Client Background

Our client, a leading E-commerce company, was facing challenges with managing and analyzing their rapidly growing data. Their existing infrastructure was struggling to handle the volume, variety, and velocity of data generated by their operations, marketing campaigns, and customer interactions. They sought a modern, scalable solution to centralize and optimize their data management processes

Industry

Ecommerce, Retail

Launch Timeline

6 Months

Country

India

Services Provided :
Tech Stack Finalisation
Data Lake Implementation
Devops & Cloud Infra Support
Engagement Overview :

The primary objective of this partnership was to design and develop a comprehensive Data Lake and Data Warehouse solution so that reporting and dashboarding can be performedthrough slicing/dicing of data for business reporting

Client Objectives

Scalability: Build a solution capable of handling large volumes of data and scaling seamlessly with business growth.

Data Centralization: Create a centralized repository for all types of data, including structured, semi-structured, and unstructured data.

Analytics and Insights: Enable advanced analytics and data-driven decision-making through efficient data processing and visualization.

Cost Efficiency: Optimize costs by leveraging cloud resources effectively and minimizing infrastructure overheads.

Data Security and Compliance: Ensure data security, privacy, and compliance with relevant regulations such as GDPR and CCPA

Solution Overview :

Dew Solutions partnered with the client to design and implement a comprehensive data management solution leveraging Amazon Web Services (AWS) cloud services. The solution consisted of two main components: a Data Lake and a Data Warehousing solution.

Data Lake

AWS S3: Used as the primary storage layer for the Data Lake, providing scalable, durable, and cost-effective storage for all types of data.

AWS Glue: Used for data cataloging, ETL (Extract, Transform, Load) processes, and schema evolution, enabling automated and efficient data processing.

AWS Lake Formation: Utilized for data governance, security, and access control, ensuring compliance with data regulations.

AWS Athena: Enabled ad-hoc querying of data stored in S3 using standard SQL, facilitating data exploration and analysis.

Data Warehousing

Amazon Redshift: Chosen for its scalability, performance, and cost-effectiveness, serving as the central data repository for structured data.

AWS Glue DataBrew: Used for data preparation and cleaning tasks, improving data quality and reliability for analytics.

Amazon Quicksight: Integrated for data visualization and business intelligence, providing interactive dashboards and reports for decision-makers.

Key Features and Benefits

Scalability and Performance

The AWS-based solution offered virtually unlimited scalability, allowing the client to handle large data volumes and concurrent users without performance degradation

Data Accessibility

The centralized Data Lake and Data Warehousing solution provided easy access to data for various stakeholders, enabling faster and more informed decision-making

Future Readiness

The solution was designed to be flexible and adaptable, allowing for future enhancements and integration with emerging technologies

Results

Improved Data Management

The client achieved a more streamlined and efficient data management process, reducing manual effort and errors

Enhanced Analytics Capabilities

The new solution enabled the client to perform advanced analytics and derive actionable insights from their data, leading to better business decisions

Cost Savings

By migrating to AWS and adopting a cloud-based data management approach, the client reduced infrastructure costs and achieved better cost predictability

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