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Scalable ETL pipelines with AWS Glue

aws glue

DATA-THE KEY DRIVER TO GROWTH

Nobody could deny the data driven aspect of business today and the impact the data has on the decision-making process. Thus, optimising the architecture for getting data driven insights should be a priority.

WHY AWS?

On premise data warehouses entails with them high upfront and maintenance cost with a lack of scalability. AWS (Amazon Web services) tends to eliminate that gap by provisioning cloud based or virtual architecture.

HOW GANIT CAN HELP YOU

Ganit can help you maximise your decision velocity and minimise the decision risk through our extensive experience in providing cutting edge solutions to our clients.

We have helped various clients to modernise their data warehousing and analytics architecture by migrating them to a more efficient, scalable, and cost-effective AWS based architecture. Our key focus is ensuring maximum efficiency at each step from data ingestion to deriving valuable insights from the data through analytics. AWS Glue has been first choice of ETL tool for many solutions, since it’s a fully managed and highly scalable serverless service and supports seamless integration with various analytical tools thus requiring minimal manual input and maximum results quickly. Besides AWS glue, all the cloud architecture along with all the necessary integrations are created as per the client’s requirements.

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THE GANIT IMPACT

At Ganit while we do strive to achieve operational and performance efficiency for our client, delivering tangible results to the clients through consistent effort remains our priority. We have helped a major retail chain company to cut costs by saving around 100,000+ man hours on a yearly basis, purely because of the simplistic and efficient Glue based architecture we created for them and are still continuously updating the same with evolving client requirements. The forementioned architecture not only provides them with new possible opportunities but provides them the flexibility to take risks by eliminating some of the uncertainty associated with the decision-making process.

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