AWS Data Engineering Solutions

Sigma Software, as an Advanced AWS Partner, provides comprehensive Data Engineering services AWS Data Analytics Lens to help companies enhance their data capabilities, increase their data maturity level, and gain valuable insights from their data assets. Aligning with AWS best practices and guidelines, Sigma Software has extensive technical experience in: - Data Ingestion Design and implement multi-source ingestion pipelines(databases, APIs, filesystems, CRMs, etc.) using services like AWS AppSync and AWS Database Migration Service Efficiently handle a wide range of data types and formats. Design and implement push/pull data ingestion models. Develop and integrate real-time data ingestion pipelines. - Data Processing Implement retry and reprocessing mechanisms to ensure data consistency. Deliver data pipelines at scale with high availability and performance requirements. Design and implement batch and real-time data processing pipelines. Leverage AWS data processing services like AWS Lambda, AWS Kinesis, AWS EMR, AWS Glue ETL or Amazon Athena - Data Storage and Warehousing Organize raw structured and unstructured data with a data lake with the help of AWS S3. Structure data with data warehouses and implement effective data rollups using solutions like Amazon Redshift. Introduce a data catalog and schema registry using AWS Glue Catalog. Implement data lineage services and multi-versioning with Amazon DataZone. - Data Analysis Prepare analytical views and tables. Gather data insights and metrics with Amazon CloudWatch. Implement aggregation groups and optimize analytical queries using Amazon Athena. - Data Visualization Utilize open-source and proprietary visualization tools with Apache Superset. Implement push/pull-driven reporting. Design low-latency BI tools for quick insights with tools like Tableau, Looker, PowerBI or Amazon QuickSight. - Data Governance Establish data cataloging and metadata management practices for data visibility. Design and implement comprehensive data quality checks for data validation. Train and develop data specialists to ensure data literacy within your organization. Implement security mechanisms and approaches to meet high data security standards and compliance requirements.