Migrating to Amazon Fast doesn’t need to imply ranging from scratch. Your dashboards encode hard-won area information: 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 watching tons of of dashboards and a migration estimate measured in months. Now you possibly can considerably speed up your migration to Amazon Fast, doubtlessly decreasing timelines from months to days.
On this put up, we stroll via the total journey, from establishing your migration workspace in AWS Remodel to subscribing to companion brokers via AWS Market to unlocking Amazon Fast capabilities that change how your group consumes information.
The true price of staying on legacy BI
If you happen to’re working a legacy BI instrument, you face compounding pressures that transcend licensing charges:
- You’re spending time on servers as an alternative 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 consists of 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 may publish dashboards straight into your individual purposes utilizing its embedded analytics APIs.
The case for modernization is evident. The query is how you can do it with out breaking what already works. To be taught extra about what Amazon Fast gives, 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 purposes, remodel Home windows and SQL Server workloads, migrate VMware environments, and modernize customized purposes. Now, the identical agentic AI platform extends to BI migration. Wavicle Information Options, an AWS Superior Consulting Companion, 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 via a conversational interface. For BI migration, Wavicle offers 4 specialised brokers obtainable for buy via 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. All the pieces runs inside your individual AWS account: no information ever leaves your surroundings, no separate instruments to acquire, and no exterior information transfers to approve. This removes the safety and procurement friction that sometimes slows migration tasks.
No matter your supply BI instrument, the migration follows the identical two-step course of:Within the Analyze step, the analyzer agent connects to your current BI surroundings, 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 would possibly require consideration. It helps groups perceive migration scope earlier than continuing.Within the Convert step, you determine 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 instrument.
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 surroundings, dealing with credential administration via workload identities and AWS Id 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 possibly can create and handle migration jobs via chat, observe progress throughout workspaces, and coordinate throughout groups.
- Amazon Bedrock AgentCore serves because the safe runtime surroundings, managing agent execution, credential storage via 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 studies and migration artifacts for audit and evaluation functions.
Your migration journey
Right here’s what the total expertise seems like, from first choice to migrated dashboards in Amazon Fast Sight:
Step 1: Full the stipulations in your supply BI
Earlier than working your first migration, you could put together your supply BI instrument 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 Conditions.
- 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 Conditions.
Step 2: Arrange AWS Remodel and Subscribe via AWS Market
Observe the steps on this interactive demo.
AWS Remodel offers the orchestration layer in your complete 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 possibly can convert tons of of dashboards concurrently with out sacrificing high quality or management.
Step 3: Analyze your BI dashboards
Observe the steps on this Energy BI Analyzer agent interactive demo or Tableau Analyzer agent interactive demo.
The excellent evaluation report captures complexity throughout varied dimensions akin to variety of information sources, analytical calculations, consumption nuances like conditional guidelines, and cross-dashboard dependencies. This permits migration venture managers to outline a migration execution plan based mostly on precedence and utility of the dashboards, even earlier than committing to further sources.
Step 4: Convert your BI dashboards
Observe 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 possibly can 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 workforce. This deliberate handoff helps keep high quality and clear accountability.Observe: The evaluation report flags elements which may want guide refinement after migration, akin to parameters, customized SQL, tool-specific calculations, and third-party visuals. There aren’t 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 buildings in your supply BI instrument hardly ever map one-to-one to Amazon Fast Sight. For instance, Tableau environments usually depend on Energetic Listing teams, whereas Energy BI makes use of workspace-level service principals. The migration agent transfers the analytical belongings, not the entry controls. You have to manually configure consumer 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 stay 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 via 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 best customers can entry the best information in Fast Sight. BI authors know their dashboards higher than automated instruments do. The agent will get the construction throughout. Your workforce confirms the substance is correct.
Publish and go stay
After validation, Fast authors publish their dashboards: configuring sharing permissions, establishing e mail subscriptions, and establishing embedding if wanted. For bigger migrations, you possibly can be taught extra about Amazon Fast Sight asset deployment APIs to automate permission assignments and dashboard distribution at scale. At that time, the unique supply dashboards could be archived.
Along with your dashboards stay in Amazon Fast, your groups unlock capabilities that weren’t attainable along with your legacy BI instrument: pure language queries, automated evaluation throughout enterprise information sources, and data-driven actions straight from dashboards.
Get began
You’ve seen the total journey, from Market subscription to production-ready dashboards. Right here’s how you can 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 workforce can cease managing BI infrastructure and begin getting insights quicker. And since AWS Remodel is the one place to go for all of your modernization wants, you should use the identical workbench in your subsequent modernization problem.You might have invested years in your dashboards. Now carry them to Amazon Fast in days and begin asking questions your legacy BI instrument might by no means reply.
Concerning the authors
