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Data Practice
Overview

As organizations collect increasingly greater amounts of data on customers, products, transactions, markets and social media, the management and maintenance of that information becomes even more important – especially if benefits and insights are to be derived.

ESP advises on the collection, management, reporting and monetization of data for maximum effectiveness. This may include developing dashboards and automated solutions for MIS reporting and regulatory compliance, as well as architectures and implementation roadmaps.

Data Visualization

Transforming text-based data into a visual format can reveal patterns, trends and correlations which go undetected, making it possible for their significance to be realized. ESP examines and visualizes data to provide insights that grow client relationships, product offerings and revenues.

We leverage cloud-based technologies and data services, integrating seamlessly with most internal systems to deliver real-time analytics for improved decision making.

Data Transformation

We help clients transform and improve data by first understanding it, and then adapting it to meet their goals and objectives. Our data modeling and rationalization teams turn functional and technological needs into requirements that ensure accurate and timely reporting from well-structured databases.

This systematic and scientific approach enables us to deliver significant impact for our client’s organizations, bring mindful of necessary and proven governance controls.

Data Science & Engineering

Leveraging the power of predictive analytics, clients can draw near-real-time insight into data to solve complex challenges, predict demand for products, improve data utilization and guide business strategies based on knowledge and forecasting.

ESP helps clients gain authority over their data with actionable insights to drive machine learning, AI and robotics. We further assist with the design and implementation of frameworks and Big Data pipelines, Data Lakes, and Lineage Tooling for Data Engineering across an enterprise.