Journey to a scalable AWS Data Lake

About this webinar

Terabytes of data landing monthly in an on-premise Data Lake doesn’t scale very well, especially when considering the amount of intermediate results generated by different pipelines consuming the data. To accommodate the amount of data that is nowadays generated by vehicles, a Data Lake should double its size every year just to accommodate the data.

This is the reason why a large German automotive company decided together with Data Reply to migrate the existing Data Lake to AWS. The main challenge was how to tackle this migration while guaranteeing zero downtime for the existing use cases, as well as a smooth transition for users and stakeholders. Developing a set of reusable Data Services which support different formats for data input and output, as well as different type actions, allowed the team to deploy 80 different data pipelines, using the same piece of code and only modifying its behaviour by the use of configurations. Common actions supported by the data service are anonymization, data enrichment, data denormalization and flatting of complex structure.

Why attend

Not many customers decide to migrate from existing Big Data platforms to the Cloud environment, mainly due to the fact that the effort may outweigh the effort spent for building the already existing Big Data platform.

In this webinar, Data Reply experts will explain how a team of 4 managed to migrate an already “oiled” platform to a new environment in a short amount of time, having almost zero impact on the users. Data Reply will also discuss how the new platform allowed the customer to find new stakeholders and investors.

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