Enhancing Analysis with OLAP PivotTable Extensions: Top Features to KnowOLAP PivotTable Extensions is a powerful add-in for Excel that enhances the native PivotTable experience when working with OLAP cubes (such as SQL Server Analysis Services, Power Pivot, and other multidimensional or tabular data sources). For analysts, BI developers, and power users who rely on fast, flexible exploration of multidimensional data, OLAP PivotTable Extensions fills important gaps: it adds functions for advanced calculations, metadata inspection, member selection, and automation that Excel alone either lacks or implements awkwardly.
This article covers the most valuable features of OLAP PivotTable Extensions, how they improve analysis workflows, practical examples, and tips to get the most from the add-in.
Why OLAP PivotTable Extensions matters
Excel PivotTables connected to OLAP cubes are already a convenient front-end for slice-and-dice analysis, supporting hierarchies, calculated members, and built-in aggregation. However, the default UI can be limiting:
- Creating MDX queries or calculated members in Excel is non-intuitive.
- Inspecting cube metadata (members, levels, properties) is cumbersome.
- Selecting multiple non-contiguous members or building complex filters requires many clicks.
- Exporting MDX or capturing the exact query behind a PivotTable isn’t available out of the box.
OLAP PivotTable Extensions provides a set of tools that directly address these pain points, making advanced OLAP operations accessible inside Excel without requiring deep MDX knowledge.
Key features and how they help
1) Create and edit calculated members and named sets
One of the most powerful features is the ability to define calculated members and named sets directly from the PivotTable UI. You can write MDX expressions or use a guided editor, then test and apply them immediately.
- Benefit: Rapidly create reusable calculations (e.g., ratios, running totals, custom aggregations) without server-side changes.
- Example: Define a “Profit Margin” calculated member using [Measures].[Profit] / [Measures].[Sales] and add it to the Pivot layout.
2) View and export the MDX query
The add-in exposes the MDX query generated by the PivotTable and allows copying or exporting it.
- Benefit: Understand precisely what data Excel requests, debug unexpected results, and reuse queries in other tools or automation scripts.
3) Bulk member selection and advanced filtering
OLAP PivotTable Extensions lets you select many members quickly (search, select visible, select non-empty) and supports filtering by rules (top/bottom N, by value, or by label) with more flexibility than native Excel.
- Benefit: Save time when building views across large hierarchies or when you need to exclude sparse members.
- Example: Select top 10 customers by sales and then refine by a custom threshold.
4) Metadata browsing and property inspection
You can browse cube metadata—hierarchies, levels, members, and properties—and inspect member properties (such as keys, captions, and custom attributes).
- Benefit: Makes it easy to locate members, understand attribute values, and craft more accurate filters and calculations.
5) Bulk operations and batch editing
Perform operations like removing many fields, changing aggregation functions, or applying formatting across multiple PivotTables with minimal effort.
- Benefit: Streamline repetitive maintenance tasks across multiple reports, especially when schema changes occur upstream.
6) Named set management and sharing
Create, save, and reuse named sets across workbooks. The add-in can store definitions that you can quickly apply without retyping complex MDX.
- Benefit: Standardize commonly used member groups (e.g., product baskets, geographic regions) and accelerate report creation.
7) Non-empty behavior and empty cell handling
Control how empty cells and non-empty behaviors are treated for measures and calculated members to ensure accurate filtering and display.
- Benefit: Prevent misleading results caused by sparse cube data, and ensure totals behave as expected.
8) Integration with Excel features
The add-in is designed to work within Excel, preserving PivotTable interactions, slicers, and refresh behavior while augmenting functionality.
- Benefit: Low friction adoption—users keep familiar workflows while gaining new capabilities.
Practical workflows and examples
- Ad-hoc profitability analysis: Use metadata browsing to find product attributes, build a named set of high-priority SKUs, add a calculated member for profit margin, and filter to top performers in a few clicks.
- Rapid troubleshooting: When a KPI total looks wrong, export the MDX, run it against the cube to verify, and inspect member properties to find mismatched keys or unexpected attribute values.
- Report standardization: Create named sets for fiscal periods (YTD, QTD), share them with colleagues, and ensure all reports use consistent period definitions.
Tips for effective use
- Learn basic MDX: You don’t need to be an MDX expert, but basic knowledge (calculated members, named sets, common functions) makes the add-in far more powerful.
- Use non-empty filters carefully: Aggressive non-empty pruning can hide members you need; test filters with and without non-empty behavior.
- Save reusable named sets: Capture commonly used member groups to reduce errors and speed report building.
- Keep workbook performance in mind: Complex calculated members and large named sets can slow Pivot refreshes; test performance incrementally.
Limitations and considerations
- MDX-based only: The add-in targets OLAP data sources that expose MDX (multidimensional and some tabular models). It won’t add the same features to regular Excel tables or some newer Power BI sources that use DAX without MDX compatibility.
- Performance: Complex MDX can be heavy on the server; optimization and testing are important.
- Compatibility: Ensure your Excel version and Analysis Services/Power Pivot setup are supported by the specific release of OLAP PivotTable Extensions.
Conclusion
OLAP PivotTable Extensions fills practical gaps in Excel’s OLAP support by exposing MDX, enabling advanced member selection, simplifying calculated members and named sets, and improving metadata visibility. For analysts working with multidimensional data, it accelerates common tasks, reduces friction when building complex views, and empowers users to create more accurate, repeatable reports without changing server-side artifacts.
If you want, I can: provide sample MDX snippets for common calculations (running totals, year-over-year growth), suggest a learning path for MDX basics tailored to PivotTable Extensions, or draft step-by-step instructions for a specific workflow you use.
Leave a Reply