Managed Data Services | Starschema
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Managed Data Services

Data platform management and DataOps for your entire data pipeline

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.

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

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Improve platform performance
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Lower operational costs
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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

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Managed Data Services
Ask the expert

Balint Kocsis, strategic accounts director at Starschema, has seven years of experience with data operations in enterprise environments either as a consultant, team lead, or a delivery manager. He builds high functioning operations teams from scratch for single technologies or a full-scope enterprise data lake architectures.

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