Migrating to Amazon Fast doesn’t must imply ranging from scratch. Your dashboards encode hard-won area data: calculated fields your analysts perfected, layouts your executives depend on each Monday morning, safety guidelines tuned to your org chart. You need AI-powered insights and serverless scale, however you’re looking at a whole lot of dashboards and a migration estimate measured in months. Now you may considerably speed up your migration to Amazon Fast, doubtlessly lowering timelines from months to days.
On this publish, we stroll by way of the complete journey, from organising your migration workspace in AWS Remodel to subscribing to associate brokers by way of AWS Market to unlocking Amazon Fast capabilities that change how your group consumes information.
The true value of staying on legacy BI
If you happen to’re working a legacy BI software, you face compounding pressures that transcend licensing charges:
- You’re spending time on servers as a substitute of analytics. Patching, scaling, and monitoring infrastructure takes effort away from the insights work that drives enterprise worth. Amazon Fast is serverless and absolutely managed, so there’s no capability planning and no upkeep home windows.
- Conventional BI instruments require customized engineering for AI-powered solutions. Amazon Fast contains native AI capabilities that your groups can use to ask enterprise questions in pure language and automate workflows straight from dashboards.
- Your analysts wait too lengthy for solutions. Provisioning capability, managing extracts, and troubleshooting efficiency creates bottlenecks. The Fast Sight SPICE in-memory engine delivers sub-second question efficiency at scale, and you’ll publish dashboards straight into your personal functions utilizing its embedded analytics APIs.
The case for modernization is obvious. The query is the best way to do it with out breaking what already works. To study extra about what Amazon Fast presents, see Getting Began with Amazon Fast.
AWS Remodel, an AI-powered service constructed to speed up enterprise modernization, now solutions that how for BI migration. Organizations already use AWS Remodel to modernize mainframe functions, remodel Home windows and SQL Server workloads, migrate VMware environments, and modernize customized functions. Now, the identical agentic AI platform extends to BI migration. Wavicle Information Options, an AWS Superior Consulting Accomplice, integrates the EZConvertBI brokers straight into AWS Remodel, bringing deep Tableau and Energy BI migration experience for accelerating your cloud journey.
The way it works: A two-step, chat-based migration
In AWS Remodel, you create a workspace and launch migration jobs by way of a conversational interface. For BI migration, Wavicle offers 4 specialised brokers obtainable for buy by way of AWS Market: one Analyzer agent and one Converter agent for every BI migration supply (Energy BI and Tableau).
Collectively, these brokers ship a guided, chat-based, AWS-native migration expertise. Every little thing runs inside your personal AWS account: no information ever leaves your setting, no separate instruments to obtain, and no exterior information transfers to approve. This removes the safety and procurement friction that usually slows migration initiatives.
No matter your supply BI software, the migration follows the identical two-step course of:Within the Analyze step, the analyzer agent connects to your present BI setting, extracts metadata solely, cataloging dashboards, datasets, calculations, and dependencies throughout your workspaces, and generates a migration readiness evaluation. The evaluation features a compatibility report that reveals what’s going to convert cleanly and what may require consideration. It helps groups perceive migration scope earlier than continuing.Within the Convert step, you establish the dashboards emigrate and begin a conversion job. The Converter agent rebuilds belongings in Amazon Fast Sight, together with datasets, calculated fields (each on the dataset and evaluation degree), visualizations and charts, filters, and parameters. This preserves the analytical logic that your groups spent years growing in your BI software.
The brokers use Amazon Bedrock, a completely managed service that gives the underlying AI capabilities wanted for migration automation. Amazon Bedrock AgentCore (a safe runtime for internet hosting and managing AI brokers) offers the execution setting, dealing with credential administration by way of workload identities and AWS Identification and Entry Administration (IAM)-based entry management. The area experience comes from Wavicle’s deep BI migration expertise encoded into the agent logic.
Structure overview
The answer is constructed on the next AWS-native providers:
- AWS Remodel is a collaborative enterprise IT transformation workbench powered by professional brokers, agentic AI programs, and steady studying that accelerates cloud migration, legacy app modernization, and tech debt discount. It offers the orchestration layer with a conversational interface powered by Amazon Bedrock, so you may create and handle migration jobs by way of chat, observe progress throughout workspaces, and coordinate throughout groups.
- Amazon Bedrock AgentCore serves because the safe runtime setting, managing agent execution, credential storage by way of workload identities, and IAM-based entry management.
- Amazon Fast Sight acts because the goal BI service, providing serverless scalability, SPICE in-memory engine efficiency, and native integration with AWS information providers.
- Amazon Easy Storage Service (Amazon S3) shops validation stories and migration artifacts for audit and evaluation functions.
Your migration journey
Right here’s what the complete expertise appears like, from first choice to migrated dashboards in Amazon Fast Sight:
Step 1: Full the conditions in your supply BI
Earlier than working your first migration, you need to put together your supply BI software so the agent can learn your dashboard metadata:
- For Energy BI: Configure workspace entry and repair principal authentication so the agent can learn your Energy BI tenant metadata. For directions, see Energy BI Stipulations.
