Enhancing Business Intelligence with AI-Powered Data Integration on AWS

We have collaborated closely with our incredible client to understand their specific challenges and business objectives. Through a series of strategic consultations and detailed planning sessions, we designed a comprehensive, tailor-made solution intended to meet their unique business needs. By focusing on meticulous planning and flawless execution, we delivered a robust system that effectively manages and processes vast amounts of data while addressing the client’s challenges and significantly contributing to the company’s long-term business growth and success.

A one-of-a-kind business intelligence platform designed to identify companies poised for growth and expansion. Since 2015, the organization has been leveraging AI and big data to rank over 10 million companies based on their likelihood of expanding. With a wide array of data sets, the platform offers a unique selection of rapidly evolving, high-potential companies in the business intelligence domain. Whether you are an economic developer, a commercial real estate broker, or part of a large corporation, the company provides essential business insights for everyone.

Throughout its professional career in the business intelligence industry, the company has faced harsh challenges in managing and analyzing vast amounts of data to identify high-potential companies. Let us take a look at the most significant customer challenges that need to be resolved.
First, the platform had data integration issues. Hence, they required a solution to efficiently import, deduce, and match various vendor data sets. Second, the AI-based solution should also be equipped with data analyzing and scoring features to build graphs of companies and people, find linkages, and compute a G-Score to rank companies.

Last but not least, the company experienced a lack of scalability. In light of this challenge, ensuring the system can handle large-scale data processing and provide real-time insights vital to their business model is essential.
The platform needs to address these challenges to avoid providing inaccurate or outdated information to their clients, potentially leading to missed business opportunities and a loss of competitive edge in the market.

Since our client needs to manage and analyze large data sets, AWS is a perfect choice due to its outstanding scalability. Amazon S3, for instance, can handle unlimited amounts of data from various sources. Over and above that, AWS offers robust security
features and compliance certifications, ensuring that the company’s vulnerable data is secured.

It is also essential to mention that AWS seamlessly integrates with Databricks, providing a unified data processing and analysis opportunity with multiple benefits. For example, the Databricks platform, hosted on AWS, enables efficient analysis and workflow management, crucial for our client’s data-intensive operations.

As a leading cloud solutions provider specializing in big data analytics and AI-powered business intelligence, the Matoffo team possesses the skills and experience to satisfy the client’s request. With a proven track record of delivering scalable, efficient, and
innovative solutions across various industries, including business intelligence, our cloud development company is adept at leveraging AWS services to solve complex data challenges.

Moreover, our expert team provides professional support throughout the whole development process, from the first touch to the final deployment. Our exceptional commitment to client success is evident through hands-on support at each step of the
product implementation. Such a customer-focused approach ensures our client can get the most out of their new solution, leading to improved business outcomes and long-term success.

Matoffo implemented a comprehensive solution leveraging AWS and Databricks to address the client’s challenges.

We have started with AWS infrastructure. Thus, our Data Engineers utilized Amazon S3 to securely store and manage large datasets from various sources, including Crunchbase, Acton, DBUsa, LexisNexis, and Gazelle.

Next, it was time for Databricks integration. It was set up as the primary computation platform and workflow management environment, enabling efficient data processing and integration. At the same time, we utilized Databricks Notebooks for developing and testing data processing algorithms, while Databricks Jobs were configured to schedule
and manage data processing workflows.

Regarding AI-powered data analysis, Apache Spark was applied within Databricks to build graphs of companies and people, identify linkages, and compute the G-Score. We implemented advanced algorithms for data import and deduplication, ensuring data consistency across multiple sources. Finally, our team created AI-based solutions for matching and linking data across different datasets, creating comprehensive profiles of companies and individuals.

Throughout the implementation process, Matoffo provided extensive support services, including pre-migration consultation, hands-on assistance, and post-implementation support and training. The development team included 2 DevOps engineers. Overall, it took us about 2 months to deliver a ready-to-use AWS solution.

The Matoffo team managed to deliver value in the following aspects:

● Efficient Data Processing
Thanks to reduced data integration time, the platform can update company rankings daily instead of weekly.

● Enhanced Accuracy
The AI-driven G-Score increased the accuracy of identifying high-potential companies.

● Next-Generation Scalability
The AWS infrastructure allows our client to process 5x more data volume without any performance degradation.

● Cost Efficiency
By optimizing AWS resource usage, the company reduced their cloud infrastructure expenses.

● Higher Customer Satisfaction Rates
Our client reported an increase in customer retention due to the improved accuracy and timeliness of their insights.

“Matoffo’s solution has revolutionized our ability to identify and rank high-potential companies,” said Viktor Kotusenko, Vice President of Engineering of the company. “The integration with Databricks and AWS has provided us with the tools to handle vast
amounts of data efficiently, and the AI-driven insights have significantly improved our decision-making process. We are now better equipped to serve our customers with accurate and actionable intelligence.”