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A leading courier delivery services company with around 12 million shipments going every month required a responsive, highly available, scalable and secure data warehouse to store and analyze the data with high level of automation.

We made a visible and measurable impact to our client's business

50,000+ man hours saved per year

Challenge

Industry Overview

With the current architecture they faced high refresh time for dashboards, high degree of manual intervention associated especially with data ingestion and lack of resilience. The client wanted an efficient glue-based architecture design to overcome these limitations and ensure greater flexibility for integrating the stored data with various other analytical tools, incurring minimum costs.

Why were we brought in?

To help the logistic giant overcome this problem Ganit was successfully able to come up with a much more robust and sustainable model.

Our approach

Methodology

  • This framework proposed by Ganit is not only an improvement over the previous one but also act as an enabler for the logistic company to take bold initiatives without worrying about the underlying infrastructure limitation, accompanied by cost optimization, optimal security and connectivity to various tools and services.
  • Initial step was to replace BODS with SAP Adapter to help the client team manage their data sources with minimal overhead then data ingestion part was automated with data pipelines. For the data warehousing part automatic table optimization was implemented on Glue for the refresh time management, materialized views were replaced with tables to ensure incremental updates rather than having a full refresh followed by glue/lambda job to copy incremental data from Glue to s3.
  • To further increase the scalability and resilience of the model Glue WLM, concurrency Scaling and Elastic resizing is enabled. Data lake is used to run big data analytics and use machine learning to gain insights from semi-structured and unstructured datasets.
  • Enabling the Glue Spectrum allows for faster analytics as it eliminates the requirement to move the stored data from the storage service to a database since it can directly query data inside the s3 bucket.

A valuable difference

Impact

By automating and streamlining the analysis and report generation process Ganit was successfully able to deliver and create a significant impact on the client company. With an estimate of around 50,000+ man hours saved per year.

The decision-making process became much quicker and more convenient while also replacing complex integrations in the architecture with much simpler AWS services for a much better smooth workflow.

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