Picalo is a collaborative, open-source effort to produce a data analysis application suitable for auditors, fraud examiners, data miners, and other data analysts!
Example uses of Picalo:
* Analyzing financial data, employee records, and purchasing systems for errors and fraud
* Importing Excel, XML, EBCDIC, CSV, and TSV files into databases
* Interactively analyzing network events, web server logs, and system login records
* Importing email into relational or text-based databases
* Embedding controls and fraud testing routines into production systems
Who Is Picalo For?
1. Auditors and data analysts who have a bent towards information technology. These people want a powerful application they have explicit control over, and they are willing to brave the learning curve that warrants such power and control.
2. Less technical, "regular" data analysts who want to efficiently use the skills of #1.
3. Python-based analysts who want a GUI to run their routines within. For example, Picalo would make an excellent front end to the Numeric/Numarray Python libraries.
Here are some key features of "Picalo":
· Picalo is an open framework. Users can either use the built-in routines or write their own. Those who write their own can share their routines with others in the Picalo community. The goal is to create a large set of analysis routines that meet many different needs--on a scale that a single company could never do.
· The philosophy of Picalo is to bridge the gap between technically-oriented analysts and non-technical analysts. Data analysts who know basic scripting routines (for loops, for example), are more efficient and effective than those who do not--usually by several orders of magnitude. Picalo allows those who are technical to quickly write wizard-based analyses that others in an organization can use. See the user manual for more information about the plugin Detectlet architecture.
· Picalo includes advanced analysis routines not found in competing products. For example, it supports grouping by a number of days for analysis of labor and time card data. Picalo can also automatically group records to achieve a specified degree of smoothness in data.
· Picalo's language is based in Python, a powerful and easy-to-learn language. Rather than creating its own language (like competing packages do), Picalo rises on the shoulders of an extremely well-done language. You can download any of thousands of Python libraries from the Internet to use in your analyses.
· Picalo runs on Windows, Mac OS X, Linux, and many other systems. Most competing data analysis applications run only on Windows.