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Former Member

This Blog contains a report on how Indian Postal Data was used to explore the Visual functionality of SAP Lumira. The data source for this project is from the Government of India Portal for Public Data Sets, and the Trademark names used in this blog are the copyrights of their respective owners,  I personally do not own any responsibility for any of the Data or Information used here.

This is an attempt to explore the functionality available in SAP Lumira, as an Evaluation Product.

Before we look into how Lumira can be used as an analysis tool, let us look into some facts about the data that we are going to use for this purpose and few common facts about Visual Analysis when compared to other type of data analysis.


          The Indian Postal Service comes under the Department of Posts, which is part of the Ministry of Communication and Information Technology, Govt. of India. Let’s have a quick view of facts that would make us more interesting on the data that we are going to work on.

  • Founded on 1st April, 1774.

  • Posts and the British Raj (1858–1947),

  • By 1861, there were 889 post offices handling nearly 43 million letters and over 4.5 million newspapers annually.

  • The world's first official airmail flight took place in India on 18 February 1911, a journey of 18 kilometers (11 mi) lasting 27 minutes.

  • Henri Pequet, a French pilot, carried about 15 kilograms (33 lb) of mail (approximately 6,000 letters and cards) across the Ganges from Allahabad to Naini; included in the airmail was a letter to King George V of the United Kingdom.

  • The first adhesive postage stamps in Asia were issued in the Indian district of Scinde in July 1852 by Bartle Frere, chief commissioner of the region, The Scinde stamps became known as ”ScindeDawks”.

  • 15th August 1947 - First slogan of Independent India "JAI HIND".

  • 1948 August 15, Gandhi Ji - The first Indian to be on stamps of India.

  • As of 31 March 2011 (2011 -03-31), the Indian Postal Service had 1,54,866 post offices, of which 1,39,040 (89.78 percent) were in rural areas and 15,826 (10.22 percent) in urban areas.

  • The highest post office in the world is in Hikkim, Himachal Pradesh, India at a height of 15,500 ft (4,700 m) (postal code 172114).

  • India Post inaugurated a floating post office in August 2011 at Dal Lake in Srinagar, Kashmir.

  • In addition to the 22 circles, there is a base circle to provide postal services to the Armed Forces of India. The base circle is headed by a Director General, Army Postal Services (with a rank of major general).



  • Design, printing and distribution of special or commemorative postage stamps.

  • Design, printing and distribution of definitive postage stamps and items of postal stationery (such as envelopes, inland-letter cards, postcards, aerograms and registered covers).

  • Promotion of philately, conduct of philatelic examinations at the national level, participation in international exhibitions and monitoring exhibitions at the state, regional and district levels.

  • Maintenance of the National Philatelic Museum (Dak bhawan).

          Hope these facts en-kindle us to explore the data sets with Lumira.

          The following snapshots give a representation of data, with the fields used and the procedure and the result that can be interpreted from the visual.


Source: Data Portal of India-

Industry: Post and Courier

There are two .CSV files that provide the data for our analysis,

1 – A file containing all the PINCODE details, with the respective Post Offices and the delivery types, including their location details. This file counts to a total of 154,725 records.

2 – A file with the details of Philatelic bureau in each state of the country.

We use these two files to explore the Visual Functionality of SAP Lumira.

Fig 1: Attributes from the .CSV file.


Head office:

A head office is the chief of a group of offices consisting of it self and a number of small offices called sub and branch offices which have been placed under its accounts jurisdiction. It is the central office for itself and for all the sub branch offices within the group and monetary transactions of the latter offices are incorporated in its accounts.

Sub offices:

A sub office is a post office subordinate to and in account with a head office. It’s headed by Sub post master

Branch office:

A branch post office is a post office which is lower in rank than sub office.It is headed by Branch Post master.

Pie-Chart Showing the Percentage of total number of post offices with respect to the office types

(Branch Office : BO, Head Office : HO, Sub Office : SO)

Fig 2 : Pie Chart with Office Types

Tree Map with top 10 States with Type of Delivery Service available.

     The following visual has the tree map with the top 10 states if India with the highest number of Post offices, differentiated by the type of service available (Delivery & Non-Delivery).

Fig 3: Tree Map Displaying no:of Post offices in ANDHRA PRADESH with Non-Delivery Status.

Fig 4: Tree Map Displaying no:of Post offices in ANDHRA PRADESH with Delivery Status.

Area Chart showing the top 10 states with the number of post offices and the office types with their respective counts.

Fig 5: Visual showing KARNATAKA with 1688 Sub offices.

Fig 6: Visual showing ANDHRA PRADESH with 13721 Branch offices.

Tag Cloud depicting the State name with respect to the number of Post Offices as the weight.

Fig 7: Tag Cloud for the maximum value

The above Visual gives us the detail that the state of UTTAR PRADESH has the maximum number of Postal Offices, having a record of 17,643 offices under it.

Fig 8: Tag Cloud for the minimum value

LAKSHADWEEP records the lowest number of Post offices counting to only 10 post offices in middle of the Ocean.

The weight for this Tag cloud is the number of Post offices, with respect to the State name. The visual can be varied with respect to the attribute used as the Word weight and Word dimension.

Column Chart Showing the Top 20 Indian States with the peak number of post offices.

Fig 9: GUJARAT showing the total count of 8934.

The chart can be varied by changing the Rank Value (Which is currently 20). This can give a better view of the data within the required range in real time scenarios.

Building Measures and Dimensions

We can build a measure from the fields available in the data file. Measures can be either built from the DATA view or from the VISUALIZE view. In additional to that we can set RANK values and FILTERS in the data, that we can opt to use in the visual.

Fig 10: Building Measure from the “pincode” field.

     SAP Lumira has the potential to generate Geographic dimension from the parameters like, Region Name, City name, country name etc. This can also be facilitated from the Latitude and Longitude details.

     In our project we are building the geographic dimensions from the Region names. This automatically maps the data to the MAP. 

Fig 11: Building Geography dimension from Region Names.

Top 10 States with Peak Number of Philatelic Bureau in India.

Fig 12: Tree map showing the Top 10 states with the number of Philatelic Bureau.

While pointing to the respective node the data is displayed with all the respective data.

Geographic Chart

With the generated geographic dimensions the geographic chart was built. SAP Lumira automatically maps the data to the MAP with Region name. The map shows the weight of Philatelic Bureau in each state.

                We can restrict the data with filters to map only the required fields, and the required range of values. This is very handy when generating demographic reports, the gives us a quick glimpse of the analysis.

Fig 13: Weight of Philatelic Bureau demographic wise.

Fig 14: Report showing the mapping of South Region of India.

Donut Chart

The following Donut Chart shows the distribution of Philatelic Bureau of each state, the chart visualizes the percentage of the bureau and displays it accordingly.

This kind of visual can be used in case of contribution from each attributes in the data.

Fig 15: Donut chart with data sorted with state name and Bureau count.

The above visual shows GOA with 1.54% of the total Philatelic Bureau in India.

Manipulation of data source

Change data source :

With the Change button in the Top Right corner, we can change the data source that we have already uploaded into the Lumira document.

Fig 16: Selecting the data source.

Fig 17: After the source changed from Philatelic Information to General Postal Information.

Refreshing data in the document:

            The data can be refreshed, this ensures that the visual is updated with the  current data, this is a very handy feature when we analyze lie data, especially from Production systems.

Fig 18: Refreshing the document data

Fig 19:  Refreshing the 154,725 records available in the file.

Here is the Video depicting the entire process.

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