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’s managed data services ensure high availability and peak performance while reducing operational costs of your data pipeline.
Managed Data Services
Data platform management and DataOps for your entire data pipeline
Data platform management and DataOps for your entire data pipeline
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.
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.
Platforms
Ask the Expert
Balint Kocsis
VP of Sales
Balint Kocsis, strategic accounts director at Starschema, has several years of experience with data operations in enterprise environments either as a consultant, team lead or delivery manager.
He builds high-functioning operations teams from scratch for single technologies or full-scope enterprise data lake architectures.
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