What we do
Our data expert helps businesses become data-driven by transforming data into valuable knowledge to anticipate market change, introduce new products and optimize cost
Data Infrastructure Modernization
Migrate your existing data pipeline to a modern and secure big data pipeline powered by major cloud providers. This ensures scalability, reduced maintenance, security, 24×7 uptime and reduced latency anywhere in the world.
ETL as a Service
Collect your raw data scattered across multiple sources and give it a cleaner, structured and meaningful representation. This will help in saving storage and DB space and get all the data in one place for convenience.
Cloud Data Analytics
Utilize cloud based industry leading technologies to get real time business value insights and optimized cost per KPI.
Components of Data Engineering Pipeline
Our data specialists support enterprises with data-driven solutions that reduce time-to-value and optimize costs.
Data collection is the process of obtaining data from a database or SaaS platform so that it can be replicated to a destination — such as a data warehouse.
Data transformation is the process of converting data from one format to another, typically from the format of a source system into the required format of a destination system.
A data pipeline essentially is the steps involved in aggregating, organizing, and moving data. Modern data pipelines automate many of the manual steps involved in transforming and optimizing continuous data loads.
Data science and ML
Data science automates the process of Data Analysis and makes data-informed predictions in real-time without any human intervention.
Data visualization is the process of giving a clear idea of what the information means by giving it a visual context through charts, graphs and numbers.
Why Choose our Data Engineering Solutions?
Leverage our expertise in multiple major cloud solution provider like Azure, AWS and GCP, and optimize your data platform based on the best practices of that cloud provider.
Use cloud based data streaming services to transfer data in real-time to get faster insights.
Leverage cloud based machine learning models to perform analytics on your data.
Leverage an event-based serverless architecture for your data pipeline which can be scaled as and when required in a cost-optimized fashion.
Data Engineering Frequently Asked Questions
2) Implementing the ETL processes
3) Validating and verifying data quality
4) Delivering analytics and KPIs based on the business need
Data engineering on the other hand is a process where you collect, transform and store the large set of data from different sources via a data pipeline.
Blogs & Articles
Check out the new stories published by our team