December 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 December 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:

To Connect to Sample Sales Data

  • 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 “New 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 CONSUMER_TECH_SALES Data Table and begin to create your masterpiece!

Product Sales Dataset

Welcome to the DataDNA December Product Sales Dataset Challenge!

Credit: Kaggle


Q: What was the best Year for sales? How much was earned that Year?

Q: What was the best month for sales? How much was earned that month?

Q: What City had the highest number of sales?

Q: What time should we display adverstisement to maximize likelihood of customer’s buying product?

Q: What products are most often sold together?

Q: What product sold the most? Why do you think it sold the most?

Dataset Details

Sales analytics is the practice of generating insights from sales data, trends, and metrics to set targets and forecast future sales performance. Sales analysis is mining your data to evaluate the performance of your sales team against its goals. It provides insights about the top performing and underperforming products/services, the problems in selling and market opportunities, sales forecasting, and sales activities that generate revenue.

Data Dictionary

  • Order ID – An Order ID is the number system that Amazon uses exclusively to keep track of orders. Each order receives its own Order ID that will not be duplicated. This number can be useful to the seller when attempting to find out certain details about an order such as shipment date or status.
  • Product – The product that have been sold.
  • Quantity Ordered – Ordered Quantity is the total item quantity ordered in the initial order (without any changes).
  • Price Each – The price of each products.
  • Order Date – This is the date the customer is requesting the order be shipped.
  • Purchase Address – The purchase order is prepared by the buyer, often through a purchasing department. The purchase order, or PO, usually includes a PO number, which is useful in matching shipments with purchases; a shipping date; billing address; shipping address; and the request items, quantities and price.

DataDNA Dataset Challenge December 2022

Select “Get Data” below to download the dataset

Please read the challenge terms and conditions before participating.

Ready to kick start your data analytics journey?