Quantopix Analytics System (QAS) is a platform for data analysis and for developing analytics apps. QAS connects to most of Enterprise Class SQL Database Managers and provides instant capabilities to build datasets and data groups from disjointed databases to prepare it for analysis. QAS provides a comprehensive and extensible set of statistical functions to instantly profile your data. It comes with advanced yet easy to invoke charting capabilities for interactively visualizing the data as well as generating static chart images. QAS comes with a built-in PHP and JavaScript App builder to help users extend the system functions and create custom applications for specific business needs. Rapid App Development QAS lets you build analysis Apps within minutes using a powerful set of APIs for data manipulation including time-series and text classifications. QAS includes a comprehensive list of math, statistics, and matrix manipulation functions for numeric analysis. The APIs include Multiple Linear Regression model generation, k-means clustering model generation, and a Predict API for both models.

1. Web Based Data Analysis Platform

2. Introduction
 A Platform for developing and deploying data analysis
and data mining applications in PHP
 Runs on a middle-tier server (between client and
database). First release will support Linux only.
 Multiuser Support (limited by server capacity only)
 First release will support Oracle, IBM DB2, MySQL,
and SQLite Database Managers. Other DBMS will be
added in future releases.
 Tested on Chrome, Firefox, Microsoft Internet
Explorer, and Mac Safari.

3. Database Connectivity
 Connects to any supported Database Managers using standard ‘connection
string’ format. Example: “Driver=Oracle; dbq=//ServerName:PortNNN/dbName;
UID=myuserid; PWD=mypassword; Description=Oracle Finance Dept Database ;
Database=Oracledb; Charset=AL32UTF8; “
 GUI Interfaces are also provided to build connection strings for supported
Database Managers. Example:

4. Data Objects and Abstraction
 QAS operates on Data Objects. A Data Object can be one of
three types:
1. Data Table (unfiltered Columns and Rows)
2. Dynamic Dataset (filtered by SQL Query)
3. Data Group (Multiple Dynamic Datasets assembled at runtime as
single object)
 QAS abstracts data types through mapping the Databases’
internal data types to one of the following basic types:
1. Text
2. Integer
3. Double
4. Date-Time
 A Data Group object is a collection of Dynamic Datasets from
different servers, different Database Managers, and different
tables in Real-Time.
 Certain proprietary Databases’ data types are not supported.
Example: BLOBs, Image Formats, etc.

5. Data Transfer
 Client-Server: Upload and Download data in
CSV/Zipped Format
 Server-Server: Transfers Data between Remote
Databases:
 Table to Table: Copy unfiltered Data Table from a
remote server to another
 Dataset to Table: Copy filtered dataset from a remote
server to a data table on another server
 Data Group to Table: Copy disjointed data sets into one
table on a remote server.

6. Data Tools
 Static and Interactive Charts
 Real-Time Data GUI Filtering
 Pre-defined statistical functions for instant analysis of
data columns. Text data tree hierarchal analysis.
 Data Randomization
 Sampling of Big-Data
 Real-Time Monitoring of Data

7. Custom Apps
 Basic PHP Language skill required.
 PHP and Javascript Syntax aware editor in the web
browser
 Instant App class template for PHP/Javascript
 Quick access to APIs Reference and Examples
 Single API for Data Query for all data objects:
dataGet (string $dsname, string $dataObjectType, string
$dataObjectName, [array $params = null])
 Statistics and Math Library
 Matrix manipulation Library
 Static (images) and Dynamic (interactive) Charting
APIs

8. Predictive Models
 Create Machine Learning Models : Auto-Generated
from Data (Unsupervised Learning):
 Multiple Variable Linear Regression Model
 K-Means Clustering Model
 Testing on Historical Data
 Prediction APIs

9. DEMO