Hastrainedothers ondata toolsCan nameone datavisualisationtoolHas useddata to solvea businessproblemCan explaindatagovernanceCan explainwhat a datawarehouseisHas usedExcelpivottablesHascleanedmessydatasetsHaspresenteddata insightsto seniormanagementUses datato track apersonalgoalHas usedPython orR foranalysisKnowswhatmachinelearning isHas dealtwith dataqualityissuesHas usedTableauor PowerBIHas workedon a datamigrationprojectLoveslooking atdashboardsHas writtena dataanalysisreportHasautomateda dataprocessHasworkedwith SQLdatabasesHas createdcharts orgraphs for apresentationAttendedLCF 101Enjoysfindingpatternsin dataHas built adashboardfromscratchHascollaboratedacrossagencies ondataHas foundan outlierin dataHastrainedothers ondata toolsCan nameone datavisualisationtoolHas useddata to solvea businessproblemCan explaindatagovernanceCan explainwhat a datawarehouseisHas usedExcelpivottablesHascleanedmessydatasetsHaspresenteddata insightsto seniormanagementUses datato track apersonalgoalHas usedPython orR foranalysisKnowswhatmachinelearning isHas dealtwith dataqualityissuesHas usedTableauor PowerBIHas workedon a datamigrationprojectLoveslooking atdashboardsHas writtena dataanalysisreportHasautomateda dataprocessHasworkedwith SQLdatabasesHas createdcharts orgraphs for apresentationAttendedLCF 101Enjoysfindingpatternsin dataHas built adashboardfromscratchHascollaboratedacrossagencies ondataHas foundan outlierin data

LCF 301 Bingo! - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
  1. Has trained others on data tools
  2. Can name one data visualisation tool
  3. Has used data to solve a business problem
  4. Can explain data governance
  5. Can explain what a data warehouse is
  6. Has used Excel pivot tables
  7. Has cleaned messy datasets
  8. Has presented data insights to senior management
  9. Uses data to track a personal goal
  10. Has used Python or R for analysis
  11. Knows what machine learning is
  12. Has dealt with data quality issues
  13. Has used Tableau or Power BI
  14. Has worked on a data migration project
  15. Loves looking at dashboards
  16. Has written a data analysis report
  17. Has automated a data process
  18. Has worked with SQL databases
  19. Has created charts or graphs for a presentation
  20. Attended LCF 101
  21. Enjoys finding patterns in data
  22. Has built a dashboard from scratch
  23. Has collaborated across agencies on data
  24. Has found an outlier in data