Our cloud data engineering services are designed to transform your business by creating robust and scalable data foundations across any scale. We provide comprehensive solutions to assess, architect, build, deploy, and automate your data engineering landscape on the leading cloud platforms.
AWS Data Engineering Services
Unlock the potential of your data with robust and scalable data foundations on the cloud, designed to meet your business needs at any scale. Our comprehensive data engineering services offer end-to-end solutions, from assessment to deployment, leveraging the full power of Azure’s cutting-edge platforms, tools, and services. We empower your organization to derive actionable insights, optimize operations, and drive innovation.
everage the power of AWS to build a scalable, secure, and highly available data engineering landscape. Our AWS data engineering services utilize the extensive suite of AWS products and services to design and implement a data-driven strategy that drives business value.
Data Engineering Assessment on AWS
AWS Well-Architected Framework: Evaluate your data architecture using AWS Well-Architected Reviews to ensure it aligns with best practices.
AWS Data Analytics Maturity Model: Assess your analytics maturity with AWS’s tools to define a clear path for data-driven transformation.
Data Foundation on AWS
Amazon S3: Scalable storage foundation for data lakes.
AWS Lake Formation: Simplify the process of creating and managing a secure data lake.
Amazon Redshift: Fast, scalable data warehouse for analytics.
AWS Glue: Fully managed ETL service for easy data preparation and integration.
Amazon RDS & Aurora: Managed relational databases to support transactional workloads.
Data Management on AWS
AWS DataOps Services: Automate data pipelines with AWS Step Functions and AWS Lambda.
Amazon Managed Workflows for Apache Airflow (MWAA): Orchestrate data workflows with a managed Apache Airflow service.
AWS CloudWatch & X-Ray: Monitoring, logging, and observability for data operations.
Data Democratization on AWS
Amazon QuickSight: Empower users with fast, easy-to-use BI service with natural language querying.
AWS Data Exchange: Access third-party datasets directly within AWS.
Data & ML/LLM Ops on AWS
Amazon SageMaker: Comprehensive ML service to build, train, and deploy models at scale.
Amazon EMR: Managed big data service to process large datasets quickly.
Amazon Comprehend & Translate: Leverage NLP and translation for LLM (Large Language Models) applications.
Data Modernization on AWS
AWS Database Migration Service (DMS): Simplify and accelerate database migrations.
Amazon DynamoDB: Modernize data architectures with a managed NoSQL database service.
AWS Glue DataBrew: Prepare and clean data without writing code.
GCP Data Engineering Solutions
Harness the power of Google’s advanced cloud infrastructure to transform your data landscape. Our GCP offerings are designed to build, manage, and optimize data engineering processes using Google Cloud’s innovative solutions.
Data Engineering Assessment on GCP
Google Cloud Maturity Assessment: Evaluate your data maturity using GCP’s tailored assessment tools.
Google Cloud Adoption Framework: Define your strategy with a comprehensive roadmap.
Data Foundation on GCP
BigQuery: Serverless, highly scalable, and cost-effective multi-cloud data warehouse.
Google Cloud Storage: Unified object storage to build data lakes.
Cloud SQL & Spanner: Managed relational databases for high-performance workloads.
Cloud Composer: Managed Apache Airflow service for workflow automation.
Data Management on GCP
Google Dataflow: Stream and batch data processing with Apache Beam.
Google Dataproc: Managed Spark and Hadoop services for data processing.
Cloud Monitoring & Logging: Full-stack observability with integrated monitoring and logging solutions.
Data Democratization on GCP
Looker: Data exploration and visualization platform for self-service analytics.
Google Data Studio: Turn data into informative dashboards and reports.
Data & ML/LLM Ops on GCP
Vertex AI: End-to-end platform to build, deploy, and scale ML models.
TensorFlow Enterprise: High-performance deep learning on Google Cloud.
Natural Language AI: Analyze and understand text data for LLM applications.
Data Modernization on GCP
Database Migration Service: Accelerate migrations with minimal downtime.
Bigtable: High-throughput, low-latency NoSQL database for massive workloads.
Anthos: Modernize applications with hybrid and multi-cloud capabilities.
Snowflake Data Engineering Solutions
Maximize the potential of your data with Snowflake’s data cloud. Our services harness Snowflake’s powerful features to architect, build, and manage a modern data platform.
Data Engineering Assessment on Snowflake
Snowflake Data Maturity Assessment: Evaluate your data environment and define a clear roadmap for data transformation.
Data Foundation on Snowflake
Snowflake Data Cloud: Unified platform for data warehousing, data lakes, and data sharing.
Virtual Warehouses: Independent compute clusters for on-demand scalability.
Secure Data Sharing: Share data securely within and across organizations.
Data Management on Snowflake
Snowpipe: Automated data ingestion for real-time analytics.
Task and Streams: Automate and schedule SQL-based tasks and data pipelines.
Time Travel and Fail-safe: Data protection with historical data access.
Data Democratization on Snowflake
Snowflake Marketplace: Access a wide array of third-party datasets and applications.
Data Sharing & Collaboration: Seamlessly share and collaborate across teams and organizations.
Data & ML/LLM Ops on Snowflake
Snowflake Data Science Workbench: Integrate with data science tools like Python and R.
Snowpark: Native support for data engineering and ML workflows.
ML Integration: Seamless integration with tools like DataRobot, Dataiku, and Amazon SageMaker.
Data Modernization on Snowflake
Seamless Cloud Migration: Accelerate your data warehouse migration to Snowflake.
Multi-Cloud Flexibility: Deploy across AWS, GCP, and Azure with unified data governance
Learn more about us at : info@transorg.com
