Vanilla Air – Tutorial Part 11 – Push to Vanilla

Dear Readers,

This part is not totally about Vanilla Air, but rather how to push Vanilla Air program to Vanilla Bi portal, to make those programs available for any BI users.

Vanilla Air – Tutorial Part 11 – Push to Vanilla

Here are the guidelines to maximize the features usage :

  • create your R program and test it.
  • make it dynamic (if it makes sense) using parameters
    • Declare parameters (with default value, parameter type)
    • insert parameters into your R program
  • turn your R program into a markdown one, to enjoy high professional output format
  • push your Markdown program to Vanilla

Air Push To Vanilla

  • Run your Markdown document from Vanilla portal, with support for parameters

Air Vanilla Portal Run

Now, everybody can develop its Analytic program and make it available in an instant on a portal, with dynamic content πŸ™‚

Have Fun !


Vanilla Air – Tutorial Part 10 – WorkFlows

Dear Readers,

Worflow, as we see it in dataming, has key objectives, such as process automation, orchestration of operation, batch comparison of algorithms performance, etc …
As a software editor, we have interesting experience with Workflow, starting with Vanilla biWorkflow, then writting Web WorkFlow interfaces for AklaBox, Vanilla Hub and now Vanilla Air.

Vanilla Air – Tutorial Part 10 – WorkFlows
WorkFlows interface is at same level as resources. By clicking on “+”, a new workflow will be created on the workplan

WorkFlow contains box of different type and different objectives :

Taking dataset into the WorkFlow, with Data Air script and DataSet selection


Data Manipulation, with recoding features


Runing standard algorithms on data


Building visualization on data


Workflows are easy to build, full featured using box that developer drag & drop on workplan, and easy to insert in a scheduler plan, to start automatically at regular intervals.

Have Fun !

Vanilla Air – Tutorial Part 9 – Parameters

Dear Readers,

A key subject in any program is to make the program dynamic, with easy to use prompt & filter, to enable dynamic selection by user at runtime.

Vanilla Air makes it easy to add and manage parameters, global parameters and parameters inside your R programs, with support for any type of parameters (data entry, list selection, multi selection …)

Vanilla Air – Tutorial Part 9 – Parameters

Parameters Management

The parameter interface, available from the left menu (below workspace and variables)Β allows developer to create and manage parameters that will be used in Markdown scripts, to make it interactives.

Air Parameter Interface

To create a parameter, please enter its name, definition, type and default value.

Parameter type is important, as it will impact on runtime interface behavior (list box, entry box …) .Parameters have also a default value (if available)

Air Parameter Interface Type

Parameters Usage

In workspace, for Markdown scripts, follow this syntax : Command {$P_nomduparametre} in scripts. Example :

Air Parameter WorkSpace Usage

The result is awesome ! It gives opportunity to end user for a vast range of simulation, when prompt for parameter’s value πŸ™‚

Have Fun !


Vanilla Air – Tutorial Part 8 – Markdown support

Dear Readers,

Doing the right data analysis is already a subject. But beeing able to share its result is also another key subject. There comes Markdown, a fantastic package to turn any R analysis (including its charts and graphs) into a Word, PDF or Html document.

Vanilla Air makes it easy to turn any of your R programs into a Markdown document, removing the burden to install Markdown package, lateX package, etc …

Vanilla Air – Tutorial Part 8 – Markdown support

  • Markdown is a R package installed by default
  • Markdown is like R script + output formatting
  • Markdown provide an easy way to create document in office format (html, pdf, word)
  • Markdown allows developer to create dynamic document


Example : Create a Markdown script for a project, using any dataset

  • Create project β€œCars1993”, using the dataset « car93Β Β» (or any sample dataset)
  • Add a script
  • Run the script from interface
  • Switch to MARKDOWN format using the specific icon



  • Use the predefined Markdown template

Air Markdown Template

  • Save it under another name
  • Modify the script : Add the R command to get dataset summary.

Air Markdown Summary

  • Run the script using the different format

Air down Run Format

  • View the results

Air Markdown View Format

Now any data Analyst can merge his R program result with his comment & explanation, making his work more easy to understand for the mass πŸ™‚

Have Fun !


Vanilla Air – Tutorial Part 7 – WorkSpace Features

Dear Readers,

Code generation is so helpful, especially when it comes to speed up development process, using best of the bread algorithms and data cleaning functions. But Vanilla Air is first a Web development studio, with a pleasant workspace and nice to have features for developer.

Vanilla Air – Tutorial Part 7 – WorkSpace Features

On the right side of the code area, you have a series of icons which provide access to R-Tools (ee previous post about R code generation), list of variables, history of command, Markdown wizard, undo/Redo and trash can management.

