October 2022

Win a $400 Amazon Voucher from our sponsors Pomerol, Qlik, Astrato, & NovyPro, a DATAcated Circle membership worth $297 and 2 data books from our sponsors Packt!

A winning entry will be chosen based on best visualization and successfully following the entry rules – winning a $400 Amazon voucher code courtesy of Pomerol Partners, Qlik, Astrato, DATAcated & NovyPro, a DATAcated circle membership worth $297 and 2 eBooks from packt!

The top 5 entries will also receive 2 data eBooks from our sponsors Packt Plus, all entries submitted using Astrato will be entered into a special mini-competition. And the winning entry will receive an exclusive Astrato goodie bag!

We also now have amazing badges to be won!

How to submit your entry:

  • Follow Pomerol Partners on LinkedIn (it’s OK if you already follow Pomerol Partners)​
  • Share a LinkedIn post on your profile that contains both a direct @ mention to @Pomerol Partners, @Qlik, @Astrato Analytics, @NovyPro, @DATAcated and the hashtag #dataDNA
  • In your post, share an image of your visualization or dashboard (remember, it must be a single image)
  • Tag, mention, and invite 5 connections to view your post or play along (optional)

How to Create an Astrato Entry:

Want to try your hand at Astrato? The October DataDNA Challenge is the perfect dataset for fun, fast, and creative exploration!

This month, you’ll find the data available in the Astrato DemoData Connection. Follow the steps below to get started:

  • Log in to Astrato
  • If this is your first time logging in, make sure that you import the demo workbooks by clicking on the demo workbook card from the workbook section to establish a connection to the demo data!
  • Click “Create Workbook” at the top right corner of your workspace.
  • On the next screen, select “New Data View”.
  • Select the Demodata Snowflake connection from the Data Source list. This will open the Data View Editor.
  • Select the Titanic Table and begin to create your masterpiece!

Titanic Dataset

  • This month we are analyzing Titanic data!
  • Can you identify which class was most likely to survive?
  • This is a themed dataset and may not be accurate against actual events of the Titanic disaster.

Credit Kaggle

DataDNA Dataset Challenge October 2022

Welcome to the October 2022 DataDNA Dataset Challenge!

This month we will be visualizing the Titanic Dataset!

Please read the challenge terms and conditions before participating.


Data Dictionary

Column NameDescription
PassengerIDPassenger number
Survived0 = Dead, 1 = Alive
Pclass1 = First Class, 2 = Second Class, 3 = Third Class
NameName of Passenger
SexGender of Passenger
AgeAge of Passenger
SibSPNumber of Siblings
TicketTicket Number
FareFare Paid for Ticket
CabinCabin number of Room
EmbarkedBoarded the ship at C = Cherbourg, Q = Queenstown, S = Southampton

Ready to kick start your data analytics journey?