HascleanedmessydatasetsCan explaindatagovernanceHaspresenteddata insightsto seniormanagementHascollaboratedacrossagencies ondataUses datato track apersonalgoalHasautomateda dataprocessEnjoysfindingpatternsin dataHas usedPython orR foranalysisHas workedon a datamigrationprojectHasworkedwith SQLdatabasesCan nameone datavisualisationtoolHas usedExcelpivottablesHas built adashboardfromscratchCan explainwhat a datawarehouseisHas writtena dataanalysisreportHas createdcharts orgraphs for apresentationHastrainedothers ondata toolsKnowswhatmachinelearning isAttendedLCF 101Loveslooking atdashboardsHas dealtwith dataqualityissuesHas foundan outlierin dataHas usedTableauor PowerBIHas useddata to solvea businessproblemHascleanedmessydatasetsCan explaindatagovernanceHaspresenteddata insightsto seniormanagementHascollaboratedacrossagencies ondataUses datato track apersonalgoalHasautomateda dataprocessEnjoysfindingpatternsin dataHas usedPython orR foranalysisHas workedon a datamigrationprojectHasworkedwith SQLdatabasesCan nameone datavisualisationtoolHas usedExcelpivottablesHas built adashboardfromscratchCan explainwhat a datawarehouseisHas writtena dataanalysisreportHas createdcharts orgraphs for apresentationHastrainedothers ondata toolsKnowswhatmachinelearning isAttendedLCF 101Loveslooking atdashboardsHas dealtwith dataqualityissuesHas foundan outlierin dataHas usedTableauor PowerBIHas useddata to solvea businessproblem

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.


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