Data Analysis Made Easy

Ariel Sepulveda

Pronto Analytics Inc.

BEST Viewpoints 9

These are just a set of screenshots of the application sections.  I will submit a detailed notebook later on.  Click here to watch screencast.

Introduction

BEST Viewpoints is an application that combines in Mathematica data manipulation and analysis capabilities commonly used in spreadsheets, database languages, and other data analysis applications.  Spreadsheet users and analysts in general will find in BEST Viewpoints a good complement to simplify and automate common data manipulation and analysis tasks.

Summarizing data using bar charts, Pareto analysis, box plots, bubble charts or line plots are some of the basic features users will be able to quickly access and use efficiently.  Additionally the application provides data exploration and statistical tools like summary statistics, histograms, scatter plots, confidence intervals, hypothesis testing, statistical control charts and process capability analysis.

More advanced capabilities of BEST Viewpoints can be used for association analysis like market basket analysis and for calculating and graphically representing retail analytics.  Additionally, basic text mining capabilities like string pattern counting are also available for datasets that contain columns of text or strings.

Furthermore, users are empowered by the full library of Mathematica functions to symbolically represent and perform calculations in datasets of multiple data types.  To enable communication with other systems and to enable the portability of results, many data formats are available for importing data and exporting results.  Additionally, a graphical user interface is provided to read data and create queries from databases without the need of typing SQL scripts.

Workflow

The software is designed for data importing, manipulation, and analysis by means of two main sections: 1. Data, for data importing and manipulation, and 2. Analysis for applying analysis methodologies and graphically representing information contained in the imported dataset.

The image below shows the application in its initial state.  Note the "Quick Start Guide" which should help the user quickly getting started using the application.

A quick description of the main navigation controls should help understand how the application is designed.  As shown in the image below the arrow wrapping the working section number is a menu with the available working options.  Note that there are three subsections in each of the main working modes.

These subsections can also be accessed by clicking on any of the circles at the right of the main section names (see images below).  Thus, there are indeed two ways to navigate the working sections; the menu with all the options which might be easier to understand, and the 'single-click circles' which might be preferred for a more efficient navigation.

The next paragraphs briefly describe the capabilities BEST Viewpoints provide in each of its main working sections.

1. Data

Section 1. Data provides a data importing and modification interface to prepare data for section 2. Analysis.  The main function of this section is simplifying the process of uploading and preparing data for analysis.  For this purpose the following external data sources are available: databases, files (spreadsheets, text files, csv files, etc.) user defined variables, and Mathematica scripts.

The image below shows section 1.1 Import displaying the sources available for data importing.  Note that the application will always charge a default dataset of sale transactions such that the user can quickly test the application in any of its sections.

Section 1.1 Import is where data is uploaded.  Some of the features of this section include the selection of spreadsheet tab names and the automatic dataset corner point identifications when the file is a spreadsheet.  Importing spreadsheet data in cross-tab format is also possible.  The image below shows some of the tools that become available when a spreadsheet file is selected.

To read data from a database a graphical user interface is provided to create queries without the need of typing SQL scripts.  The image below shows a simple example of the user interface provided for selecting tables from a database and creating queries.  The table Sales is selected and a simple query has been created and applied.  The yellow color is used to highlight the preview of results before formally applying the query and loading the resulting dataset.

The two data modification sections are named 1.2 Modify 1.1, and 1.3 Modify 1.1 or 1.2.  These sections are useful for data transformation visualization and manipulation.  In these sections the user can calculate new fields, transform existing fields, summarize data, query data, and sort by one or more columns.  All data transformation procedures defined in these sections can be saved as Analysis Templates for future use in different datasets that have the same column headers.

The image below shows Modify 1.1 in the Transform module.  Note that a dummy data transformation was applied to MonthNo.

2. Analysis

Section 2. Analysis contains three data analysis interfaces named 2.1 Summarize,  2.2 Explore, and 2.3. Associate.  These modules are designed to facilitate the application of many data analysis methodologies visualizing and extracting the information contained in one or more data columns (or fields) grouping by one or more categorical fields.

Section  2.1 Summarize is designed to summarize data in form of Pivot Tables or Cross Tabs of any of the following formats: Bar Charts, Pie Charts, Pareto Plots, Box Plots, Confidence Intervals and Line Plots.  The image below shows a simple example of this section in use: calculating Total Sales grouped by CountryID and then by Product.

Section 2.2 Explore facilitates the creation of Summary Statistics, Histograms, Scatter Plots, Bubble Charts, Statistical Control Charts, Capability Analysis, Hypothesis Tests (including goodness of fit tests), Box Plots, Distribution Charts, Mean Confidence Intervals, Standard Deviation Confidence Intervals, 3D Plots, Line Plots, Quantile Plots, and Probability Plots among other.  The image below shows a simple example of this section in use: Bundle of box plots and line plots of Sales by CountryID.

Finally, section 2.3. Associate is for identifying associations between one or more analysis variables.  This way of analyzing and portraying the information in data is sometimes referred as Market Basket Analysis , Affinity Analysis or Association Analysis.  Additionally, this section provides an easy way of performing Retail Analytics with calculations like Penetration, Footprint, Average Transaction Revenue, and Sole Purchase Count, among other.  Finally, basket statistics like Total Baskets, Min, Max, and Mean Basket Size, are also calculated.  The image below shows a simple example of this section in use: count of strongest associations of products sold together in purchase orders (represented by OrderID).

Additionally, a well documented library of functions for data processing and analysis is provided for Mathematica users.  This Mathematica package named MXL Plus (data Miners eXtensible Library) is intended to be used by programmers who would not only use this program for analyzing data, but that would also like to create Mathematica scripts using some of the functions used by BEST Viewpoints.

Startup

After installing BEST Viewpoints the commands below (Needs["BESTViewpoints"] and BESTViewpoints[]) are used to start the application and creating the directory BESTViewpoints in your $HomeDirectory.  This directory is used to store datasets and other information generated while using BESTViewpoints.  Other directories inside BESTViewpoints will also be created.  Thus, administrator privileges in the computer running BESTViewpoints may be needed the first time the program is run.

Needs["BESTViewpoints`"];
BESTViewpoints[]

The following sections briefly describe the use of BEST Viewpoints for data importing, manipulation and analysis.  Note that BEST Viewpoints is a user interface created to simplify the use of Mathematica for data analysis, thus, in Mathematica users have other complementary capabilities for data analysis.

Data

Importing data from spreadsheets

Importing data from databases

Calculating new fields

Analysis

Section 2.1 Summarize

Section 2.2 Explore

Section 2.3 Relate