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    Data Modernization

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    Many organizations have moved their data to the cloud, expecting faster insights, better data quality, and lower costs—yet the expected value hasn’t materialized. Data silos persist, insights take too long to deliver, and promised cost savings remain elusive. Thoughtworks accelerates insight delivery by incrementally delivering meaningful use cases, using a product-centered approach to meet user needs, and applying DataOps practices to build quality data pipelines. This blend of user-centric thinking and engineering discipline enables rapid insight delivery and adaptation to evolving business needs. From data platform modernization to governance automation and AI-enhanced analytics, our approach ensures structured, accessible, and business-aligned data, enabling enterprises to reduce cloud costs, enhance compliance, and accelerate digital innovation.

    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

    Delivery method

    Deployed on AWS

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