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October 9, 2022|
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AWS Solution Overview
The below architecture diagram illustrates high-level infrastructure components of the customer’s production environment.
Data Engineering Pipeline for Text and Audio Data
This solution helped in building a data engineering pipeline for data in the form of JSON and audio data from the source.
The pipeline includes 4-5 different steps that were performed on the source data:
- Source text data coming from the customer application was first stored in a central data lake solution like S3
- An ETL operation is performed on it to clean the raw data
- A querying mechanism is set up to extract important data from the cleaned data.
- The audio data is transcribed into SRT format and translated to the desired language
- This formatted audio data is again stored in a central data store for more feature implementation.
AWS Services Leveraged
- Amazon API Gateway
- Amazon DynamoDB
- Amazon S3
- AWS Lambda
- Amazon Transcribe
- Amazon Translate
- AWS CloudFront
- AWS Glue Crawler, Data Catalog, and ETL-jobs
- AWS Athena
- Amazon Kinesis Data Streams
- Amazon Kinesis Firehose
Solution Outcome
- Data-driven Architecture helped in new feature releases for their application, with an increased number of customer registration and better customer experience.
- AWS Transcribe and Translate integration helped in attracting more customers from different language backgrounds.
WRITTEN BY Bhavesh Goswami
Bhavesh Goswami is the Founder & CEO of CloudThat Technologies. He is a leading expert in the Cloud Computing space with over a decade of experience. He was in the initial development team of Amazon Simple Storage Service (S3) at Amazon Web Services (AWS) in Seattle. and has been working in the Cloud Computing and Big Data fields for over 12 years now. He is a public speaker and has been the Keynote Speaker at the ‘International Conference on Computer Communication and Informatics’. He also has authored numerous research papers and patents in various fields.
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