Creating a data-driven organization, one that can see insights buried deep where competitors cannot, requires more than just access to data. It requires organizations to have a strategy, plan, and roadmap of how they plan to capture, organize, curate, and finally analyze their data to create actionable insights for the business to become more competitive, efficient, and responsive.
We improve their business through data management and analytics, working with individual departments and across the enterprise, to employ solutions that use data that businesses are already collecting and generating from their operations. By working closely with stakeholders to understand their needs, we define strategies, roadmaps, implement technology, and guide our clients to make a data-driven organization possible.
Maximize return on data assets by defining the future state of the analytical program and conducting maturity assessment using 'Information Analytics Maturity Assessment Wheel©.'
Address the ever-changing world of digital marketing by leveraging data to develop a strategy using our 'Marketing Analytics Maturity Assessment Wheel©.'
Adopt our best practices to build self-serving data architecture, data models, and data pipelines for big data platforms like GCP, AWS, Azure, and Snowflake.
Create rich visualizations using enterprise dashboarding and reporting software, and build a storyline with custom open-source components like D3 or Chart.
Drive engagement with targeted campaigns in Adobe, Marketo, Salesforce, Unica, etc. by using machine learning-based segmentation and integrating with the marketing platforms.
Define the roadmap and cost of ownership for analytics program capabilities and the associated implementation plan, technology stack, garnering executive, and stakeholder sponsorship.
Build uber reports and executive dashboards from transactional systems or streaming data that are not bound by a single underlying reporting tool stack.
Predict issues in the processes and applications before they operationally manifest using machine learning and advanced analytics capabilities.
Nitrate™ leverages Artificial Intelligence (AI) and Machine Learning (ML) to understand the correlation and causality of operational incidents. It provides a holistic view of applications, analyzes the system’s health, detects anomalies, and constantly learns to keep the applications performance-optimized. Nitrate™ also has a built-in ML-driven ChatOps framework that helps teams in reducing dependencies on manual ‘search and react’ aspects of production operations.LEARN MORE
Migration of data to the seed data lake is a huge task, requiring a lot of development cycles to build the pipelines, and put auditing and error checking in place. CARBON automates the source metadata identification, builds the pipeline, including the deployment dags, based on the source (file, database, service, or stream) with error checking and audit functionality.LEARN MORE
Automating ETL testing and data validation has been a gap in the industry. BEAT™ has a unique way of solving this problem by building a solution that tackles this from the data consumers perspective. BEAT™ also moves data integration work to a BDD methodology for ETL stories.
Taken from delivering large data management and analytics solutions within retail, high technology, manufacturing, and financial services, our Data Management and Analytics practice has developed capabilities around technologies and practices to support departmental and enterprise initiatives.
Build high-fidelity, governed, trusted streaming, real-time batch, and data pipelines with ETL routines for data platforms and programs.
Build party, product, and location masters using enterprise MDM tools or custom purpose-built solutions to project 360-degree views to generate deeper insights.
Use marketing analytics services (SEO, Campaign Management, Tagging, Social and Web Analytics, Segmentation) and predictive models to understand customer behavior.
Implement machine learning to discover data stories, predict actions required to influence change, and develop data engineering to deploy ML models.
Leverage big data to optimize industrial equipment, instruments, and engineering processes to ensure sustained performance and implement cyber-physical systems.
Implement big data and advanced analytical-based solutions to identify potential failure points in technology operations using custom engineering based on Nitrate™.
Build high-impact dashboards using industry tools and open-source libraries for storytelling and develop enterprise reports to run the business.
Equip DevOps for data pipeline in the big data ecosystem and implement continuous deployment for machine learning models in production.