Managed Data Services

Today’s data platforms are complex, dynamic environments critical to the success of your organization. Managing all the integrated components across the data lifecycle, from ingestion to visualization, has become increasingly difficult and costly. Most large data platforms consist of dozens of technologies, each requiring specialized skills to manage and support. Starschema offers data platform management and DataOps managed services for your entire data pipeline — ensuring high availability and peak performance while reducing operational costs.

Data Platform Management

Starschema provides SLA-based managed services for all major databases, ETL tools, ingestion layers, and visualization platforms. These services ensure your critical data is clean, secure and delivered to end-users in near-real-time. Our proprietary tools alert us to problems so they can be resolved before affecting your users and operations.

Key Benefits

Improve platform performance

Lower operational costs

Increase business agility

Key features

Performance optimization

Proactive platform performance monitoring with routine health checks and proprietary tools that identify configuration modification opportunities, reduces issues and accelerates time to resolution.

Platform operations

Regular maintenance, upgrades, backup to ensure that your data platforms operate at peak efficiency, are secure and can be recovered quickly and efficiently should the need arise.

Cloud infrastructure management

Platforms dynamically scale according to your changing business needs. Using infrastructure as code, new infrastructure can go into production with minimal time loss and room for error.

24x7x365 support

Our help desk and online issue reporting tools ensure satisfied data consumers.

DataOps

Starschema’s expert teams coordinate and manage people, process and technology to operationalize data management and integration to ensure the continuous delivery of trusted data to analysts, users and applications on-time and at scale. Our methods, systems and knowledge enable clients to maximize the value of data during times of continuous change and throughout the data lifecycle.

Key features

Data integrity assurance

Automated and continuous data quality checks catch potential issues on the fly and trigger proprietary self-healing mechanisms to ensure that problems are discovered and fixed at the earliest possible time without interrupting business.

On-time data delivery and availability

Performance is measured and the necessary actions are taken at every stage of the data flow. Service level agreements (SLA) guarantee availability that meets your performance needs.

Data governance

Enterprise-grade data governance manages data availability, usability, integrity, and security so your data is protected and readily available by all necessary systems.

Cost & performance optimization

Reduces monthly cost for ingestion infrastructure and maximize performance.

Platforms

The Starschema Difference

Proven onboarding methodology

With standard processes for deployment, knowledge transfer, and integration with ticketing systems, Starschema ensures faster time to value.

Experience in large environments

Fortune 100 companies trust Starschema to keep their data pipelines robust, resilient, and reliable.

Flexible service models

Starschema offers Platform management and DataOps for entire, multi-vendor data pipelines or specific components.

Tools-based approach

Starschema deploys open source and proprietary frameworks, methodologies and tools to provide effective, accurate, and repeatable solutions and services.

Complete data lifecycle management

From ingestion to consumption, our teams of database administrators, data engineers, ETL developers, and data visualization experts can provide a seamless solution for your complete data pipeline.

Ask the Expert

David Kalan

Delivery Manager at Starschema

David has worked on data operations in enterprise environments either as a consultant, team lead or a data engineer for the better part of a decade. He builds high-functioning operations teams from scratch for both single technologies and full-scope enterprise data lake architectures.

A Fortune 50 conglomerate was not satisfied with its ability to serve internal customers’ data needs and track the costs associated with data requests. To achieve improved data access, as well as transparency and accuracy in intra-conglomerate financial affairs, they needed a flexible, metadata-driven solution.

Managed Data Services