A restaurant is trying to develop more effective staffing strategies. A data analyst recognizes that there are significantly fewer customers earlier in the business day. They conclude that opening later would be more effective for staffing. What is this an example of?1 pointTailoring products to consumer buying habitsGathering customer opinions about business changesCreating efficiencies by analyzing customer foot trafficCreating more effective customer communication

A data analyst at a restaurant analyzes data about past sales and customer trends. They identify that the restaurant does not generate enough revenue to pay the staff whenever the restaurant is open before 4 p.m. The restaurant then adjusts their hours of operation to open at 4 p.m. What is this an example of?1 pointUsing intuition to create efficienciesSurvey data gatheringFollowing data ethicsData-driven decision-making

1.Question 1A restaurant is struggling to accurately staff for the different daily customer volumes. On some days, there are many servers and few customers. On other days, the restaurant is very busy and there are not enough servers and kitchen staff. What reports could a data analyst use to create more efficient staffing strategies? Select all that apply.1 pointAnalyze staffing levels for different daysReports using historical sales data to predict sales for the current day/dateReports of past and future reservations Reports of planned local events in the area of the restaurant2.Question 2A doctor’s office has discovered that patients are waiting 20 minutes longer for their appointments than in past years. A data analyst could help solve this problem by analyzing how many doctors and nurses are on staff at a given time compared to the number of patients with appointments.1 pointTrueFalse3.Question 3In data analytics, what is the term for an obstacle to be solved?1 pointIssueProblemSolutionQuestion4.Question 4Data analysts answer questions and solve problems. These are called business tasks. 1 pointTrueFalse5.Question 5Fill in the blank: Data-driven decision-making is described as using _____ to guide business strategy.1 pointintuitionvisualizationsfactsgut instinct6.Question 6At what point in the data analysis process should a data analyst consider fairness?1 pointWhen decisions are made based on the conclusionsWhen conclusions are presentedWhen data collection beginsWhen data is being organized for reporting7.Question 7When reviewing student data, a data analyst calculates course pass rates across the entire student population in two ways: once for students in academic support programs and once for students not utilizing academic support. What would be an example of a factor creating a bias in this example?1 pointPicking and choosing data from the data setConsidering systemic issues that may influence dataNot accounting for opportunities to utilize support programsEnsuring a large enough sample size is used

Question 9As a project manager, your team has been tasked to come up with a new service that increases customer engagement by 4% within one year. The team implements a new service, a website has gone live, catalogs have been printed and delivered, orders have been received, and customer engagement starts to go up. A year later, customer engagement has increased by 2%. What is this an example of?1 pointA successful implementation of OKRs A failed project launchA failed project landingA successful project landing

A restaurant hires a data analyst to determine the best times to have the restaurant open. Which of the following methods can the data analyst use to help build a better schedule for the restaurant? Select all that apply.1 pointAnalyze weekly weather dataAnalyze staffing levels for different daysExamine hourly customer numbersSurvey customers on their preferred times to dine

Question 2A restaurant has noticed many popular dishes are running out early in the day. How could a data analyst help identify a solution to this problem? Select all that apply.1 pointExamine overall daily sales of the restaurantAnalyze the number of staff on shift during peak timesAnalyze ordering patterns of those productsExamine the number of sales of those products