Overview
Thoughtworks’ AWS-centric data modernization approach helps organizations to identify key changes needed to maximize cloud investments, demonstrate proof of value, adopt and scale a data products approach, and build the foundational workbench to sustain long-term impact. With 20+ years of expertise in engineering and data transformation, Thoughtworks helps businesses accelerate insights, optimize costs, and unlock the full potential of their data investments.
Thoughtworks enables enterprises to:
- Adopt a product-based approach to data, ensuring solutions align with business needs.
- Implement Agile engineering and DataOps practices to improve efficiency, scalability, and data quality.
- Transform governance into an enabler, allowing organizations to scale AI and analytics effectively.
- Establish a "data workbench" to standardize best practices and accelerate data product development.
- Optimize cloud costs through a structured data modernization roadmap.
Built with AWS technologies upon a structured data architecture that ensures enterprises unlock scalable insights, leveraging operational efficiencies from a cost-optimized cloud infrastructure. This cloud-native data engineering offering is enhanced with a suite of accelerators and proven governance frameworks to ensure a high-quality AI-ready data ecosystem.
Sample agenda:
- Week 1-2: Data modernization strategy & AWS alignment
- Week 3-6: Cloud-native data architecture implementation
- Week 7-10: AI-driven optimization & data quality enhancement
- Ongoing: Continuous governance & cost optimization
Client benefits and outcomes:
- Data readiness assessment & strategy definition–Identify modernization gaps and align transformation with AWS capabilities like Amazon S3, Amazon Redshift and AWS Glue
- Cloud-Native data platform implementation–Use Thoughtworks' suite of data product accelerators to define and deploy structured data products on AWS Glue Data Catalog and AWS Lake Formation
- AI-Enabled data optimization–Enhance data intelligence using Amazon SageMaker and predictive analytics frameworks
- Continuous data governance & compliance scaling–Automate governance and security with AWS Glue, DataZone & AWS Lake Formation
Highlights
- Cloud-native data engineering, resulting in AI-ready data pipelines–Leverage AWS Glue and AWS Lake Formation for scalable, high-performance data; optimize data transformation with AWS SageMaker Unified Studio ensuring structured, AI-ready datasets.
- Automated data governance & compliance–Ensure business relevance and regulatory alignment with Amazon DataZone and AWS Glue Data Catalog.
- Enterprise-wide data democratization–Enable seamless access, self-service analytics, and real-time AI insights using Amazon Athena and Amazon QuickSight.
Details
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