Why Companies Are Moving Their Analytics to AWS Cloud

Moving analytics to the cloud is now a best practice for companies of all sizes and industries. According to a 2020 survey by MicroStrategy, 47 percent of organizations have already moved their analytics platform into the cloud, while another 42 percent have a hybrid cloud/on-premises analytics solution.

As an AWS Advanced Consulting Partner, Datavail has helped countless companies move their analytics tools to Amazon Web Services. Below, we’ll go over the benefits of migrating to AWS cloud analytics, as well as some tips and tricks we can share from our AWS cloud migrations.

The Benefits of Analytics on AWS Cloud

More and more companies are running their business intelligence and analytics workloads in the cloud. The advantages of moving analytics to AWS Cloud include:

• Lower IT costs: Cloud migrations save businesses the costs of on-premises hardware, software licenses, and ongoing support and maintenance.
• Increased scalability and flexibility: As you accumulate more and more data, scalability becomes an increasingly important concern for analytics, especially to handle rapid usage spikes. The AWS Auto Scaling feature lets you define rules to automatically adjust your capacity, so the system never goes down due to heavy demand.
• Data backup and business continuity: Tools like AWS Backup help you get your business back up and running more quickly in the wake of a disaster.

Tips and Tricks for Moving Analytics to AWS Cloud

The benefits of an AWS cloud migration are clear—so what are some tips, tricks, and best practices for moving your analytics to AWS Cloud?

1. Don’t rush into things

   Before executing any cloud migration, organizations need to perform due diligence and develop a clear strategy.

   The due diligence phase incorporates multiple steps:

   • “Discovery” of existing data assets and technologies.
   • Evaluating the organization’s goals and requirements.
   • Understanding the relationships between data, applications, and workflows that will be affected by the migration.

    
   Next, organizations need to decide the appropriate strategy for migrating their on-premises analytics solution. Amazon outlines 6 cloud migration strategies (known as the “6 Rs”):

   • Rehosting legacy applications by moving them to the cloud largely unchanged.
   • Replatforming applications by making a few changes and optimizations.
   • Refactoring applications by changing their architecture for the cloud.
   • Repurchasing by shifting to a SaaS (“software as a service”) model.
   • Retiring applications that are no longer used or necessary.
   • Retaining on-premises applications that require extra work before a cloud migration, but that are too critical to abandon.

 

2. Use AWS tools to help with the migration

   If you’re moving your analytics to AWS Cloud, why not leverage all that the cloud has to offer? The AWS cloud includes multiple tools to assist with a cloud migration, including:

   • AWS Application Discovery Service for collecting information during due diligence
   • AWS Database Migration Service to avoid downtime with your on-premises database during the migration
   • AWS S3 Transfer Acceleration for faster data transfers into Amazon S3
   • AWS Migration Hub for monitoring the status of a migration

 

3. Take full advantage of the AWS ecosystem

   Just the simple fact of having migrated your analytics workloads to AWS Cloud doesn’t mean that you’re actually taking full advantage of the capabilities of the AWS ecosystem. One of Datavail’s clients, a media supply chain company in California, had already migrated its on-premises analytics to the cloud, but was struggling to adapt the platform to its new home. As a result, the client was experiencing common growing pains of cloud migrations, such as poor scalability, lack of licenses and servers, and various technical limitations.

   With the help of Datavail, the client developed its analytics platform into a robust, completely serverless AWS cloud solution leveraging the entire AWS ecosystem:

   • First, existing data sources are placed in Amazon S3 staging areas, and then migrated into Amazon RDS data marts.
   • The client uses the Amazon QuickSight BI tool to run queries and self-service analytics.
   • Datasets can be easily transferred and delivered using S3 buckets and the AWS Data Pipeline managed ETL service.
   • Key decision-makers receive timely, scheduled reports in their email inboxes.
   • The entire AWS environment is monitored using the Amazon CloudWatch

How Datavail Can Help

Datavail is an AWS Advanced Consulting Partner, with years of experience helping businesses migrate to the AWS cloud. We have the knowledge and skillset to make your next AWS cloud migration a success. Our cloud migration services include:

• Selecting the right cloud technologies.
• Completing a cloud readiness assessment of your organization.
• Developing a cloud migration roadmap with an appropriate timeline.
• Creating a total cost of ownership (TCO) estimate and deploying a proof of concept.
• Uplifting analytics solutions from on-premises to the cloud.
• Providing ongoing cloud support, maintenance, and management.

Conclusion

Want to see the benefits of moving analytics to AWS Cloud for yourself? Get in touch with Datavail’s team of cloud migration experts today for a chat about your business needs and objectives—or download our white paper “Across the Continent with Cloud Analytics” to see how 8 of our clients have leveraged cloud analytics to their advantage.