Overview

MavX stands at the forefront of the digital content creation industry with a mission to empower creators through monetization. Their innovative approach facilitates collaboration between brands and influencers, creating a mutually beneficial ecosystem. This synergy not only assists in product discovery but also fosters trust among audiences, encouraging them to make informed purchasing decisions.

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Challenge

MavX realized that to achieve their mission effectively, they needed to take a data-centric approach. They faced the challenge of tracking video engagements and sales, mapping these metrics to viewer behaviour, and measuring the impact of coupon code usage. The scope of the project was crystal clear MavX required a scalable system that could extract data from diverse APIs and sources on set schedules, transform this data using scripts, and provide a unified view of sales generated through video views.

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Our Solution

1. Comprehensive Data Extraction System: We developed  python scripts to effectively extract data from various APIs, organizing this process according to a precise schedule. This system was designed using Dasgter, accommodating the vast amount of data generated by MavX's operations.
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2. Integration of Big Query and Looker: Our engineering team strategically selected a data stack consisting of Big Query, Dagster, and Looker. Dagster was instrumental in automating and monitoring data pipelines on a large scale. Big Query served as the backbone for structured data storage, while Looker provided the tools necessary for effective data visualization tailored to business needs.
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3. Advanced Data Modeling and Analytics: Building on the raw data extracted, we created sophisticated data models and queries within Big Query. This approach enabled our analysts to quickly derive insightful and actionable information from the data.
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The Outcome

The implementation of our solution resulted in significant improvements:

1. Efficiency in Invoicing: The time required to invoice customers was significantly reduced from about 4 hours per customer to just around 10 minutes.
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2. Enhanced Productivity of Analysts: They observed a dramatic decrease in the time analysts spent on repetitive data cleanup and excel formatting, from over 80% to less than 10%. This shift allowed them to dedicate more time to generating insights, which is crucial in the growth stage.

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Conclusion

This project marked a significant milestone in the evolution of MavX, enabling them to leverage advanced data analytics for improved operational efficiency and decision-making. The transformation streamlined processes and provided MavX with the agility and insights needed to stay competitive in the dynamic world of digital content creation.

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