Power BI Optimization & Remediation Services

Slow performance is rarely caused by the tool itself, but rather by how the data is modeled. Based on our audits of manufacturing environments, the most common culprits are inefficient DAX queries (such as using nested IF statements instead of SWITCH), “Model Bloat” caused by unnecessary columns, and the default “Auto Date/Time” feature which can generate massive, hidden tables that consume memory. We identify these specific bottlenecks during our initial assessment to reduce load times from minutes to seconds.

Hardcoding occurs when a developer types a specific value (like “Year = 2024” or a specific product name) directly into the code instead of making it dynamic. It works fine initially, but as soon as the year changes or a product name is updated in your ERP, the report shows zero data or incorrect totals. This is a “silent killer” of data trust. Our remediation process scans for these static values and replaces them with dynamic logic that adapts as your business grows.

Refresh failures are a major disruption to daily operations. They usually stem from one of three issues: Gateway misconfigurations (common in on-premise manufacturing setups), expired credentials, or unannounced changes to the source data structure (like a column rename in the SQL database). We not only fix the immediate connection issues but also implement proactive monitoring alerts so IT is notified before the business users even notice a problem.

In 95% of cases, no. A “rip and replace” strategy is expensive and disruptive. We use a remediation approach. We analyze your existing .pbix files to identify what is salvageable. We then perform surgical fixes—optimizing the data model, cleaning up code, and removing unused artifacts—to stabilize your current environment. We only recommend a rebuild if the fundamental architecture is completely unscalable.

Manufacturing data is unique because of its volume and variety. You are likely blending financial data from an ERP (SAP, Oracle) with high-frequency sensor data from MES or SCADA systems. This often creates “Many-to-Many” relationship problems in Power BI that lead to incorrect calculations. We specialize in normalizing this data, creating proper “Star Schema” models that allow you to accurately correlate financial costs with production uptime and OEE without crashing the system.

We go beyond the basic Power BI interface. We utilize advanced diagnostic tools like DAX Studio, Tabular Editor, and VertiPaq Analyzer. These allow us to see “under the hood” of your reports to measure exactly how much memory every column uses and exactly how long every query takes to run. This data-driven approach allows us to pinpoint the root cause of performance issues with scientific precision.

This is usually caused by a lack of a central “Date Table” or inconsistent definitions of metrics (e.g., how “Gross Margin” is calculated). We solve this by introducing a Governance Framework. We consolidate shared dimensions (like Customer, Product, and Date) into a centralized dataset. This ensures that a report generated by the Finance team matches the report generated by the Plant Manager, down to the decimal point.

You will receive a detailed technical report that categorizes issues by severity (Critical, Major, Minor). It includes an analysis of your Data Model, DAX Code efficiency, Security settings, and Refresh architecture. Most importantly, it provides a prioritized “Remediation Roadmap”—a step-by-step plan of what to fix first to get the highest return on investment and immediate stability.

Yes. Large files (>500MB) are slow to download and prone to crashing. Often, these files are bloated with data that isn’t actually being used in any visual. We perform an audit to identify unused columns and high-cardinality fields (columns with thousands of unique text values) that hog memory. We have seen cases where optimizing data types and removing hidden tables reduced file size by over 90% while keeping all the visible data intact.