https://store-images.s-microsoft.com/image/apps.46648.f81e1129-1e77-4115-995a-fffd49398c7e.6a612c9c-8d28-4d58-8307-c79503e12f04.2cffd7ca-737c-44e7-86a8-24d452cd0364

Migration to Power BI – 1 Hour Workshop

Hexaware Technologies

In this Value Discovery Workshop, learn how you can cut down on Power BI migration cost & timelines via a risk mitigated approach using Hexaware’s AMAZE®

Why Migrate to Power BI :

Data landscapes are growing increasingly complex as more and more data keeps flowing in. Enterprises rely upon powerful reporting tools to derive meaningful insights which fuel critical business decisions. But the license cost for some of these reporting tools is extremely high. In comparison to which Power BI offers a solution that is 50%-60% cheaper while providing competing features.

However, migrating to Power BI itself can be a cost-intensive process that eats into the ROI of the solution. Moreover, testing of the reports in the new environment can be effort and time consuming.

Hexaware’s Solution :

Hexaware’s AMAZETM carries out cost-effective re-platforming of reporting tools such as SQL Server Reporting Services (SSRS), SAP Business Objects, COGNOS, MicroStrategy, Tableau, Qlik View and Oracle Business Intelligence to Power BI Report Builder. The solution assesses the current state to provide complexity and fit-gap with Power BI. For report verification and performance testing the report output extracts and report execution time will be compared between pre and post migration snapshots.

Agenda :

  • Hexaware Overview
  • Current & Target Technology State
  • Assessment & Migration Plan
  • Commercials
  • Relevant Proof-points
  • Q&A

Objective :

Provide an estimate on the following:

  • Cost of migration
  • Migration timeline
  • TCO savings
  • Risk mitigated approach for a successful migration

Who should be participating?

CXO, VP and Director level stakeholders in Data Analytics Ecosystem.

Vos žvilgtelėjus

https://store-images.s-microsoft.com/image/apps.8236.f81e1129-1e77-4115-995a-fffd49398c7e.350e5654-aa75-4589-9819-3c71b4e1cdd1.668fd943-bed8-4a03-9362-e2e2923f1a2e