Air WorkSpace Icons

Please try those icons, make you own opinion about R-Tools, Markdown Wizard (see next post), etc .. . reading is something, trying is always a different challenge.


On the right side of the panel, you have thumbnails

  • R Log interface : the first thumbnail, which cannot be closed
  • Screens to display the code – R and Markdown code
  • Screens to display markdown result : PDF, Word and HTML rendering

Air WorkSpace Thumbnail

When you click on one of this thumbnail, the thumbnail content is displayed on the main workspace : either R program or markdown visualization.

Keeping the interface pleasant, with useful development features, is a key challenge for wide adoption.

Have Fun !


Vanilla Air – Tutorial Part 6 – R Code generation

Dear Readers,

This series of post is not about R programming. There are dozen of interesting tutorial on R available on the Web, and sometimes subject is not to know about R itself, but rather to understand what is data mining, how to understand a specific algorithm result such as a correlation or a K-Means.

Vanilla Air provides Code generation interface and wizard to create complex R portion of code, in 2 different parts of the platform

Vanilla Air – Tutorial Part 6 – R Code generation

From dataset interface, when you run the dataset exploration (see tutorial 4), you can have the mouse rolling over the graph to display a Code Generation Tooltip, that will push the code generated to create the chart inside your current program. Note : you need first to create a R program from the workspace interface


From the workspace interface, to work on dataset, we provide a series of tools to recode your data, that will generate the R code for you


A Web development studio for R that generate complex R code for you … amazing :)

Have Fun !


Vanilla Air – Tutorial Part 5 – Create a Project and a R program

Dear Readers,

Now that we have connected the data and start with initial exploration,let’s write some programs using R

Vanilla Air – Tutorial Part 5 – Create a Project and a R program

To create program, you need first to create a project : see below some information about icons, and let the different wizard guide you to get it done.

Air Project Program


A Web development studio for R … no head ache anymore with local workstation installation (JAVA, R, Package) … pretty cool πŸ™‚

Have Fun !


Vanilla Air – Tutorial Part 4 – DataSet exploration

Dear Readers,

Analysis, Predictive, Statistics, Data Mining … its all about data. So once we connect to data, we need to visualize it !:)

Vanilla Air provides interface to explore your dataset, whatever the initial format (Text files, Sql or NoSql database, R data package)

Vanilla Air – Tutorial Part 4 – DataSet exploration

Dataset exploration is available in the dataset panel, for every dataset you have defined.

Dataset exploration comes with predefined data exploration algorithms (see example below)

Air Dataset Visualization

We also provided a Web cube designer, and we exposed our WebAnalysis Cube explorer (also available in Vanilla)

Air Dataset Cube Visualization

If you don’t see it, it doesn’t exist ! (famous sentence in search engine domain) … which applies also to Data Mining & Analytics, where purpose is to make data speak about themselves !

Have Fun !


Vanilla Air – Tutorial Part 3 – DataSet definition

Dear Readers,

Analysis, Predictive, Statistics, Data Mining … its all about data. So we need data ! πŸ™‚

Vanilla Air provides an intuitive interface to connect to numerous data sources, from Excel/csv/xml to any Sql database and even Nosql database such as hbase, cassandra, mongodb …

Dataset interface has 2 major interests :

  • Define dataset, database connectivityΒ  -> bring data into the studio
  • Discover datas, play with data, eventually create code to manipulate data -> Understanding data content will allo better analysis

We make it easy for you to take any dataset on the platform and we provides also wizard to ease the initial dataset analysis.

Vanilla Air – Tutorial Part 3 – DataSet definition

Air Dataset Definition

You can see again an instant advantage : no head ache to connect to data, no head ache to browse your data and start with some interesting visualization

Have Fun !


Vanilla Air – Tutorial Part 2 – Package Installation

Dear Readers,

Vanilla Air runs R programs and is powered by the latest R engine available. Packages are the heart of R, like a collection of functions that make R richer and easier to use.

Vanilla Air provides an easy interface to manage packages

Vanilla Air – Tutorial Part 2 – Package Installation

Once connected toΒ Vanilla Air, Chose the “Configuration” menu, to display this interface below

Air Package Interface

From this interface, Administrator of the platform can perform operation like :

  • Select the CRAN mirror (just click on the map πŸ™‚ )
  • Install new R packages
  • Manage packages (validate, delete, update)
  • Access Package documentation : so useful !

You can see an instant advantage : no head ache with package installation on local workstation, and interface is very intuitive

Have Fun !