How CloudWick Out-Performs the Competition in Big Data-as-a-Service

CloudWick is a proportionately large enterprise that offers Big Data-as-a-Service and now manages more than 50,000 Big Data clusters using AWS. As a Consulting Partner Expert within the field of APN Big Data Competency, the company has the background and the methodology (three repeatable steps) to perform Big Data integrations to AWS. The company allows architecting a Data Lake and moving workloads to be painless and simple.

The company is currently trusted with directing Cassandra, Hadoop and Spark provisions for numerous Global 1000 corporations. The experience they have with working in AWS allows them to be an ideal partner you can work with to construct a Data Lake within AWS. Find out the advantages of an AWS Data Lake using CloudwickQuick and construct your Data Lake service securely.

This will streamline the time you spend analyzing. Gain insight using the Cloudwick Jumpstart Package for an Advanced Analytics Data Lake.

Advantages of using a Data Lake with Cloudwick on AWS

Fixed Price Benefits: By giving prices that are fixed for their Big Data and cloud-managed platforms, Cloudwick is able to furnish customers with better performance, fewer costs, and assured SLA production with no additional risk of other expenses.

3-Step Approach: With experience in merging large Big Data loads of work to AWS, Cloudwick has gained the ability to develop a 3-step methodology that’s repeatable for Big Data Migrations such as Data Lake architecture.

Big Data Lake Managing Experience on AWS:

Handling more than 50,000 Big Data workloads within AWS, the company has grown to be one of the most sought-after Big Data managers. Their background in managing and architecting Data Lakes allows them to let organizations concentrate more on strategic initiatives in their respective businesses. With all of these combined aspects, working with CloudWick is a no-brainer.

https://pages.awscloud.com/rs/112-TZM-766/images/AWS_SolutionLaunchpad_DataLake_Cloudwick_08032017.pdf