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DATA ENGINEERING 

Build the foundation for data that can power AI

Rackspace Data Engineering modernizes databases, analytics and data platforms into governed, connected foundations, then operates them 24x7x365. Put trusted data to work across reporting, analytics and AI, with the quality, access and controls each use case requires.

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AI requires data that is connected, governed and usable

Enterprise data is usually spread across databases, applications and platforms, often with different definitions, quality standards and access controls. This creates friction when teams need to connect, analyze and use information across the business. Analytics and AI can expose those gaps quickly. Data Engineering brings that information together with the pipelines, governance and quality controls needed to make it usable across reporting, analytics, applications and AI.

Outcomes

Data that is trusted, available and ready for the work ahead

One trusted view

Consolidate fragmented sources with consistent definitions and governance so teams across the business can work from the same information. 

Faster access to insight

Give teams self-service reporting and analytics so they can explore data and answer business questions without waiting on lengthy data preparation. 

Data ready for AI

Build pipelines, quality controls and data products that can reliably feed analytics, models and agents in production.

Governance built into the platform

Apply lineage, residency, access controls and auditability across the data platform to support regulatory and business requirements. 

OUR SERVICES

Modernize your data environment and operate with confidence

Choose the modernization services your data environment needs, then extend into ongoing operations for the platforms, pipelines and databases you rely on. Each service can stand alone or connect with the others as your requirements evolve.

Modernize

Analytics modernization

Move legacy data warehouse and BI environments to modern cloud analytics platforms. Migrate and validate reporting, analytics and data models while improving scalability and access to data. 

Database modernization

Move self-managed, on-premises databases to cloud-native platforms designed for performance, scalability and cost efficiency. Rackspace handles assessment, conversion, migration and cutover. 

Cloud-native data platform build

Build a new cloud-native data platform that consolidates sources, supports governance and scales with reporting, analytics and AI requirements. 

Operate 

Modern operations for data and AI 

Operate data platforms and pipelines with ongoing monitoring, data quality alerting and automation, reducing routine management work for internal teams.

Modern operations for databases 

Run day-to-day database operations with Rackspace managing patching, backup, performance tuning, availability and response. 

WHERE IT FITS 

The layer between infrastructure and AI

Data engineering builds and operates the data layer between governed infrastructure and Enterprise AI. It prepares and manages the data foundations that analytics and AI rely on. Rackspace Forward Deployed Engineers can then build AI solutions on that foundation, connecting infrastructure, data and AI under one operating model.

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Industrias

Pericia de confianza para industrias donde hay más en juego

Healthcare

Epic and clinical platforms kept available, patient data protected, and a governed foundation ready to move AI from pilot to the point of care.

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Financial services

Core banking and payments modernized with proven recovery, data control and the audit evidence regulators expect, so AI can follow safely.

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Public sector

Sovereign, accredited cloud for citizen services, run by cleared teams, with the control to modernize today and adopt AI when you’re ready.

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Rackspace has done a superb job with the SDDC migration, with excellent project governance, hitting milestones on time and with minimal disruption to business as usual.

Ian Kerwin, 

Head of IT & Cloud Operations, Metro Bank

FAQ

Frequently asked questions

Rackspace Data Engineering includes services to modernize analytics, databases and data platforms, along with ongoing operations for data and AI platforms and databases. These services address data integration, quality, governance and operations to support reporting, analytics and AI.. 

Rackspace supports data and analytics services across AWS, Microsoft Azure and Google Cloud, along with Rackspace Private Cloud for workloads with specific control or residency requirements. We also support relational and NoSQL databases across cloud and on-premises environments. 

Yes. Modernized data platforms and databases can move into ongoing Rackspace operations, including 24x7x365 monitoring, data quality alerting, patching, backup and performance management. Rackspace can also operate existing platforms it did not build. 

Yes. Rackspace provides managed relational and NoSQL database services, including database as a service, with availability, backup, patching and performance tuning managed by Rackspace. 

AI-ready data is consistently defined, quality-controlled, documented and governed for access and lineage, with pipelines that can deliver the data models and agents need. The specific requirements for quality, latency, context and access depend on the AI use case. 

Rackspace can incorporate cataloging, lineage, quality rules, access policies and auditability into the data platform. Data can also remain in private or sovereign environments when residency or control requirements call for it. 

Get your data ready for analytics and AI

Over the course of a two-hour session, Rackspace data architects can assess your current data environment, identify what analytics and AI require and map the priorities for moving forward.