Optimize at every stage of your implementation
Alignment of your architecture to specific use cases is key to maximizing the value of your data. Cloudera offers the most technical insight to help move your Hadoop cluster from proof of concept to production quickly, painlessly, and with peak performance. No one has more real-world experience with Big Data deployments than Cloudera Solution Architects.
Shorten your timeline to production
An Enterprise Data Hub certified to Cloudera's requirements stands up faster, with less risk, and at lower cost. Cloudera provides onsite support to design, prototype, deploy, secure, and optimize the complete data pipeline from ETL to data science. We also offer expertise in web servers, distributed logging, message buses, search indexing, and databases.
Realize the full value of your use case
Our goal is to ensure your infrastructure outperforms standards at every stage of the Big Data lifecycle. Cloudera Solutions Architects draw on the most significant Hadoop knowledge base, documenting hundreds of deployments across all industries to configure your cluster to use-case specifications and fine-tune to avoid downstream issues.
- Install, upgrade, and certify your environment according to best practices
- Fully review hardware, data sources, typical jobs, and existing SLAs Develop, implement, and benchmark deployment best practices
Ingestion ETL pilot
- Design and implement a custom data pipeline in two weeks
- Reference implementation to three sources, five transformations, and one target. Create, execute, test, and review a custom ingestion/ETL plan
Descriptive analytics pilot
- Architect a real-time query and delivery solution for petabyte-scale data
- Architect a pilot system based on Hive, Pig, HBase, and Impala Implement storage, schema, partitioning, and integration processes
Security integration pilot
- Exceed requirements with a governance, audit, and compliance plan
- Customize a secure reference architecture. Meet requirements for authentication, authorization, and access
- Identify challenges to ensure a fast, successful production rollout
- Optimize platform, architecture, and team structure for production. Set strategy for rollout and cluster evolution aligned to future needs