Shellkode Helps PreSkale Accelerate Decision Making Using AWS Services

Built on AWS, PreSkale is a pre-sales intelligence platform for monitoring daily sales operations and quantifying their impact on deal outcomes. To better serve its clients, PreSkale wanted to add a data visualization tool that would help users easily view the status, process, and results of their presales motions. They also wanted to modernize their data platform. The company partnered with Shellkode, an AWS Partner that offers tailored, high-quality AWS solutions, to refine PreSkale’s data pipeline and implement a dynamic reporting dashboard. By introducing Amazon QuickSight, Amazon Redshift, and Amazon Managed Workflows for Apache Airflow to its infrastructure, Preskale can build data dashboards 95 percent faster and enable clients to accelerate decision-making.

Preskale is a software-as-a-service (SaaS) solution that helps businesses maximize presales efficiency by pulling in data from various platforms, such as marketing, sales, and project management software. This allows clients to track everyday sales operations, review ongoing deals, quantify pre-sales work against deal outcomes, and identify critical product gaps and their revenue impact. As part of the company’s expansion on Amazon Web Services (AWS), PreSkale wanted to provide users with a visual representation of their data, which was primarily stored in their application database. This would give them a holistic view of revenue impact and make reporting easier. Additionally, PreSkale wanted to modernize its data platform. But the company wasn’t sure how to best achieve this with minimal disruption to its infrastructure.

“We knew what kind of data we wanted to collect, but we didn’t know how to represent it,” said Prashanth Ganesh, chief operating officer at PreSkale. The company brought in IT service provider Shellkode, an AWS Advanced Tier Partner that offers specialized consulting services to empower cloud and data-driven solutions on AWS.

Shellkode assessed PreSkale’s infrastructure and designed a scalable data architecture that leverages AWS services for data processing and analytics. To remedy inefficiencies in PreSkale’s data pipeline, Shellkode implemented Amazon Redshift, Amazon Managed Workflows for Apache Airflow, and Amazon QuickSight. This improved the speed, resilience, and security of PreSkale’s data pipeline and allowed the company to implement data-driven dashboards that offered more granular data at a glance.

In the new architecture, data is exported from Preskale's database to Amazon Simple Storage Service (Amazon S3) and then sent to Amazon Redshift, where it is transformed and aggregated according to business requirements. Amazon Managed Workflow for Apache Airflow orchestrates and automates the entire extract, transform, and load (ETL) process. The data then feeds into Amazon QuickSight to provide a flexible, intuitive, and easy-to-use dashboard with custom visualizations for PreSkale clients. This yields a self-serve and scalable ETL platform, improves data security and resiliency, and reduces dashboard management overhead. The data transfer can be done in a single click through the private network connection.

“PreSkale’s clients now have more control over how they want to visualize the data and we can render their data faster,” said Manasa Kallakuri, data practice lead at Shellkode.

Amazon QuickSight unifies business intelligence (BI) at hyperscale and enables PreSkale to build dynamic dashboards with a large selection of advanced filters, parameters, and visualizations. Users can meet varying analytic needs from the same source of truth through modern interactive dashboards, paginated reports, embedded analytics, and natural language queries. While PreSkale provides the same type of dashboard to its customers, each customer can access only their data from a single Amazon QuickSight dashboard using parameters and application authentication.

“Amazon QuickSight is a cloud-native, serverless, business intelligence service that is scalable and easy-to-manage, and includes a usage-based pricing model,” Manasa Kallakuri said. “And it came at a lower price point than other third-party options.”

With the former infrastructure, constructing a dashboard could take four days. Doing anything programmatically with the stack could take up to 14 days.

“With QuickSight in place, we can build any dashboard we want in less than five hours, which is approximately 95 percent less time,” said Ganesh.

PreSkale found that Amazon QuickSight offers the best visual representation of data, which includes Sankey graphs that clients find valuable. Additionally, it seamlessly integrates with Amazon Redshift.

With the new infrastructure that Shellkode and AWS enabled, PreSkale accelerated the decision-making process for clients thanks to faster data processing and time saved on ETL.

“Now, whenever a user views a dashboard, they see better data in a better format, and we can offload the reporting to Amazon Redshift,” said Ganesh. “And with Amazon QuickSight, clients have more control with features like filtering and designating time periods. We ingest massive amounts of data and run complex aggregation queries while deploying everything in a more secure environment.”

These improvements have led to an increase in customer sign-ups. “Shellkode and AWS have helped us take our business to the next level,” Ganesh said. “The data visualization provides a real wow factor for potential clients. It’s a prime factor in business growth.”

Looking ahead, PreSkale will work with Shellkode to integrate generative artificial intelligence (AI) and ML solutions using AWS, helping clients find product gaps faster. And as the company takes on bigger customers, it knows that the scalability of AWS can handle increasingly large volumes of data.