Real-World Scenarios

You are a data professional. An insurance company has an issue: amount has jumped and managers do not know which region is causing it. As a Data Analyst, you are tasked to solve it.

You are a data professional. A river protection agency has an issue: the board wants one page of KPIs for water_tests every month. As a BI Analyst, you are tasked to solve it.

You are a data professional. A national game reserve has an issue: the animal_counts export has blank and duplicated rows, so reports disagree. As a Reporting Analyst, you are tasked to solve it.

You are a data professional. A public clinic group has an issue: leaders want to know what percentage each ward contributes. As a Data Analyst, you are tasked to solve it.

You are a data professional. A clothing retailer has an issue: a manager says the items values are "all over the place". As a Insights Analyst, you are tasked to solve it.

You are a data professional. A building contractor has an issue: each record should stay under a target of 6 workers. As a Data Analyst, you are tasked to solve it.

You are a data professional. A packaging factory has an issue: the team wants a league table of every line. As a Commercial Analyst, you are tasked to solve it.

You are a data professional. A water pumping utility has an issue: management asks whether vibration is rising or falling. As a Data Analyst, you are tasked to solve it.

You are a data professional. A city bus operator has an issue: staff need a two-chart dashboard image for an email. As a Reporting Analyst, you are tasked to solve it.

You are a data professional. A renewable power producer has an issue: the director wants one clear recommendation from the power_readings data. As a Data Analyst, you are tasked to solve it.

You are a data professional. A community bank has an issue: managers want amount per region in one small table. As a Data Analyst, you are tasked to solve it.

You are a data professional. A coastal clean-up charity has an issue: leaders only have time to read about the top 2 records. As a Data Analyst, you are tasked to solve it.

You are a data professional. A marine turtle project has an issue: staff argue about what a "normal" seen is. As a BI Analyst, you are tasked to solve it.

You are a data professional. A children's hospital has an issue: the Kids manager only wants their own numbers. As a Data Analyst, you are tasked to solve it.

You are a data professional. An online grocery shop has an issue: a poster needs one simple picture of items by store. As a Reporting Analyst, you are tasked to solve it.

You are a data professional. A road building company has an issue: nobody knows how many records each site has. As a Data Analyst, you are tasked to solve it.

You are a data professional. A bakery production plant has an issue: staff want each units labelled Low, Medium or High. As a Data Analyst, you are tasked to solve it.

You are a data professional. A bridge inspection firm has an issue: a new manager wants a quick feel for the pump_checks numbers. As a Insights Analyst, you are tasked to solve it.

You are a data professional. A delivery van fleet has an issue: the finance team wants the bus_trips data as a file. As a Data Analyst, you are tasked to solve it.

You are a data professional. A solar farm operator has an issue: leaders want to see each plant's slice of the whole. As a Data Analyst, you are tasked to solve it.

You are a data professional. A community bank has an issue: the board asks for the total amount across all regions. As a Data Analyst, you are tasked to solve it.

You are a data professional. A coastal clean-up charity has an issue: managers want to compare every river side by side. As a Data Analyst, you are tasked to solve it.

You are a data professional. A marine turtle project has an issue: the Rhino team only wants its own records. As a BI Analyst, you are tasked to solve it.

You are a data professional. A children's hospital has an issue: staff argue about what a normal wait_minutes looks like. As a Reporting Analyst, you are tasked to solve it.

You are a data professional. An online grocery shop has an issue: leaders want the biggest items records first. As a Data Analyst, you are tasked to solve it.

You are a data professional. A road building company has an issue: the director has time for only the top 2 records. As a Data Analyst, you are tasked to solve it.

You are a data professional. A bakery production plant has an issue: nobody knows how many records each line holds. As a Reporting Analyst, you are tasked to solve it.

You are a data professional. A bridge inspection firm has an issue: any vibration above 5 needs urgent review. As a Data Analyst, you are tasked to solve it.

You are a data professional. A delivery van fleet has an issue: the report needs the best and worst delay_minutes in one line. As a BI Analyst, you are tasked to solve it.

You are a data professional. A solar farm operator has an issue: staff cannot remember the exact spelling of a plant. As a Data Analyst, you are tasked to solve it.

You are a data professional. An insurance company has an issue: planners need to forecast next period's amount. As a Data Scientist, you are tasked to solve it.

You are a data professional. A river protection agency has an issue: some water_tests records look suspicious. As a Data Scientist, you are tasked to solve it.

You are a data professional. A national game reserve has an issue: staff want to know early which records will be "high". As a Data Scientist, you are tasked to solve it.

You are a data professional. A public clinic group has an issue: the team wants to group similar wards for different treatment. As a Data Scientist, you are tasked to solve it.

You are a data professional. A clothing retailer has an issue: someone claims items grows over time. As a Data Scientist, you are tasked to solve it.

You are a data professional. A building contractor has an issue: a vendor model claims 90% accuracy on site_jobs. As a Data Scientist, you are tasked to solve it.

You are a data professional. A packaging factory has an issue: the model cannot read the line words. As a Data Scientist, you are tasked to solve it.

You are a data professional. A water pumping utility has an issue: a manager asks the chance a random record is from PumpA. As a Data Scientist, you are tasked to solve it.

You are a data professional. A city bus operator has an issue: a single tree gave unstable answers for bus_trips. As a Data Scientist, you are tasked to solve it.

You are a data professional. A renewable power producer has an issue: executives need predictions explained in plain words. As a Data Scientist, you are tasked to solve it.

You are a data professional. A community bank has an issue: the payments model was tested on the data it learned from. As a Data Scientist, you are tasked to solve it.

You are a data professional. A coastal clean-up charity has an issue: ph values are too big for the model to compare fairly. As a Data Scientist, you are tasked to solve it.

You are a data professional. A marine turtle project has an issue: staff need a yes/no prediction for each animal_counts record. As a Data Scientist, you are tasked to solve it.

You are a data professional. A children's hospital has an issue: the Healthcare team wants to see exactly where the model is wrong. As a Data Scientist, you are tasked to solve it.

You are a data professional. An online grocery shop has an issue: some items values are blank and break the model. As a Data Scientist, you are tasked to solve it.

You are a data professional. A road building company has an issue: staff want to label a new site_jobs record by its closest neighbours. As a Data Scientist, you are tasked to solve it.

You are a data professional. A bakery production plant has an issue: a manager says two halves of machine_runs are different. As a Data Scientist, you are tasked to solve it.

You are a data professional. A bridge inspection firm has an issue: leaders ask which input matters most for vibration. As a Data Scientist, you are tasked to solve it.

You are a data professional. A delivery van fleet has an issue: nobody knows how delay_minutes values are spread out. As a Data Scientist, you are tasked to solve it.

You are a data professional. A solar farm operator has an issue: someone thinks later power_readings records have bigger megawatts. As a Data Scientist, you are tasked to solve it.