Case Study

Enhanced Data Accuracy by 20% Through Preprocessing and Cleaning with Duplicate Removal and Format Standardization

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Industry 

FinTech

Expertise 

Amazon S3, Amazon QuickSight, AWS IAM, Amazon CloudWatch, AWS Systems Manager

Offerings/solutions 

Preprocessed and organized data, streamlined integration, and created effective dashboards for insightful analysis.

About the Client

The client is an IT company specializing in FinTech, offers FinAlyzer, which revolutionizes CFO reporting with integrated group reporting, consolidation, and profitability insights for improved decision-making and financial performance.

Highlights

20%

Improvement in Data Accuracy

25%

Enhancement in Data Accessibility and Management

50%

Reduction in Manual Effort

The Challenge

The client is a leading FinTech IT company, struggles with monitoring and analyzing the performance of their FinAlyzer product deployed on Amazon EC2 instances. They lack the infrastructure needed for comprehensive monitoring of both the application and its underlying infrastructure, affecting their ability to capture critical performance parameters and gain real-time insights, thus impacting the reliability and performance of their deployments.

Solutions

• The initial setup of AWS IAM users was all provided by the client.
• The relevant data was provided by the client, which was then processed as per requirements.
• The processed data was stored in the Amazon S3 bucket in various folders for better partitions and understanding.
• There are 5 Glue Crawlers that are run on this bucket that create the raw tables in the database.
• The crawlers were set to run accordingly for the latest data and create the tables.
• Amazon Athena creates the dataset based on the tables created in the AWS Glue catalog for the main data partitions.
• The data is pulled into Amazon QuickSight from Amazon Athena tables for actionable and interactive dashboards.
• Interactive dashboards were generated as per the requirements.

The Results

Improved data accuracy by 20%, management by 25%, and reporting accuracy by 20% through advanced data processing and visualization.

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