Ingest data and load into AWS. Ingest Module can be hosted on prem to push to S3. Alternately deploy it in AWS cloud
Build your data transformation pipeline using the rich drag and drop GUI and PySpark
Configure transformed output as data product that can be leveraged in other pipelines.
Deploy to different environments or create new versions at the click of a button. Let the tool handle all the operations in the backend.
Run your pipelines on serverless spark that auto scales based on load. Save on cost and improve efficiency
Organize teams around data domains/business units to manage the various sets of products.
AI Sutra product is a AWS hosted solution that is deployed into your Virtual Private Cloud (VPC) using Terraform/Cloudformation.
View and manage organization wide data mesh in the mesh view. Manage Scheduling of the pipeline runs
Track usage of the Spark server in EMS by each run and analyse at product level
Assessing an organization's current data infrastructure,understanding its business goals, and developing a strategic plan to leverage data effectively
Assist in designing and implementing data integration solutions that enable organizations to aggregate, cleanse, and harmonize data from disparate sources. This may involve setting up data warehouses, data lakes, or implementing ETL (Extract, Transform, Load) processes
Provide expertise in statistical analysis, machine learning, and predictive modeling techniques to uncover patterns, trends, and predictive insights from data.
Assist organizations in processing and analyzing large volumes of structured and unstructured data using big data technologies such as Hadoop, Spark, or NoSQL databases
Offer services in developing machine learning models, implementing AI algorithms, and deploying predictive analytics solutions tailored to specific business use cases.
Communicating insights effectively through compelling data visualizations and storytelling techniques, enabling stakeholders to understand and act upon the insights derived from data.
Assist organizations in migrating their analytics workloads to cloud platforms like AWS, Azure, or Google Cloud, leveraging scalable infrastructure and services for data processing and analysis.
Services to assess risks, implement security measures, and ensure compliance with data protection regulations.