About the Customer
Any customer that needs to transfer files securely between two remote servers and perform data extraction and transformation can use the “SndLegal” project.
However, some potential customers for this project could include:
- Finance and banking institutions that need to transfer financial data securely between different systems or organizations.
- Healthcare institutions that need to transfer patient records, medical reports, and other sensitive information between different healthcare providers.
- Insurance companies that need to transfer policyholder data, claims, and other financial records between different systems or providers.
- Government agencies that need to transfer sensitive data, reports, and records between different departments or agencies.
- E-commerce companies that need to transfer product data, order records, and other transactional data between different systems or vendors.
Project Overview
This project is a type of ETL process, which allows you to transfer many files from one server to another. It will allow you to setup a connection from which you can send and receive files.
Files are in Excel, CSV, JSON, Zip and Text formats. Each file will be processed to extract data, perform the transformation, count records that is present in the files.
This project has 4 job types such as Clean Up, Direct Transfer, Direct Transfer with record count and Data Processing
- Clean Up: Delete all the files from specific folder of the selected SFTP server.
- Direct Transfer: Transfer files from one SFTP server to another.
- Direct Transfer with Data Processing: Transfer files from one SFTP server to another, validation of dat and perform the required data processing based on data mapping provided by client.
- Data Processing: Transfer files from one SFTP server to another and provide record count and validate as well as count of phone number, zip codes and letter codes as per give JSON format by client.
How is this project called an ETL process?
- Basically, ETL process means Extract, Transform and Load.
- Extract:
- It will Extract files from source server [one SFTP connection].
- Transform:
- Transform will execute the scripts that has been created for record counts and validation as per given JSON format by client.
- Load:
- Load will send extracted files to its destination server [another SFTP connection]
Purpose
The purpose of Data Bridge is to provide a platform for vendors to transfer files securely and efficiently from one server to another server, while also performing quality checks on the transferred data to ensure its accuracy.
Business Challenge
- Integrating with diverse vendors can be challenging, requiring close collaboration with each vendor to ensure successful file transfer and processing.
- Processing files and counting records can be complex due to different data formats and quality rules. The client can address this by defining rules carefully and creating reusable functions.
- The client must allocate enough resources to perform accurate and thorough quality checks on the data, including validating JSON data and checking email formats, which can be resource-intensive and time-consuming.
- The client may need to implement effective error handling and logging mechanisms to promptly identify and resolve errors and warnings that occur during quality checks and data processing.
- Generating accurate and easily readable reports with all necessary information and delivering them via email can be a complex task. The client should focus on creating a reliable and efficient reporting mechanism.
- The platform must be scalable to handle increasing vendors and files, and designed to handle high volumes of data that can be scaled up or down as needed.
Our Solution
- We will create a flexible platform that can accommodate various vendor setups and file formats, ensuring that the files are transferred and processed correctly.
- To overcome the challenge of processing data in different formats, we will define quality rules carefully and create reusable functions that can process the data correctly. We will also implement advanced data processing techniques such as data parsing and transformation, which can handle data in various formats.
- To ensure that the data quality is maintained, we will allocate sufficient resources for quality checks such as validating JSON data and checking email formats. We will also implement automated quality checks and error handling mechanisms to detect and resolve errors and warnings promptly.
- To provide reliable reporting, we will design a reporting mechanism that is accurate, easily readable, and contains all necessary information. We will also implement automated reporting that can generate short reports and send them to the client via email.
- To ensure scalability, we will design the platform to handle high volumes of data and have the capability to scale up or down as needed. We will leverage cloud-based services such as AWS Batch Jobs, AWS Secret Manager, and AWS ECR to ensure that the platform can handle high volumes of data and scale up or down based on the load.
- Overall, our solution will provide a flexible, scalable, and reliable platform that can transfer files from one server to another while performing quality checks and maintaining data quality.
Key Challenges
- Processing files and getting a count of each record can be complex due to different formats and quality rules.
- Quality checks on the data, such as validating JSON data or checking email formats, can be resource-intensive and time-consuming.
- Ensuring the platform is scalable enough to handle increased load as the number of vendors and files increases.
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Project Name
Data Bridge
Category
Python Development
Technology Stack
- Python
- Django
- SFTP
- Docker
- AWS Batch
- AWS CloudWatch
- AWS Secrets Manager
- AWS Event Bridge
- AWS Elastic Container Registry
- HTML and CSS
- JSON (JavaScript Object Notation)
Industry
FinTech, HealthTech, GovTech, InsurTech, E-commerce
