Harnessing AI for Metric Management: Metric as a Service

A collaborative platform automating data metrics creation, MetricLoop.ai simplifies metric management with AI and config-driven processes.

Phani Kumar Yadavilli, the Founder and CTO of People Tech Ventures, has been at the forefront of driving growth and customer success through his pioneering work in data analytics. At the Data Engineering Summit 2024, held in Bengaluru, Phani captivated the audience with his insights on “Metric as a Service” (MaaS) and the revolutionary platform, metricloop.ai, which is designed to streamline the creation and management of data metrics. His talk, marked by humor and deep technical insights, was a highlight of the conference.

The Data Engineer’s Dilemma: Fear of Metric Outage (FOMO)

Phani began his talk with a light-hearted introduction, jokingly redefining the popular acronym FOMO (Fear of Missing Out) to “Fear of Metric Outage,” immediately resonating with the audience of data engineers. He underscored the common struggles faced by data engineers in handling metrics, from identifying bad data to ensuring data quality across complex pipelines.

Identifying and Solving Metric Failures

Phani engaged the audience with a participatory discussion on the importance of metrics, highlighting their role in identifying noise from signals and maintaining data quality. He emphasized the nightmare scenario for data engineers: dealing with failed metrics. By sharing real-world examples, he illustrated how metrics travel through pipelines and the challenges in identifying and rectifying failures.

He posed questions to the audience about their approaches to troubleshooting metric failures, which elicited various responses, including the use of historical data, business rules, and source reconciliation. These interactions set the stage for introducing the solution provided by metricloop.ai.

Introducing MetricLoop.ai: A Collaborative Platform

Phani then introduced MetricLoop.ai, a collaborative platform that automates the creation and management of data metrics. He explained how the platform uses AI to identify trends and automate metric creation, making it a config-driven process. This approach reduces the manual effort involved in building metrics from scratch, thus addressing one of the significant pain points for data engineers.

Metric as a Service (MaaS)

The core of Phani’s presentation focused on the concept of “Metric as a Service” (MaaS). He explained how metricloop.ai tracks each aspect of a metric from its creation to validation. By leveraging AI, the platform ensures that metrics are built accurately and efficiently, enabling seamless integration with APIs and other services.

Phani highlighted several key statistics to underline the platform’s impact: data engineers spend over 44% of their time on data preparation, and 69% of companies report inefficiencies in integrating data from multiple sources. Metricloop.ai aims to address these challenges by making metric creation and ETL processes config-driven, which enhances accuracy and reduces the time spent on manual data integration.

Key Features of MetricLoop.ai

Phani delved into the features of metricloop.ai, showcasing its capabilities through a live demonstration. The platform supports role-based access control, version control, and seamless collaboration among team members. It integrates with various data sources and tools, offering a centralized platform for building and managing metrics.

  1. Role-Based Access Control and Version Control: Ensuring secure and trackable metric development.
  2. Integration with Data Sources: Flexibility to connect with different data stacks.
  3. Automated ETL: A config-driven ETL process that boosts accuracy and reduces manual effort.
  4. Visualization and Reporting: Integration with visualization tools like PowerBI and Metabase for creating dashboards and real-time monitoring.
  5. Predictive Analytics and Intelligent Recommendations: Leveraging AI for predictive insights and actionable recommendations.

The Future of Metrics: Real-Time Monitoring and Predictive Analytics

Phani shared his vision for the future of data metrics, emphasizing the importance of real-time monitoring and predictive analytics. He discussed how metricloop.ai enables real-time insights and the ability to send automated alerts through various channels, including Slack and email. The platform’s AI capabilities provide intelligent recommendations, helping organizations optimize their metrics and reduce costs.

A Practical Demonstration

Phani concluded his talk with a practical demonstration of metricloop.ai. He showcased how a simple manifest file can define a metric, which the platform then converts into a directed acyclic graph (DAG) for execution. This automated process significantly simplifies metric creation, allowing data engineers to focus on analysis and insights rather than the mechanics of metric generation.


Phani Kumar Yadavilli’s presentation at the Data Engineering Summit 2024 was a compelling exploration of how Metricloop.ai is set to transform the landscape of data engineering. By addressing the common challenges faced by data engineers and providing innovative solutions through a collaborative platform, Phani highlighted the potential of MaaS in driving digital transformation. His insights and practical demonstrations left a lasting impression, promising a future where data-driven decisions are more accessible and efficient than ever before.

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