The Big Data Hadoop ecosystem has established itself as an enterprise-grade data stack, for both on-premises and cloud-hosted deployments. The full stack provides strong support for every layer, from storage, with HDFS and cloud object stores, streaming pipelines, analytical engines to SQL-based query and analytics capabilities. New innovative ways to extract value from big data are being created every day, including exciting advances in artificial intelligence (AI) and machine learning (ML).
I’ve spent a majority of my career building database-related software infrastructure products and find it a fascinating as well as fast-paced technology space. One thing I can say for sure is, that while extracting intelligence from historical data can be very powerful and strategic, it can also be extremely daunting.
Challenges include managing hardware (cloud) costs as well as the engineering and IT effort required to assemble and maintain rapidly growing and continually-evolving data platforms. And finally, the data must be secure, yet easily accessible by authorized staff and business intelligence tools within your enterprise. While it would be possible for companies to take the DIY approach to big data, it often requires upwards of 5 – 7 engineers plus one to two years lead time to create a enterprise-class data lake that can securely power your enterprise.
Cazena’s mission is to remove these challenges for you. Then, you can focus on producing (and acting on) insights from enterprise data and analytics rather than deploying managing and monitoring infrastructure and big data software components. To that end, Cazena offers Fully-Managed Big Data as a Service.
This means that Cazena delivers:
- Security, first and foremost. Cazena provides a SOC II-compliant cloud environment: Your data must be secure, protected, with access controlled and audited, and continuously monitored. In essence, Cazena provides Chief Security Officer-level responsibility for your data lake.
- Big Data, Cloud, DevOps and Data Lake expertise. We provide architect-level expertise across the Big Data ecosystem, including Cloudera, and the many Hadoop-related components such as Spark, Kudu, Impala, Kafka as well as the enterprise analytics, data science, ML and business intelligence tooling surrounding the data lake.
- Big Data DevOps support around the clock. A data lake is not very useful if it is unavailable. Our team manages your data lake for you, providing high-availability, failure resolution, component upgrades, security patches helps resolve any user issues, such as job performance tuning and day-to-day maintenance.
In short, Cazena does the heavy lifting for you by creating, securing and fully managing your corporate data lake as a service in the cloud. That’s what excites me about Cazena. Deployments usually take less than a month, with no additional staffing required. All you need to do is point your existing analytics/ML tools at the newly created data lake, and you are off and running. The result is an agile big data strategy at a greatly reduced cost, delivering significant ROI.
All of this is made possible by the team at Cazena. Cazena’s team knows data, with a strong pedigree in data and data warehousing technologies. The founding CEO, the sales and marketing teams, and of course the engineering team are staffed with veterans from Netezza, Sybase and other analytical and transactional database companies. They know how to deliver highly-available data and analytics systems, designed for the needs of enterprises and innovative businesses.
I am thrilled to have joined this smart group of people as their VP of Engineering, and look forward to helping to build the Cazena offering. Should you wish to dive deeper into the technical details of Cazena’s fully-managed Big Data as a Service, this quick read gives a great summary. Feel free to drop me a note with any questions.
Photo credit: Author and Cazena VP of Engineering John Piekos took this inspirational photo of actual lakes (not data lakes!) from a bush plane over the Alaskan Tundra in Katmai National Park.
