Budget: 5000 UAH Deadline: 30 days
Hello!
Directly connecting PowerBI to several disparate databases and local Excel files creates a fragile architecture that will start to "crash" your servers when generating the first massive report. As my current project with complex data integration of SAP and OpenCart shows, trying to work with "raw" streams without an intermediate storage turns business analytics into a generator of system failures and inaccurate figures.
Abandoning data chaos "on the wire": Collecting metrics via API from various sources directly into the visualizer creates a critical bottleneck. It is necessary to implement an ETL (Extract, Transform, Load) architecture for centralized extraction, cleansing, and normalization of data from clouds, servers, and Excel into a single storage (Data Warehouse), and only from there safely deliver them to PowerBI.
Isolating analytics from production: Pulling arrays for reports directly from working servers means creating uncontrolled load on active databases. Analytical queries should refer to an independent, prepared copy of the data to avoid blocking transactions and slowing down current business processes.
Eliminating logic conflicts: Manual Excel spreadsheets and disparate SQL databases always have different formats and structures. Without prior strict standardization in the intermediate database, your consolidated dashboards will inevitably start to produce distorted metrics and discrepancies when trying to merge them.
How exactly do you plan to ensure the reliability of metrics and the stability of working servers if PowerBI starts pulling hundreds of thousands of unsynchronized rows directly from all sources at the same time?
Sincerely, Arseniy.