Spotfire: Forecasting

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Importing data from a .dxp file

Spotfire_Forecasting_1

Drilling down on the data

Spotfire_Forecasting_2

Spotfire_Forecasting_3

Using filters to customize views for different categories

Spotfire_Forecasting_4

Using Forecast – Holt-Winters feature

Spotfire_Forecasting_5

Creating a forecasting model

Spotfire_Forecasting_6

Setting up confidence level: 0.99

Spotfire_Forecasting_7

Application using MongoDB with FreeMarker and Spark

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We will use the FreeMarker template engine to create the template mappings. Also, to keep the web application simple using Java code alone, Spark Web Application Framework is used.

Source (Git)

MongoDB Java Application

MongoDB Java Application 2

Querying the Mongodb and checking the value (mongo) which has been displayed using the Java application created.

> db.hello.findOne()

{ "_id" : ObjectId("52ce3490c85b1177b58ec638"), "name" : "mongo" }

Principal Component Analysis using R

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Principal Component Analysis (or PCA) is used as one of the initial step in a larger problem involving multivariate data analysis. It allows reducing the dimensionality of  a data set.