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Data platform: Orchestration, catalog, and quality

In an era marked by growing velocity, volume, and variety in data, managing this constant influx of competing data points and information is crucial for businesses aiming to stay ahead. Data platforms help achieve this—but building and customizing them is key to success.

In our experience working with clients on analytics and ML platform modernization projects, we discovered that transforming data chaos into a streamlined asset often involves embarking on a comprehensive digital transformation journey. In one such scenario, we worked with a leading Fortune 500 entity to revitalize their data management strategies and harness the power of advanced customer intelligence.

This white paper takes a closer look at how we helped achieve that. 

Transforming data management with a robust data platform

Our experience with a Fortune 500 pioneer underscores the importance of data analytics as a critical enterprise asset. Going beyond mere enhancements to the digital customer experience, our work involved the refinement of data acquisition, architecture, and utilization.

Known to industry insiders as an exercise to turn the data swamp into a data lake, such undertakings typically revolve around boosting the effectiveness of data, accelerating innovation, and helping amplify the productivity of data engineering teams. 

Implementing a three-step approach for data excellence

Three key initiatives guided our strategy to overhaul the data architecture for the company:

  • Automating the data transformation pipelines: This involved streamlining data ingestion which, in turn, trimmed the operational burden for data preparation and integration. As a whole, the process helped facilitate more seamless data transfers and flows. 
  • Establishing a centralized data catalog: Building upstream from data ingestion and preparation, we created a foundational layer for data storage. Now, any new data fed to the system possesses a credible lineage and is traceable with metadata management that improves data discovery and governance. 
  • Elevating data quality: Deploy a cutting-edge data quality control framework across the workflow to detect anomalies and business-driven quality checks to ensure all recorded data is of the highest integrity. 

Results that speak volumes

The transformation yielded remarkable outcomes, setting a new benchmark in data management and utilization:

  • Reduction in the time to market for new AI/ML models from weeks to mere days, optimizing the decision-making process and enabling rapid adaptation to market changes.
  • Enhanced efficiency in model retraining and data problem troubleshooting, slashing downtime by 40% and fortifying data reliability.
  • Significantly improved team productivity by promoting the reuse of data sets and transformation jobs, thereby dismantling data silos and fostering a culture of collaboration and innovation.

Harnessing a next-generation data platform architecture

A sophisticated analytics platform and MLOps is crucial to driving business intelligence, enhancing customer experiences, and securing a competitive edge through informed business decisions. 

It offers a blueprint for deploying cloud, data science, and machine learning models to extract useful business insights and ensure that data assets can be put to real, practical business use.

With our innovative approach to data orchestration, cataloging, and quality, we can help your enterprise data platform become a cornerstone of digital transformation. 

Reach out to us today to begin the move.

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