AWS Partner Network (APN) Blog
How Wavicle’s QuickSight Migration Solution Accelerates Adoption of Amazon QuickSight
By Arthur K. Chan, Sr. Partner Solutions Architect – AWS
By Kalyan Kumar Neelampudi, Partner Solutions Architect, Analytics – AWS
By Anantha Choppalli, Chief Architect, AWS Solutions Practice – Wavicle Data Solutions
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Business intelligence (BI) software has matured over the decades from its roots in statistical analysis, online analytical processing (OLAP), and basic reporting.
Amazon QuickSight is a modern cloud-based BI service that helps Amazon Web Services (AWS) customers work with large amounts of data regardless where it’s located, such as in a traditional relational database, data warehouse, data lake, or joined with machine learning (ML) insights.
Amazon QuickSight enables users to create dashboards, generate multi-page reports, and answer questions to identify new business opportunities and gain strategic insights. As a cloud-based solution, it brings the capabilities of traditional BI tools into the modern era.
There are a number of new artificial intelligence (AI) features in QuickSight that many customers would like to adopt. However, migrating to QuickSight from legacy or high-cost BI solutions is not always cost effective and may introduce errors. In this post, we will introduce Wavicle’s QuickSight Migration Solution (QMS) which automates this process.
Wavicle Data Solutions is an AWS Specialization Partner and AWS Marketplace Seller with the Amazon QuickSight service delivery designation. From strategy to migration, Wavicle offers the cloud expertise to help you accelerate the value of your AWS investments.
What’s New with Amazon QuickSight
Amazon QuickSight Q is a feature that allows users to ask questions and get instant answers on their dashboards and datasets without having to rely on a pre-built dashboard.
Previously, answering next-level questions often required additional research, dashboard modifications, schema alterations, and other procedures by BI developers. With QuickSight Q, users are presented with a search bar where they can type natural language questions or choose from a list of verified answers to questions that have already been asked.
This self-service approach to getting insights reduces the burden on BI teams and allows dashboard consumers to quickly get the information they need through conversational interaction. Overall, QuickSight Q makes it simple for users, regardless of technical skill, to unlock deeper insights from their business data.
Amazon QuickSight offers competitive and flexible pricing to help clients avoid overprovisioning. QuickSight’s serverless architecture enables it to scale elastically based on usage rather than fixed resources, minimizing infrastructure planning and management. This allows QuickSight to handle high concurrency and seasonal peaks in demand while customers pay only for capacity used. The cloud-native, serverless design provides responsiveness during peak times without pre-provisioning infrastructure.
Migrating to QuickSight
Many business users are highly invested in other disparate BI solutions. In some cases, hundreds or thousands of staff hours have been invested in the development of existing dashboards. To take advantage of Amazon QuickSight, this typically requires BI developers to understand the original dashboards and then re-author them in QuickSight.
Despite the high total cost of ownership (TCO) with current solutions, the calculus of making additional investments to port current dashboards may not yield an acceptable return on investment (ROI) for years.
For organizations looking to migrate their legacy data visualization solutions to Amazon QuickSight, Wavicle’s QuickSight Migration Solution (QMS) is the answer to accelerate and automate the process. Rather than manual re-authoring, Wavicle’s QMS employs a technical solution to translate an existing dashboard to QuickSight.
Wavicle’s QMS is offered to customers who are looking to migrate their BI solutions to Amazon QuickSight. Here are links to Wavicle’s QMS offerings on AWS Marketplace:
To get started, users can assess the BI environment in-scope for migration using Wavicle’s QMS Analyzer to identify complexities, compatibility, and ultimately fixed migration costs. QMS will advance to the next stage, wherein it will systematically convert dashboards based on the complexities and compatibility identified in the preceding step.
Automated Analysis with Wavicle’s Analyzer
Utilizing Wavicle’s Analyzer, QMS provides advanced analytics capabilities including complexity analysis of each unique dashboard to determine migration effort, costs, and timelines.
A scoring system for duplicate recognition enables rationalization before scoping migration work. “Chart type” compatibility analysis identifies one-to-one mappings and any automated migration limitations. Results detailing compatibility and migration recommendations are delivered to clients in an Excel spreadsheet that they retain full ownership of.
