Firebolt Case Studies Revolutionizing In-App Analytics Experience with IoT: A Case Study

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	Revolutionizing In-App Analytics Experience with IoT: A Case Study Firebolt

Revolutionizing In-App Analytics Experience with IoT: A Case Study

Firebolt

Technology Category	Platform as a Service (PaaS) - Application Development Platforms
Applicable Functions	Sales & Marketing
Challenge	The client, a market research tech company, provides interactive analytics to marketing teams, enabling them to research their competitors’ brand and marketing activities as well as their own. The platform relies on massive volumes of web-traffic data and other sources, which are continuously streamed into S3 and used for various use cases and features within the customer-facing analytics platform. A key component of delivering a great user experience for their customers is ensuring that users don’t have to wait long to get results for their questions. However, waiting more than a couple of seconds was considered unacceptable. This led the company to make several painful tradeoffs. They had to limit their analysis to a month of data (~10TB), instead of a quarter (~40TB), due to the decrease in performance when trying to analyze a larger data set. They also had to aggregate data for full-year analysis features to maintain performance, while sacrificing the ability to drill into the granular data. Furthermore, they had to limit the types of data that could be analyzed, as many semi-structured sources could not be analyzed quickly enough compared to structured data. Read More
About Customer	The customer is a market research tech company that provides interactive analytics to marketing teams. Their platform allows users to research their competitors’ brand and marketing activities as well as their own. The platform relies on large volumes of web-traffic data and other sources, which are continuously streamed into S3 and used for various use cases and features within the customer-facing analytics platform. The company is committed to delivering a great user experience and ensuring that users don’t have to wait long to get results for their questions. However, they were facing challenges in terms of data analysis and user experience, which led them to seek a solution with Firebolt. Read More
Solution	Firebolt was able to quickly fill the gaps with the data already stored in S3. After a swift integration through the AWS Marketplace, the company selected the right combination of EC2 clusters and mapped them to the various use cases. Since Firebolt does not charge any markup on AWS resource costs, the company was able to utilize more resources to overcome their challenges and painful tradeoffs. Firebolt was easily placed between the data stream and the customer-facing application, replacing multiple data technologies with one centralized, efficient, and elastic engine that could handle all the analytics workloads. This solution allowed the company to overcome the limitations they were facing in terms of data analysis and user experience. They were able to analyze larger data sets, delve into granular data, and analyze semi-structured sources quickly and efficiently. Read More Log in to view content
Contents

Technology Category

Platform as a Service (PaaS) - Application Development Platforms

Applicable Functions

Sales & Marketing

Challenge

The client, a market research tech company, provides interactive analytics to marketing teams, enabling them to research their competitors’ brand and marketing activities as well as their own. The platform relies on massive volumes of web-traffic data and other sources, which are continuously streamed into S3 and used for various use cases and features within the customer-facing analytics platform. A key component of delivering a great user experience for their customers is ensuring that users don’t have to wait long to get results for their questions. However, waiting more than a couple of seconds was considered unacceptable. This led the company to make several painful tradeoffs. They had to limit their analysis to a month of data (~10TB), instead of a quarter (~40TB), due to the decrease in performance when trying to analyze a larger data set. They also had to aggregate data for full-year analysis features to maintain performance, while sacrificing the ability to drill into the granular data. Furthermore, they had to limit the types of data that could be analyzed, as many semi-structured sources could not be analyzed quickly enough compared to structured data.

About Customer

The customer is a market research tech company that provides interactive analytics to marketing teams. Their platform allows users to research their competitors’ brand and marketing activities as well as their own. The platform relies on large volumes of web-traffic data and other sources, which are continuously streamed into S3 and used for various use cases and features within the customer-facing analytics platform. The company is committed to delivering a great user experience and ensuring that users don’t have to wait long to get results for their questions. However, they were facing challenges in terms of data analysis and user experience, which led them to seek a solution with Firebolt.

Solution

Firebolt was able to quickly fill the gaps with the data already stored in S3. After a swift integration through the AWS Marketplace, the company selected the right combination of EC2 clusters and mapped them to the various use cases. Since Firebolt does not charge any markup on AWS resource costs, the company was able to utilize more resources to overcome their challenges and painful tradeoffs. Firebolt was easily placed between the data stream and the customer-facing application, replacing multiple data technologies with one centralized, efficient, and elastic engine that could handle all the analytics workloads. This solution allowed the company to overcome the limitations they were facing in terms of data analysis and user experience. They were able to analyze larger data sets, delve into granular data, and analyze semi-structured sources quickly and efficiently.

Impact #1	The operational results of the solution were significant. By integrating Firebolt, the company was able to overcome the limitations they were facing in terms of data analysis and user experience. They were able to analyze larger data sets, delve into granular data, and analyze semi-structured sources quickly and efficiently. This not only improved the user experience but also allowed the company to provide more comprehensive and detailed analytics to their customers. By replacing multiple data technologies with one centralized, efficient, and elastic engine, the company was also able to streamline their operations and improve efficiency. The solution also allowed the company to utilize more resources without any additional costs, further enhancing their operational efficiency and effectiveness.

Impact #1

The operational results of the solution were significant. By integrating Firebolt, the company was able to overcome the limitations they were facing in terms of data analysis and user experience. They were able to analyze larger data sets, delve into granular data, and analyze semi-structured sources quickly and efficiently. This not only improved the user experience but also allowed the company to provide more comprehensive and detailed analytics to their customers. By replacing multiple data technologies with one centralized, efficient, and elastic engine, the company was also able to streamline their operations and improve efficiency. The solution also allowed the company to utilize more resources without any additional costs, further enhancing their operational efficiency and effectiveness.

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Overview

Revolutionizing In-App Analytics Experience with IoT: A Case Study

Operational Impact