If Data is the new Oil, Data View House is the crude oil refinery.

Krupesh Desai
Data View House
Published in
3 min readAug 24, 2023

The Data View House phrase struck me in 2017 when I managed multiple data quality dashboards and related ETL. As a naive entrepreneur, I quickly bought a domain and trademark. I sought to package my tricks and tips as a framework that helped me manage numerous data pipelines, target tables/visuals, and their catalogue. The idea was to formulate a service with deliverables for an organisation to start the data view house journey.

In this service bundle, I envisioned about the possibility of a “Data” department in the business hierarchy due to the actively changing data storage and process offerings with the emergence of Big Data technologies. I was convinced that a business that could convert its business data to intelligence faster would do better than its competition in the future — the race of “Datum to Intelligence.

Virtually everything in business today is an undifferentiated commodity, except how a company manages its information. How you manage information determines whether you win or lose.” — Bill Gates

The Race of “Datum to Intelligence”

Later, I kept exploring the data governance domain and developing the idea as a product and a framework. Between 2018 and 2019, the rapidly growing cloud ecosystem started offering products and services I could stack to achieve the end-to-end business data management framework I envisioned initially without building a product as such. Over time, with research, I realised the meaning of being data-driven and the real challenges in front of any large organisation to become data-driven. The solution I could envision was a dedicated Data department solely responsible for managing the organisation’s data as an asset and providing maximum value back to the business backed by a robust data strategy using the Data View House Framework. To get started, I bundled a discovery starter package as “Test the Big Data Waters” to onboard clients on the Data View House journey.

Data View House school of thoughts.

2019 to 2022 was an interesting period where I lost focus on Data View House due to unexpected professional and personal circumstances. However, I was still employed in the data space in these three years as a data analyst, senior business intelligence consultant and data architect, where I was re-witnessing similar patterns of roadblocks to data-driven culture in front of prominent organisations. I realised that nothing much has changed regarding what it means to be data-driven and the factors preventing it. Below are the characteristics of the data-driven culture as I understood it back then, followed by the challenges that prevent the data-driven culture. After this, I will endeavour to elaborate more on the following images in the next blog.

Data Driven Culture — Characteristics
Factors preventing the data-driven culture

Next :

People, Process and Technology are three components of any product, project or service delivery. What fascinates me today is how rapidly the technology has evolved with various cloud offerings for data engineering and ML. However, challenges with people and processes are the same as before, preventing the data-driven culture. On the brighter side, The recent introduction of data-contracts and data-mesh has sparked an interest in me again to carry on the quest of data view house, complete the framework and produce regular content along the way.

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Krupesh Desai
Data View House

Certified Data Management Professional. Solving data-intensive problems and creating Value. Sharing the Data View House™ school of thoughts.