MLOps & Data Architecture

for

Freeda Media

Buildo assisted Freeda Media in revamping its data platform to analyze social media metrics from Instagram, Facebook, and TikTok, enhancing its analytics capabilities.

INDUSTRY
Scale-ups
SERVICES
Machine Learning
MLOps
TECHNOLOGIES
Python
Kubernetes
Valohai

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Buildo assisted Freeda Media in redeveloping its data platform, designed to analyze metrics from major social networks such as Instagram, Facebook, and TikTok.

Our involvement included conducting in-depth architectural analyses within a domain-driven design framework to support the redevelopment of the platform. These efforts enhanced Freeda's capacity to utilize data for impactful social media analytics.

Challenge

Navigating complex architectures

Navigating Complexity in Data Flow and Systems Integration

At the beginning of our partnership, Freeda Media encountered significant challenges in managing their data infrastructure, marked by complex data flows and interdependencies. The existing systems struggled to handle the scale and complexity required for effectively deploying machine learning models and evolving the data platform to align with business objectives. Moreover, the need to seamlessly integrate and diversely analyze multiple data sources further complicated their operations.

Ensuring Business Continuity During System Migration

A critical challenge in the project was migrating from an existing, less flexible system to a more robust and scalable platform while ensuring business continuity. The migration process required meticulous planning and execution to avoid any disruption to ongoing operations. Freeda Media needed a strategy that not only supported the transition without affecting their daily workflows but also ensured that all data was accurately transferred and fully functional in the new environment.

Handling Significant Volumes of Data

Another significant challenge was managing the large volumes of data necessary for analyzing social media trends. Regular polling of content is required to obtain updated metrics, necessitating a precise calibration of data collection tailored to the specific needs of each customer and use case.

Outcome

Scalable systems transformation

We redesigned Freeda Media's system architecture, balancing software module coupling with client needs using a design-driven approach. This new architecture not only integrated seamlessly but also enhanced the system's stability and scalability.

The result is a robust platform that aligns with Freeda's strategic objectives, enabling streamlined operations and facilitating future growth. This transformation has enhanced Freeda Media's ability to leverage data for more impactful social media analytics within the digital media landscape.

"Buildo’s expertise in MLOps has substantially improved our platform, enabling enhanced scalability and data quality."
Marco Cerri
Head of Data Analytics & Technology Innovation
Methodology

Collaborative system redesign

The project focused on a comprehensive redesign of an existing system. Our initial task involved a detailed analysis of the current architecture, aiming to migrate to a new solution with minimal disruption to business continuity and team operations.

We conducted a thorough architectural analysis using data flow diagrams and event storming. Event storming was instrumental in defining the functionalities, essential for outlining use cases and targeting key areas for improvement. Simultaneously, data flow diagrams provided a clear visualization of the backend architecture, identifying how data moves and is processed across systems.

These tools were essential for crafting a data architecture that not only meets theoretical design requirements but also functions effectively in practice. The process was underpinned by a domain-driven design approach, emphasizing the balancing of coupling within the software architecture to enhance system integration and operational efficiency.

MLOps platform selection and implementation

We evaluated various platforms, from established market leaders like SageMaker and Kubeflow to emerging startups like Valohai, choosing one that best matched Freeda's unique needs. This strategic selection was essential in proposing an MLOps solution that integrated seamlessly with Freeda’s existing operations.

Following the selection, our team started the implementation phase, involving extensive Python development within a Kubernetes environment. This phase was characterized by a sustainable team augmentation approach, where our developers worked as part of a cross-functional team alongside Freeda’s technical staff. This collaboration ensured that while maintaining autonomy and responsibility for results, the team remained fully integrated and aligned with Freeda’s goals. The joint efforts facilitated a smooth integration of the new systems, significantly enhancing Freeda Media’s data processing workflows and machine learning capabilities.

The new system architecture and MLOps integration have transformed Freeda Media’s operations, enhancing agility and scalability. This enables more rapid adaptation to market changes and improves data-driven decision-making capabilities. As a result, Freeda Media has significantly boosted its operational efficiency, securing a stronger competitive position in the digital media industry.

Conclusion

Strategic tech advancement

Buildo's support in redesigning the architectural and data flow frameworks for Freeda Media highlights the critical role of in-depth analysis in tailoring software solutions that effectively meet both the technical and strategic needs of clients. Our meticulous approach to system redesign, combined with a carefully executed selection and implementation of MLOps platforms, has equipped Freeda Media with a robust, scalable infrastructure optimized for advanced social media analytics.

This partnership underscores the critical impact of strategic technological advancements on enhancing Freeda Media's data analysis capabilities, solidifying their competitive position in the digital market.

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