We are excited to launch our Data Viz Challenge for 2022! This is the perfect opportunity to show off your data skills while working with others in the data community and building your portfolio.

For this edition of the Data Viz Challenge, we will be using newly released survey data from Statistics Canada on the Canadian Survey on Business Conditions. The dataset for the challenge can be found via this link.

This contest is open to all skill levels and you can use any BI tool you are comfortable with. You will get a chance to present your visualization at one of our meet-ups and compete for awesome prizes!

More Details Here 👇

Canadian Survey on Business Conditions Data Viz Challenge

The Canadian Survey on Business Conditions data is sourced from Statistics Canada and can be accessed via the following link: https://www150.statcan.gc.ca/n1/en/type/data?sourcecode=5318

Since the dataset is wide reaching and comprehensive, we recommend you focus your visualization on a specific theme/topic

Suggested topics include:

• Impact of COVID-19 on businesses
• Business expectation, conditions and obstacles faced by rural businesses
• Business expectation, conditions and obstacles faced by small businesses
• Business expectation, conditions and obstacles faced by businesses owned by diversity groups (for example: women, First Nations, Metis, visible minorities, LGBTQ, persons with disability etc.)

Each data file corresponds to data extracted for Saskatchewan and all of Canada. The file naming convention corresponds to the table name from Statistics Canada. As an example, data file named “3310046801_databaseLoadingData.csv” corresponds to Table: 33-10-0468-01 (Business or organization expectations over the next three months, first quarter of 2022) on the Statistics Canada website.

Meta data for each data file can be extracted by:

• Clicking on the data table
• Clicking the “Download Options” button
• Clicking the “Download cuba metadata information” file

If you have questions, shoot Arnav an email 

Data For Good is a collective of do gooders, who want to use their powers for good, and not evil, to help make our communities better through data.

We help other not for profit, and non-governmental, organizations harness the power of their data to make more informed and better decisions in their quest to make their communities flourish.

Who we are

The team in Regina is led by Kevin Hayes and a host of other volunteers who are committed to making an impact through data in Regina.

We are a community of data professionals who provide pro-bono data analytics services to registered charities, non governmental and not for profit organizations.

Our aim is to unlock insights which may be lurking within your data assets that can support your strategic planning activities and improve your operational efficiency.

How we can help

Many non-profit organizations collect data from a variety of sources during the normal course of operations, including details on funding, campaigns, resource allocation and the clients they serve. Over time all such systems accrue vast amounts of data that can support the organization’s strategic decision making.

In-house data can be combined with external data from open sources such as census and economic data from government repositories like Statistics Canada. On past engagements, clients have been interested in, for example,

• understanding how to better target their donor base
• analysing their volunteers and where best to engage them
• optimising the locations of food banks

The output of our analysis is made up primarily of different types of visualisations. We use several types of tools ranging from Excel and Tableau to create charts and dashboards, to more sophisticated statistical software packages like R and Python for regression and time series analysis.

Data for Good can assist in a variety of ways depending on your needs. The engagement begins with a consultation with the Data Ambassador (the contact for the project) in order to assess how we can best add value and the feasibility of the engagement.

It is worth noting that you do not need to have any specific business questions in mind at the time of the engagement. Data for Good is often brought in for an undirected general exploration of trends and other interesting correlations that exist within the data. Usually this will then guide further analysis by prompting interest in drilling down deeper into specific subjects. Regular checkpoints with the client ensure that the ‘wheat’ remains separated from the ‘chaff’.