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Case Study

Government Data Hub

We have a proven track record of assisting numerous companies in preparing their data infrastructure and pipelines for the Big Data World. Our expertise lies in delivering scalable, robust, and flexible data infrastructures that effectively transform our customers' analytics strategy into reality.

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The Government Data Hub project aimed to create a scalable Data Lake Infrastructure that revolutionizes the way data is collected, ingested, and harnessed from a multitude of sources. From ingesting standard tables to seamlessly incorporating internal and external data into the organization, our hub project leveraged and propelled analytics at our client. Supported by Airflow components on a Cloud Platform, this dynamic Data Lake Layer enabled the organization to embrace the potential of unstructured and contextual data, elevating the decision-making process to unprecedented heights. With a colossal 1 TB of accessible data, our project empowered the government institution organizations to utilize AI-driven use cases like never before, propelling them into a data-powered future.


As soon as you embed contextual data into your organization, you add a new layer of complexity to your data pipelines. Incorporating Continuous Integration and Delivery into your data pipelines is a must to ensure that you can keep your data hub healthy, consistent and useful.


Integrating sources from unstructured data introduces an additional layer of complexity to your data pipeline infrastructure. It's understandable that customers might be apprehensive when they initially consider the challenges associated with managing, processing, and gleaning insights from such diverse and often voluminous data sources. The concerns typically revolve around issues like data quality, security, compliance, and the need for new skills or specialized expertise.


We start by setting up a Data Lake that can receive ingested data from internal data sources. Later, we add scraping and API processes the information for analysis and decision-making. hat enables the scalability of external data sources. As the Data Lake continues to grow and accumulate vasts amounts of data from both internal and external sources, we recognize the need for effective data governance and management. To ensure data quality, security, and compliance, we implement robust data governance policies and establish a data catalog that provides metadata information about the stored data.

Scale your Analytics

Having a centralized Data Hub enables your organization to unlock the full potential of its data assets and foster a data-driven culture that drives innovation, efficiency, and competitive advantage.

Time Line



Setting Up Infrastructure on Cloud



Building Dags and Integrating Data



Building DataMarts and APIs



Scalling First Analytics Use Cases


Key Insights

The implementation of Airflow with Azure in the Government Data Hub Project allowed seamless integration of internal and external data sources. By centralizing data in a data lake, our customer gained access to a unified platform for data sharing and collaboration.

Scalability and Adaptability for Cloud Deployment: With the use of Airflow and Azure, the Government Data Hub Project achieved its first cloud deployment at our customer that used an on-prem infrastructure. This cloud-based infrastructure offered the flexibility to scale resources up or down based on changing data requirements.

People, Processes and Technology must work together to harness analytics and a data-driven mindset at the organization.