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From the time I saw Data Geek challenge,  I was thinking to participate into it with my data story and today is the time I am going to share it with you.


I choose Aadhaar Dataset which is available at Aadhaar public data portal at https://data.uidai.gov.in/uiddatacatalog/dataCatalogHome.do


Reason I selected this dataset is I was looking for data which will let me do geographical analysis 🙂 as well as I want to get answers to below few questions such as, 

  • Which states are generating more number of aadhaar cards?
  • Which Enrolment agencies are doing better?
  • What is the number of residents providing email, mobile number?
  • Top districts where enrolment numbers are high?
  • Aadhaar generated by States and gender?
  • Top districts in Maharashtra state where enrolments is high? and etc.etc…


To get answers, First I downloaded “Enrolment Processed in Detail” data set from https://data.uidai.gov.in/uiddatacatalog/getDatsetInfo.do?dataset=UIDAI-ENR-DETAIL

Here I provided date range from 1st August till 15th August and selected dataset with maximum number of records which I got for 6th August with around 1 million records!


After importing this data, I selected option to create geography hierarchy where I found out that at state and district level, names resolution did not found proper propositions and hence I cleaned data at least for Maharashtra State.  After data cleaning activity, I re imported CSV file as below.

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With below screen, it is clear that number of residents providing mobile number is quite high than those providing email id.

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Maharashtra state is having maximum number of residents providing email during aadhaar registration.

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But with the combination of enrolment agency, registrar and state, Karnataka is having maximum number of residents providing email.

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With below screenshot, we can easily identify top districts where enrolment number is high. Warangal is topmost district followed by Pune. for this view, Lumira took lots of time. I guess this is because of big number of rows.

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Within Maharashtra state, Pune is at the top of the list!

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Now if we go one level down i.e. at district level, In the Pune district, Pune City sub-division is having maximum number of residents which provides email. again as Pune city is having maximum number of residents, I am not surprised by this outcome.

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In Maharashtra state, Mumbai is the district where maximum number of residents are providing email.

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Please note – This analysis is based on data generated on 6th August 2013.

I also tried my hands on with SAP Predictive Analysis and was curious to know the difference between SAP Lumira and SAP Predictive Analysis. and below is what I can say about it.

SAP Lumira = Prepare + Share

SAP Predictive Analysis = Prepare + Predict + Share

And hence SAP Predictive Analysis = SAP Lumira + Predict 😉

I hope you enjoyed reading this blog. Please feel free to share your comments! Have a great day and Happy Analyzing 🙂 🙂


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7 Comments

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  1. Jitendra Kansal

    SAP Lumira = Prepare + Share

    SAP Predictive Analysis = Prepare + Predict + Share

    And hence SAP Predictive Analysis = SAP Lumira + Predict 😉

    nice !!!

    I feel you could share some points about Aadhar card.

    Rgrds,

    Jitendra

    (0) 

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