Introduction to FlexPivot
Business applications often need to organize large datasets, identify trends, and present summarized information in meaningful ways. FlexPivot provides interactive data analysis capabilities for grouping, filtering, summarizing, and visualizing data through pivot tables, charts, and reports.
FlexPivot supports multidimensional analysis similar to traditional OLAP tools while maintaining the lightweight architecture expected of WinForms applications. Drag-and-drop field arrangement, dynamic filtering, and customizable views simplify exploration of large datasets without modifying the underlying data source.
Built on C1DataEngine, FlexPivot efficiently processes large datasets using a high-performance, in-memory analytics engine that delivers fast aggregation and responsive analysis.
Analytical Processing
FlexPivot summarizes data by grouping records into dimensions such as product, region, or date. Instead of displaying individual records, each summarized value represents an aggregation of multiple records, making it easier to identify trends, compare results, and analyze business data.
Grouping criteria can be modified at run time to generate different summary views without changing the underlying data source.
Consider a scenario where a dataset must be analyzed to answer questions such as:
Date | Product | Region | Sales |
|---|---|---|---|
Oct 2015 | Product A | North | 12 |
Oct 2015 | Product B | North | 15 |
Oct 2015 | Product C | South | 4 |
Oct 2015 | Product A | South | 3 |
Nov 2015 | Product A | South | 6 |
Nov 2015 | Product C | North | 8 |
Nov 2015 | Product A | North | 10 |
Nov 2015 | Product B | North | 3 |
Are sales increasing or decreasing?
Which products contribute most to the company?
Which products are most popular in each region?
Answering these questions requires summarizing the dataset into aggregated views:
Sales by Date and by Product
Date | Product A | Product B | Product C | Total |
|---|---|---|---|---|
Oct 2007 | 15 | 15 | 4 | 34 |
Nov 2007 | 16 | 3 | 8 | 27 |
Total | 31 | 18 | 12 | 61 |
Sales by Product and by Region
Product | North | South | Total |
|---|---|---|---|
Product A | 22 | 9 | 31 |
Product B | 18 | 18 | |
Product C | 8 | 4 | 12 |
Total | 48 | 13 | 61 |
Each cell in a summary table represents values aggregated from multiple records in the original data source. Value fields are summarized (for example, total sales) and grouped by dimensions such as date, product, or region. Although spreadsheets can generate these summaries, the process becomes repetitive and difficult to maintain as the number of required views increases.
Interactive Analysis
FlexPivot supports interactive, ad-hoc data analysis through drag-and-drop field arrangement and filtering. Saved views automatically reflect changes to the underlying data source, making it easy to compare different perspectives and explore data relationships.
Reporting and Data Export
FlexPivot presents summarized data as interactive grids and charts for reporting and analysis. Reports support print preview, printing, and export to formats such as XLS, XLSX, and PDF.
Enhanced Data Engine
FlexPivot is powered by C1DataEngine, a lightweight analytics engine optimized for high-performance data processing. In-memory, column-oriented storage enables rapid aggregation and responsive analysis of large datasets.
C1DataEngine can also be used independently to build custom analytics solutions.
Note: All features of the data engine are supported on 64‑bit operating systems.
For programmatic scenarios, the C1FlexPivot class library provides APIs and extensions that allow applications to retrieve complex data and implement custom data analysis logic.