The video tutorial guides students through an assignment involving Big Query. Students are instructed to access the Chicago Taxi trips dataset, run a query to select specific data, and render this data in an HTML page. The tutorial emphasizes using a unique key for caching data in memcache. Students are encouraged to complete the assignment using their knowledge, with a solution available if needed.

What is the first step in accessing the Chicago Taxi trips dataset?

• Type 'Chicago Taxi trips' in the search bar

• Scroll down to find the dataset

• Type 'Big Query' in the search bar

• Directly access the taxi_trips table

Which table should be queried to retrieve trip data?

• taxi_data

• trip_data

• taxi_trips

• Chicago_trips

What columns are required to be rendered in the HTML page?

• trip seconds, trip cost, and timestamp

• trip miles, trip duration, and timestamp

• trip miles, trip cost, and timestamp

• trip miles, trip seconds, and timestamp

What should be used as a key for memcache?

• Timestamp

• Post ID

• Unique key

• Trip ID

Where can you find the solution code for the assignment?

• Inside the Python memcache folder

• In the video tutorial

• In the course textbook

• In the Big Query documentation