Month: February 2014

Spotfire

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Spotfire is an easy-to-use, extensible and customizable visualization product – a more viable long-term alternative to Tableau. It has great GIS integration features and other APIs such as webplayer JS API allowing integration with GIS software and extensions such as OpenSpirit® for the energy sector. Further, it can be customized to build custom charts.

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Tableau: Table Calculations and Time Series Analysis

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Using Running total for duplicate SUM(Sales)

Table Calc and Time Series 1

We can see that Corporate is performing best

Table Calc and Time Series 2

Looking at the year on year percent difference in Sales

Table Calc and Time Series 3

Using bar charts to look at the quarterly performance. We can further drill down to more granular levels to check monthly and daily performances

Table Calc and Time Series 4

Looking at every day sales with “Running Sum” and “Moving Average” of Sales

Editing calculations at the date level with “Previous value” as 30 – for the 30 day moving average

Table Calc and Time Series 5

And using filters to see the data for particular years

Table Calc and Time Series 6

At Tableau Public: 

Time Line

Spotfire: Position Data on Map Charts with Geocoding or Coordinates

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There are two methods for our coordinates to appear on the map chart.

  1. Giving the coordinates using Longitude and Latitude values
  2. Using Geocoding

Using the Longitude and Latitude values for mapping

Map_Chart_Geocoding_1

Create a new page and add a new map chart

Map_Chart_Geocoding_2

For better presentation remove legends, filters and enable labels for cities (on click)

Map_Chart_Geocoding_3

2. Using Geocoding

Use the map layer setting in “My Data” to use geocoding data (a Spotfire feature) by “City”

Map_Chart_Geocoding_4

Automatic geocoding automatically adds three data columns from data table and uses US cities for mapping

Map_Chart_Geocoding_5

You can see the point by selecting them in marking mode

Map_Chart_Geocoding_6

FYI. TIBCO provides Geocoding data tables for different geographies

Map_Chart_Geocoding_7

The Data Landscape

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Storage and Processing:

  • Oracle
  • Microsoft SQL Server
  • IBM DB2
  • MySQL
  • PostgreSQL
  • NoSQL (MongoDB, Neo4j etc.)

Data Integration:

  • Informatica
  • Ab Initio
  • IBM InfoSphere DataStage
  • SAP BusinessObjects Data Services
  • Microsoft SSIS

Data Modeling:

  • CA ERwin Data Modeler
  • IBM InfoSphere Data Architect

Data warehousing and Business Intelligence:

  • Teradata
  • IBM Netezza
  • Oracle Exadata
  • Sybase IQ (SAP)

Business Intelligence and Reporting:

  • Microstrategy
  • IBM Cognos
  • SAP Business Objects
  • Microsoft SQL Server Reporting Services (SSRS)

Statistics:

  • SAS
  • R

Data Visualization:

  • Tableau
  • TIBCO Spotfire
  • QlikView
  • MicroStrategy Analytics Desktop

Cloud Solutions:

  • Amazon EC2
  • Google Big Query
  • Amazon  RDS

Big Data Frameworks:

  • Cloudera
  • Hortonworks
  • MapR
  • Pivotal

Big Data Analytics:

  • Aster data (Teradata)
  • Greenplum (EMC)
  • Vertica (HP)
  • Splunk
  • ParAccel
  • Infobright
  • Pentaho
  • Talend

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