Data Strategies for Data Lake, Machine Learning and Advance Analytics Platforms
Our Services
Build Data Models
Pre-built data models to automate various ETL functions and customized for your business use cases. These models are battle tested and help build self monitoring, self correcting at-scale data platforms
Data Architecture
We conceptualize the data architecture of your desired end state of the data platform including documentation, diagrams, best practices, standards and roadmap for the team to execute. The scope includes ETL engine, data pipelines, BI platform, ML models, data observability platform, anomaly detection and so on
Design BI & Reporting Systems
Lot of companies strive to build a scalable reporting system but are often struggling to just keep up with business demand and as a result not able to innovate and modernize their BI stack. We build a scalable self service BI system for you which removes the data engineering department from critical path and help them focus on their core competency
Data Migrations
Data migrations have been a fact of life, are full of complexities and most data practitioners are resigned to it. The modern cloud stack and big data strategies, however, are more than a match. We help you build a 'future-proof' data lake system on which you can stand all your applications and don't have to worry about migration ever again
Prototyping
We stand behind our design and architecture guidance. However it is not just words, we build the initial prototype to prove the concept and build credibility with the leadership. Our engineers have experience of multiple implementations behinds them and can help to bring the vision into fruition
Execution Guidance & Support
We mentor, train and coach your team to stand on their own and guide them into building successful data platform. Our success lies in our eventual redundancy
We Integrate With Your Ecosystem
We front load our time in thinking, plotting, strategizing on the tools, design, scaling, performance, security, maintenance before writing the code .The emphasis on thinking through the design is what separates a well oiled data system from chaos and a key differentiator