Key benefits include automation to reduce effort, advanced analytics to inform migration planning, and deliverable results that equip clients to make data-driven migration decisions. Lastly, the product offers automated conversion of BI dashboards to Amazon QuickSight.
Utilization and Rationalization Analysis
Duplicate sets of data in multiple dashboards can be unnecessary, consumes resources, and increases the TCO of business intelligence solutions. QMS performs cross-analysis of the legacy BI service usage reports with Wavicle’s Analyzer. This identifies utilization and activity for each unique dashboard.
Analyzer associates each dashboard with a duplication percentage score from 0-100%. Dashboards scoring above a threshold are flagged as de-duplication candidates. Wavicle then conducts a rationalization and utilization working session with clients to review the analysis results and confirm the final number of dashboards that are in scope for the final conversion.
This comprehensive approach enables optimized conversion of legacy BI dashboards by eliminating redundant or unused dashboards based on data-driven analysis and client validation.
Solution Architecture
QMS runs in a customer’s Amazon Virtual Private Cloud (VPC). Running QMS within a VPC provides connectivity to customer’s existing BI systems, while ensuring the customer can ensure proprietary data does not leave their control. This is particularly important for customers in regulated industries looking to migrate from existing BI systems.
Figure 1 – QMS running in customer’s AWS environment.
Sample Process Flow Chart
The process flow reads from the BI server from client’s environment, through QMS and into the customer’s QuickSight instance.
Figure 2 – Typical QMS process flow.
Running QMS Inside a Customer Environment
You can obtain the Amazon Machine Image (AMI) from Wavicle to run in your Amazon Elastic Compute Cloud (Amazon EC2) instance. To get started, launch a browser and navigate to the web interface running on the EC2 instance.
When licensing QMS, Wavicle will send the customer license details by email. Upload the license file and validate it in the application. Once validated, the Analyzer application is ready to be configured with existing BI server configuration. QMS Analyzer will fetch available sites and workbooks from the BI server.
Figure 3 – QMS Analyzer result representing identified dashboard complexities.
Next, select and analyze workbooks, and then export the Analyzer report. Make selections for dashboard complexity and proceed to conversion. Enter details about the target Amazon QuickSight environment.
Select dashboards to convert, review, and proceed to conversion. Enter the required database connection details and click “Convert” to confirm the conversion.
Figure 4 – QMS Analyzer results representing destination configuration.
The application will go through the conversion and create necessary datasets and analysis in the target Amazon QuickSight environment. The application may take some time to complete depending on the number of workbooks.
Figure 5 – QMS Analyzer report representing conversion results.
End-to-End Testing, Validation, and Production Release
QMS offers robust validation to ensure all objects are successfully converted and the dashboard design matches the original BI service. End-to-end testing is a shared responsibility between the customer and Wavicle to ensure data flow, functionality, and usability to help meet or exceed expectations.
The production roll-out is customized to customers’ release schedule, and can be performed as an immediate cutover or phased deployment to fit their needs. Overall, QMS focuses on seamless conversion, collaborative testing, and flexible deployment options to provide a smooth transition to the new platform.
Conclusion
As organizations look to modernize their business intelligence services and to consolidate and modernize BI to Amazon QuickSight, migrating from legacy solutions can pose challenges. Significant time and resources are often required to manually redevelop dashboards in the new environment.
Wavicle’s QuickSight Migration Solutions (QMS) provides an automated, analytical approach to accelerate and optimize these migrations. By assessing complexity, identifying duplication, enabling automated conversion, and facilitating seamless rollout, QMS can reduce the effort, costs, and risks associated with moving to Amazon QuickSight.
The end result is that organizations can realize the benefits of self-service analytics, flexibility, and cost savings with Amazon QuickSight in a fraction of the time and with minimal business disruption. With solutions like Wavicle’s QMS, companies now have a clear path to unlocking the potential of modern analytics.
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Wavicle Data Solutions – AWS Partner Spotlight
Wavicle Data Solutions is an AWS Specialization Partner with the Amazon QuickSight service delivery designation. From strategy to migration, Wavicle offers the cloud expertise to help you accelerate the value of your AWS investments.