Cloudwick And The Data Lake Foundation On AWS Quick Start

Cloudwick is a digital enterprise which provides big data services and solution to the Global 1000. The company was founded by Maninder Chhabra in 2011 and is based in California. Their portfolio includes biomed business transformation, CDAP, and Cloudwick one. CDAP is designed to store and manage events from syslog, proxy, netflow, and firewall logs. Bimodal business transformation helps assist its users when it comes to gaining competitive advantage as well as revenue. Last but not least, Cloudwick one offers its clients consumer insights as well as business intelligence services.

When it comes to data lakes, they can be applied to any industry vertical and they usually employ an ELT strategy, as opposed to an ELT strategy, which was employed in traditional data warehouse. Cloudwick is an AWS Advanced Consulting Partner, and in a while back they began offering Data Lake Jumpstart in order to help its customers deploy, pilot and also migrate into production a data lake that is running on Amazon Web Services. The heavily-discounted program from Cloudwick as well as AWS ia four-week engagement, having a typical cost of under $20,000.

One alternative for someone who is not ready for that type of investment is Data Lake Foundation on AWS Quick Start, which was co-authored with AWS Solutions Architects. This allows users to experiment with a data lake, and using Quick Start it can be up and running in approximately 20 minutes. Beyond the cost of running it on AWS, there are no additional payments needed or consulting fees. In addition, a data catalog which is based on Amazon ES helps automatically capture and surface the contents of the data lake.

The proven phases when it comes to deploying and managing a data lake are 3 in total. Quickly setting up Data Lake and starting analytics within 4 weeks, migrating the pilot deployment to production with best practices implemented around scalable data ingestion, lifecycle management for security, data quality, governance, etc., and finally managing the AWS Data Lake and workloads after migration. The last phase helps to ensure high performance, while at the same time enabling the organization to focus on strategic business priorities.

 

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