- For Tableau: Allow the Metadata API in your Tableau Server and generate a Private Entry Token (PAT) for authenticated API entry. For directions, see Tableau Stipulations.
Step 2: Arrange AWS Remodel and Subscribe by way of AWS Market
Comply with the steps on this interactive demo.
AWS Remodel offers the orchestration layer on your total migration. It deploys specialised AI brokers that automate assessments, dependency mapping, and transformation planning. Everybody works in the identical shared workspace, collaborating in actual time, monitoring progress, and managing the migration from begin to end. As a result of AWS Remodel executes duties in parallel, you may convert a whole lot of dashboards concurrently with out sacrificing high quality or management.
Step 3: Analyze your BI dashboards
Comply with the steps on this Energy BI Analyzer agent interactive demo or Tableau Analyzer agent interactive demo.
The excellent evaluation report captures complexity throughout numerous dimensions equivalent to variety of information sources, analytical calculations, consumption nuances like conditional guidelines, and cross-dashboard dependencies. This enables migration undertaking managers to outline a migration execution plan based mostly on precedence and utility of the dashboards, even earlier than committing to extra sources.
Step 4: Convert your BI dashboards
Comply with the steps on this Energy BI Convertor agent interactive demo or Tableau Convertor agent interactive demo.
The Converter agent rebuilds your chosen dashboards in Amazon Fast: datasets with mapped information sources and information varieties, calculated fields at each the dataset and evaluation degree, visualizations with preserved chart varieties and formatting, and filter controls with parameter inputs. All through the conversion, you may monitor progress straight within the AWS Remodel chat interface.
After the conversion completes, you obtain your Fast Sight belongings and may start the ultimate validation and go-live course of.
After migration: From transformed to production-ready
The migration agent delivers your transformed belongings: Fast Sight datasets and analyses, together with calculated fields, visuals, controls, and parameters. These are the constructing blocks. What comes subsequent, governance, validation, and publishing, is owned by your crew. This deliberate handoff helps preserve high quality and clear accountability.Observe: The evaluation report flags parts which may want handbook refinement after migration, equivalent to parameters, customized SQL, tool-specific calculations, and third-party visuals. There are not any surprises at this stage.
For Fast admin: Assign possession and configure governance
As Fast Sight administrator (the function configured within the Fast Sight connector), you assign possession of every migrated dashboard to the suitable BI authors.Consumer authentication and listing constructions in your supply BI software hardly ever map one-to-one to Amazon Fast Sight. For instance, Tableau environments usually depend on Lively Listing teams, whereas Energy BI makes use of workspace-level service principals. The migration agent transfers the analytical belongings, not the entry controls. It’s essential to manually configure person permissions, row-level safety (RLS), and sharing settings in Fast Sight to match your group’s necessities. For enterprises with complicated listing hierarchies, plan for this as a definite workstream.
This step establishes clear accountability: who owns every dashboard’s accuracy, who maintains it, and who controls entry. Nothing goes reside till permissions are correctly configured.
For Fast authors: Validate and settle for
You obtain the assigned dashboards and personal UAT. This implies verifying that visualizations, calculated fields, filters, and interactivity match the supply by way of side-by-side metric comparability, testing drill-downs and dashboard actions, and confirming structure consistency. As a result of the migration agent doesn’t carry over permissions or row-level safety, take into account verifying that the suitable customers can entry the suitable information in Fast Sight. BI authors know their dashboards higher than automated instruments do. The agent will get the construction throughout. Your crew confirms the substance is correct.
Publish and go reside
After validation, Fast authors publish their dashboards: configuring sharing permissions, organising electronic mail subscriptions, and organising embedding if wanted. For bigger migrations, you may study extra about Amazon Fast Sight asset deployment APIs to automate permission assignments and dashboard distribution at scale. At that time, the unique supply dashboards may be archived.
Together with your dashboards reside in Amazon Fast, your groups unlock capabilities that weren’t potential along with your legacy BI software: pure language queries, automated evaluation throughout enterprise information sources, and data-driven actions straight from dashboards.
Get began
You’ve seen the complete journey, from Market subscription to production-ready dashboards. Right here’s the best way to take step one:
Whether or not you’re migrating 10 dashboards or 10,000, AWS Remodel offers you a ruled, repeatable path to Amazon Fast. Mixed with Amazon Bedrock AI capabilities and Wavicle’s migration experience, your crew can cease managing BI infrastructure and begin getting insights sooner. And since AWS Remodel is the one place to go for all of your modernization wants, you should use the identical workbench on your subsequent modernization problem.You’ve gotten invested years in your dashboards. Now convey them to Amazon Fast in days and begin asking questions your legacy BI software might by no means reply.
Concerning the authors
