Instant Cloud Data Lake Architecture: A New SaaS Platform to Accelerate time to analytics

At Cazena, we have just released the latest version of our Instant Cloud Data Lake. Unlike DIY (do-it-yourself) cloud data lakes, the Instant Cloud Data Lake aims to shrink time to analytics from months to minutes with zero operational resources required. How does it do that? 

The Instant Data Lake architecture is based on a new, fully automated SaaS platform with three key capabilities: 

1.     SaaS Orchestration  The Instant Data Lake is turnkey “SaaS-as-code”, meaning the entire stack including cloud resources, security, IDM, data processing engines (or PaaS), and analytical tools are integrated, instantiated, configured, secured, and hybrid-connected to the enterprise. Production-ready with certified compliance in minutes.  

2.     Self-Service Analytics Console Data scientists and data engineers can immediately start using their tools or access popular third-party tools with a simple Self-Service console.  All the tools are automatically and securely wired into the data lake. No platform skills are needed. 

3.     Continuous Ops  The Instant Data Lake is continuously optimized and monitored to ensure performance, cost, and security. All DevOps, SecOps and PlatformOps are built-in, so zero operational resources are required by the enterprises.

The figure above shows the Instant Data Lake architecture and the underlying SaaS data platform. The novel part about the SaaS platform is that it can flexibly embed best of breed, cloud-native and open-source PaaS stack alternatives with a variety of data processing engines (SQL, Spark, etc.). This provides enterprises with flexibility and ease of use, and future-proofs their cloud data lake.

You can download the Instant Data Lake white paper for more details on the architecture.

What’s a typical Instant Cloud Data lake experience? The outcomes speak for themselves. At Cazena, we have had 100% renewal rates on our production cloud data lakes, with over 60% average growth. Most enterprises have deployed immediately and experienced production outcomes within weeks. Zero operational or platform engineering resources are required, so enterprise data and analytics teams can focus entirely on their strategic mission and outcomes. Time to analytics is the key metric to evaluate the success and business value of cloud data lakes. Read here about time to analytics acceleration and customer case-studies like CWT and Worthington.

Click here if you would like a hands-on experience with the Instant Cloud Data Lake.