this Big Data Scientist team, will be shipped as data products in a form of services or products to internal or external consumers. Smart Steps from Telefonica is a successful example of building data products and providing them to external companies. Smart Steps is an insight solution that uses anonymized and aggregated mobile network data to provide useful insights [33]. Therefore, the principal goal of the Data Supermarket is to generate new revenue to the company and enable the organization to increase penetration in new markets, not explored before. Organizing the data into one single repository and creating a data product catalog is also a benefit for the end business users. Data will be democratized to the business users with a proper data definition [34].
In Fig. 6 the lifecycle to build data products and sell in the Data Supermarket is showed. As mentioned, the Data Supermarket concept is based on a normal supermarket. In daily life people can buy multiple products in a single place, they are all available in the supermarket. The same concept can be transposed to data. Using this same idea, it is proposed that data will come from different data suppliers (source systems), ingested/moved to the Raw Zone (landing zone) where the raw data is organized in a catalog (raw area). The next step is to transform the raw data into different data products according to the internal and external business user’s needs. Like the experience of going to a food supermarket, where all the products are gathered and arranged in an organized manner.
The benefit of a data supermarket is the synergy of having best practices applied to activities like data collection, data transformation, data storage and data consumption. All the complexity of dealing with data is hidden from the end business user and presented in the Data Supermarket in a better user experience. The presentation or Data Supermarket store will handle the important tasks of data access, data security and data commercialization (free or paid) for internal or external users. The data supermarket store is the broker responsible for selling data products and for allowing market-oriented companies to profit from the data products available in the company data asset. The future data supermarket/data marketplace could become an important key asset of the modern MO organization.
This paper was also presented at ICAAI (International Conference on Automation and Artificial Intelligence) in London, UK on May, 21, 2020.
How to cite us:
Moreno, C., González, R. A. C., & Viedma, E. H. (2019). Data and artificial intelligence strategy: A conceptual enterprise big data cloud architecture to enable market-oriented organisations. IJIMAI, 5(6), 7–14.
Paper link:
https://doi.org/10.9781/ijimai.2019.06.003
