Cazena, a Big Data as a Service provider, expanded its services with the launch of a Data Lake as a Service that runs on Microsoft Azure and is securely integrated with the enterprise. The managed cloud service embeds Cloudera Enterprise and radically simplifies the process of deploying, operationalizing and maintaining a modern data management and analytics platform in the cloud. Cazena launched a similar service on Amazon Web Services (AWS) last year.
Cazena also added new capabilities for data science and analytics with embedded support for Spark, SparkR and RStudio so enterprises can use the latest analytic techniques and technologies without having to build and maintain their own Hadoop infrastructure. Data science teams want to use the Hadoop ecosystem for advanced analytic techniques but find that the infrastructure requirements can create time-consuming distractions from their goals. Cazena’s new offer makes it easier for companies to more quickly and easily, and with limited resources, move their successful big data pilots into production. Cazena also offers a Data Mart as a Service on Azure and AWS for high-performance, SQL-oriented analytical workloads.
Customers are increasing revenue, delivering value to customers, and reducing business risk by making Cloudera Enterprise a core component of their modern data strategy. Cazena’s fully-managed, as-a-service offering on AWS and Azure allows customers to move faster, be more agile, and easily expand the scope of their Cloudera Enterprise-based projects,” said Tim Stevens, vice president, Corporate and Business Development at Cloudera.
Gartner analysts Nick Heudecker and Mark A. Beyer succinctly summarized the current state of the market in a recent report: “The maturity of data lakes remains at “emerging” for 2016. Despite rampant interest, adoptions are limited to aggressive technology adopters, and false starts are frequent,” they noted in the data lake section of the Gartner Hype Cycle for Information Infrastructure, 2016, Donald Feinberg, Adam M. Ronthal, July 8, 2016.
Many consider the cloud for Hadoop and big data but find it difficult to integrate cloud with existing data centers. Lack of integration leads to cloud data silos, which are disconnected from other enterprise processes and not able to deliver value. That’s why Cazena services are delivered on a managed service platform, with built-in functions to securely move data and integrate the cloud seamlessly with on-premises infrastructure.
Cazena’s new Data Lake as a Service on Azure meets strong market demand to make big data infrastructure easier for analysts, business professionals and IT. Enterprises that trust Cloudera to deliver value and insights from big data and rely on Azure as their cloud platform now have a single, managed solution to accelerate time to insight for production projects without compromising on security and compliance,” said Prat Moghe, Founder and CEO of Cazena.
Data Lake as a Service addresses two primary use cases:
- Data Lake expansion, augmentation and migration to cloud – Many companies pilot Cloudera on-premises, then look to the cloud to quickly and easily scale for production. Cazena’s new service simplifies the migration of Cloudera workloads from on-premises environments to the cloud for big data staging and processing, collecting and exploring cloud data sources like SaaS, IOT, social or third-party datasets, and disaster recovery.
- Data Science and Analytic Sandboxes – Highly skilled scientists want to focus on advanced analytics, not infrastructure. They also want to use newer processing engines, such as Spark, along with Java, Python, and Scala, without all the troubleshooting required in DIY environments. Cazena supports existing development and analytics workflows while seamlessly managing infrastructure for data analysts and data scientists.
Cazena’s Data Lake as a Service is available now on Microsoft Azure and AWS through a single annual subscription fee that includes database, cloud and all other licenses, data movers, security, 24 x 7 SLA monitoring and support.
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