Ami Gal, CEO and Co-Founder
With terabytes and petabytes of data pouring into organizations today, managing them becomes a challenge when traditional system architectures and infrastructures are not up to the mark. Storing immense volumes of structured and semi-structured data, analyzing it, and obtaining real-time, actionable insights is an issue for enterprises in the financial sector. For years, the banks have been conservative regarding the usage and adoption of advanced technology. Now however, the ground is shaking for all the financial institutions as they are constantly flooded with enormous streams of data. “Banks are required to analyze longer ranges of data (years instead of months) than they used to in the past” says Ami Gal, CEO and Co-Founder, SQream Technologies. “There was a time when they would make do with the archives, but it is a different scenario now with the need to process every single entity,” he adds.
Based in Israel with offices in New York and San Francisco, SQream addresses these challenges by enabling analytics on rapidly scaling datasets to identify patterns and predict potential future outcomes. SQream employs the usage of patent-pending innovative technology that streamlines the performance of analytics through massive parallel computing produced by Graphic Processing Unit (GPU) based technology. Their solution, SQream DB is a columnar SQL database that makes use of aggressive compression procedures that actually deliver high performance in terms of speed. “When it comes to the banking landscape, SQream provides the ability to implement all kinds of applications such as risk management, behavior analysis, cyber security, fraud detection, predictive analytics and more,” explains Gal.
This led a leading Israeli credit card group, operating in the payment industry, approach SQream to improve their self-service BI center for their business clients alongside their data analysts. The client was using Teradata as its major data warehouse.
SQream provides the ability to implement all kinds of applications such as risk management, cyber security, fraud detection, predictive analytics and more on a larger scale and in a faster manner
The model that was employed involved 4 hours of pre-processing and staging performed on the Teradata database, followed by an Extract, Transform, and Load (ETL) migration process to their Microsoft SQL platform for Online Analytical Processing (OLAP) cube structuring.
This is where SQream stepped in and provided them an easy-to-implement, hassle-free SQL-based solution. Within a week, SQream seamlessly shifted the complete flow of Teradata to a shorter and more efficient process—Teradata ETL to SQream Reporting Services, replacing both their Microsoft SQL server and OLAP cube. This resulted in an impressive decrease in response times— from 4 hours to 10 minutes for the entire reporting process. The client was able to deliver business related analytics and other immediate query needs to their customers within minutes instead of hours; courtesy of the new, more agile and flexible data structure.
In addition to analytics and big data, Gal believes that cloud is one technology that has been creating a huge impact on the banking landscape and will continue to do so. When it comes to safe and flexible storage, the topic of cloud is unavoidable in businesses these days. “It is not just the cloud, technological trends like big data and the Internet of Things(IoT) all have to work in together in sync, and not as different silos,” emphasizes Gal.
Commenting on the company’s future, Gal says, “In the next three to four years, we are aiming to turn SQream into a public company.” SQream will be focusing on expanding its business in North America, while stretching its horizon and going global. “Down the line, SQream will be a much larger company, enabling big data and providing analytical solutions to clients,” he concludes.