NetCharts® Analytics
Add powerful analytics functionality to your dashboards and online reports in minutes!
The NetCharts Analytics library is designed for easy integration of analytics functions within the NetCharts Reporting Suite. It provides the ability for users to apply sophisticated data transformations to raw or minimally processed data. The resultant data can then be easily displayed in graphical or tabular formats.
Analytic packages are used to extract useful information from raw data by applying various algorithms to the original data set. For example, a grocery store manager could apply a Pareto function to raw register receipts to see a ranking of the most popular products in the store. Trend and forecasting lines can be applied to gauge future sales. Statistical Process Control (SPC) functions can determine if the store is meeting sales and/or quality expectations.
The NetCharts Analytics package is implemented in the NetCharts Reporting Suite as process modules. The process module interface allows data to be modified through one or more transformations. In NetCharts Designer, the process modules may be selected via the Functions tab on the NDX data editor. Any combination of functions can be chained together and mixed with other data processing routines to provide the information required. NetCharts Analytics transforms your raw data using such functions as Pareto analysis, trending, seasonality, regression, correlation, control charts and other statistical techniques that provide actionable information. Using standard NetCharts Designer features, you can customize the look of the chart and create pages for deployment.
NetCharts Analytics provides more than 50 different analytical functions in five categories: General, Statistics, Financial, Calculus, and Statistical Process Control. Each Analytic module has built-in a GUI and online help dialog; a 100-page companion document helps you get the most out of your data.
List of Functions
- General Purpose Functions
- Aggregate Column
- Grade Column
- Delete Column(s)
- Delete Row(s)
- Include Headers
- Count Group Names
- Sum Group Names
- Sort 1 Column
- Two Column Operation
Two Column Operation allows you to perform item-by-item addition, subtraction, multiplication or division with two columns of data of equal length and return the result in a column of the same length as the input columns.
- Statistical Functions
- Bin Data
- Univariate Metrics
- Histogram Distribution
- Pareto Analysis
- Normal Distribution
- Quantile
- Mode
This Pareto chart is based on a combo chart and shows the number
of occurrences and the cumulative effect each failed part has
on the total causes of computer failure. The 80/20 lines are also
plotted using notesets.
- Calculus Functions
- Area
- Differentiation
- Integration
- Curve Length
- Surface Metrics
- Regression
- Fourier
- Filter
- Track Order
- Interpolation
Regression functions are useful in statistical surveys, polling, or other situations where a finite set of samples is used to determine the characteristics of the overall data set.
- Financial Functions
- Moving Average
- Bollinger Bands
- Linear Regression
- Stochastic Oscillator
- Chaikin Oscillator
- Ultimate Oscillator
- Price Oscillator
The Price Oscillator is an indicator based on the difference between two moving averages over a short and a long period. It is expressed as either a percentage or in absolute terms. The short and long periods values can vary depending on user
preference. It is used for for predictive stock analysis.
- Statistical Process Control (SPC) Analytics
- SPC Attributes Chart – c
- SPC Attributes Chart – np
- SPC Attributes Chart - p
- SPC Attributes Chart - u
- SPC Variables Chart - EWMA
- SPC Variables Chart - Histogram
- SPC Variables Chart - Median-R
- SPC Variables Chart - Median-s
- SPC Variables Chart - Probability
- SPC Variables Chart - XBar-R
- SPC Variables Chart - XBar-s
The c chart is used to measure the number of defects for a
given item. It implies that each sample has an equal size.
