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Secure Data Platforms

Sherlock Data Services provides a one-stop shop for building and managing cloud-based data management solutions that enable access to on-demand, elastic, secure, data services to tackle a variety of data. These turnkey services span the entire data pipeline including ingestion & integration, storage, compute and end user tools.

Hurdles Academia and Research Projects Face

Challenges for Organizations

  • Existing on-premises data platforms are unable to scale.
  • Not maximizing ROI and overspending on compute, staffing and licensing costs.
  • Data compliance regulations with security and legal requirements.
  • Many academic and research teams lack time and resources to retrain on new technologies.
  • Hiring data and cloud engineers with the right expertise is slow and expensive.
  • SLAs must be upheld despite market changes and data complexity.
One-Stop Shop, Bespoke Data Solutioning

Benefits of Sherlock Data Management

Sherlock strives to create a well-architected solution that focuses on delivering value to customers while addressing key attributes around modernization, scalability, reliability and performance, security and cost savings

Cost-Efficient and
Agile Operations

Secure and Compliant
Cloud Hosting

Serverless and Automated
Data Management

Enhanced Data Processing
and Productivity

Unified, Secure Research Data Management

Accelerated Data Management | Unified Analytics

Move from dated data silos to a modern, cloud-based, secure data platform. End-to-end value around cloud infrastructure automation, security & compliance, FinOps, data management, and user apps. Platform for both engineering and data analysis teams.

Evolving Data Stacks to Meet Customer Needs

Sherlock Use Case

Sherlock, the University of California Office of the President’s (UCOP) risk and technology delivery services groups and DataMorph partnered to successfully re-architect and migrate the UCOP Risk Services Data Management System from an on-premise, Hadoop-based platform to a serverless, data lake platform in the AWS cloud.

Prior 2016

2016 (RDMS 1.0)

  • High License and Maintenance Costs
  • Process Semi & Un-Structured Data
  • Implement Data Lake

2021 (RDMS 2.0)

  • Serverless Computing
  • Pay-Per-Use
  • Reduced Infrastructure Maintenance
  • Efficient Data Processing
  • Reduced Cost


  • Additional Benefits
  • Simpler Data Engineering
  • Support for ACID Transactions
  • AI/ML Use Cases
  • Additional Reduction in Costs
Best of class Enterprise Products

Our Partners

DataMorph is a visually-driven data engineering platform for scaling ELT processes.

  • A low-code/no-code data engineering platform to build Data Products.
  • Designed for Business Analysts, Analytics Engineers, and Data Engineers.
  • Data integration, transformation & orchestration.
  • A single unified framework for real time and batch data pipelines.
  • Leverages simplicity of SQL and power of Spark.
  • Out-of-the-box pre-built data transformation processors.
  • Improves data team productivity by 80%-90%.

Databricks is a cloud-based platform designed for large-scale data engineering and collaborative data science.

  • Delta Lake offers industry-leading performance and a cost-effective lakehouse.
  • Efficiently handles large volumes of data and scales automatically.
  • Advanced analytics capabilities with support for machine learning and AI.
  • Supports a wide range of data sources and formats.
  • Robust security features.