Xcelyst Partners

Success Stories

Xcelyst Partners driving tangible business impact

“The real treasure of AI is not the UI or the model – they have become commodities. The true value lies in data and metadata, the oxygen fueling AI’s potential” : Marc Benioff

Quality and accessibility of data are fundamental to the success of BI and AI initiatives. AI models rely on vast amounts of accurate, structured, and well-governed data to make predictions, uncover insights, and drive business decisions. Without the right data infrastructure and processes in place, AI efforts can quickly become ineffective, slow, or biased.

Traditional data architectures leveraging cloud data warehouses and Hive experience significant challenges including frequent file locking issues during writes, inefficiencies arising from data duplication, and complications in managing multiple data file formats across various processes.

Transitioning from a traditional data warehouse to a modern lakehouse is a strategic move, enabling companies to leverage the best of both worlds: the reliability of a data warehouse and the flexibility of a data lake.

Our solutions and expertise spans industries:

Financial Services

Retail & Ecommerce

Consumer Packaged Goods

Travel & Hospitality

Media & Entertainment

Automotive

Manufacturing & Industrial

Energy & Utilities

Healthcare & Life Sciences

Success Stories

1. Implementing a Delta Lake Platform for a leading Fashion E-retailer

One of India’s foremost fashion e-commerce platforms, recognized for delivering a vast selection of products and a superior online shopping experience was looking at modernizing their legacy Data Platform.

Prior data architecture leveraging cloud data warehouse and Hive experienced significant challenges, including frequent file locking issues during writes, inefficiencies arising from data duplication, and complications in managing multiple data file formats across various processes.

Xcelyst collaborated with the business to design and implement a new data platform leveraging Delta Lake with key goals of platform scalability, time to market improvements, and cost reduction.

  • Integration of Delta Lake addressed prior challenges, provided support for ACID transactions and enhanced data governance. This unified approach also streamlined processing across batch and real-time workflows, simplifying data management.
  • Implementation of Medallion architecture allowed for organized data structuring into bronze, silver, and gold layers. This categorization ensured raw data was consistently managed while facilitating efficient processing and enriching analytics

Results:

  • Performance Improvements: Shift to Delta Lake resulted in significant performance gains, enhancing real-time pipeline efficiency by 25%. Improved processing speeds and reduced latencies contributed to faster personalized recommendations.
  • Cost Savings: Infrastructure costs dropped by approximately 35% as the new architecture minimized the need for extensive legacy clusters. Enhanced batch processing efficiency also played a crucial role in reducing overall job execution times and expenses.
  • Enhanced Data Governance: Standardization on Delta format simplified data governance, fostering uniformity across the data ecosystem. This development led to improved collaboration between data teams and more reliable decision-making processes.

2. Data Warehouse Modernization for Enhanced Vehicle Genealogy Insights

A pioneer in the electric vehicle (EV) market and clean energy solutions was preparing for the launch of the new model and needed a cloud-based data warehouse solution to store and process vehicle genealogy data. Their existing internal teams struggled with data aggregation and required faster, more flexible data insights.  This was critical to ensure quality assurance, traceability, efficiant supply chain management and regulatory compliance.

Xcelyst helped the business by developing a data warehouse solution capable of aggregating and analyzing data in near real-time. This reduced business dependency on internal IT teams and improved the speed of data insights.  Used Azure’s data services to modernize data platform, including Azure Data Factory for ETL, Azure SQL DW for scalable data storage, and Power BI for reporting. The system allowed for real-time data gathering, significantly enhancing analytics capabilities

Results:  The implemented solution allowed for seamless data migration, ensuring efficient processing and real-time insights, ultimately overcoming the challenges faced by the company:

  • Enabled real-time data processing for genealogy of vehicles
  • Reduced SLA from 10 minutes to under 5 seconds for hot data
  • Leveraged Azure for handling 4TB of data for real-time insights