About

A large, American Fortune 200 multinational financial services corporation caters to customers across various industries. With millions of transactions processed daily, the company’s existing traditional data warehouse proved to be a challenge to keep up with the increasing demand for data processing, analytics, and reporting. To address this, the company decided to migrate its data warehouse to a modern Big Data architecture and partnered with Sakha for the same.

The Challenge

The existing data warehouse faced several problems, including:

• Limited scalability: The traditional data warehouse was not designed to handle the massive amounts of data generated by the company’s modern operations. As a result, the system often experienced bottlenecks and slowdowns, which impacted the company’s ability to access and analyze data in a timely manner.
• Lack of agility: The traditional data warehouse was inflexible and not easily adaptable to changing business needs. This made it difficult for the company to keep up with the pace of innovation and respond quickly to changing market conditions.
• High costs: The existing data warehouse was expensive to maintain, both in terms of hardware and software. The company needed a more cost-effective solution that could deliver the same level of performance and functionality.

Solution

To address these challenges, the client decided to migrate to a modern Big Data architecture. The new architecture, designed by Sakha, included the following features:

• Distributed storage: Sakha adopted a distributed storage system that allowed it to store and manage large volumes of data across multiple nodes. This provided the scalability and flexibility needed to handle the company’s growing data needs.
• Data processing framework: Sakha implemented a data processing framework that could handle large-scale data processing tasks, such as batch processing and stream processing. This enabled the company to process data in real-time and generate insights faster than before.
• Analytics tools: Sakha adopted advanced analytics tools that could handle complex data analysis tasks, such as machine learning and predictive analytics. This helped the company gain deeper insights into its data and make more informed business decisions.

The migration to a modern Big Data architecture provided several benefits to the company, including:

• Improved scalability: The new architecture was able to handle the company’s growing data needs, without experiencing bottlenecks or slowdowns. This allowed the client to access and analyze data in real-time, improving its ability to respond to changing market conditions.
• Increased agility: The new architecture was more flexible and adaptable than the traditional data warehouse, enabling the client to respond quickly to changing business needs and market conditions.
• Reduced costs: The new architecture was more cost-effective than the traditional data warehouse, both in terms of hardware and software. This allowed the client to allocate its resources more efficiently and focus on delivering value to its customers.

The migration from a traditional data warehouse to a modern Big Data architecture enabled Sakha’s client to improve its data processing, analytics, and reporting capabilities. The company was able to handle its growing data needs, respond quickly to changing business needs, and reduce costs. The new architecture provided the foundation for continued innovation and growth, enabling the client to stay competitive in a rapidly-changing market.