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Job Trends Presentation

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Data Analytics using Business Intelligence tools in this project helped us analyze the trends in the job market based on countries, timelines, job profiles and salaries. This data allows comparison of salaries across countries for different job profiles over time and shows how job market evolved over years.

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Job Trends Presentation

  1. 1. Job Trends Using Data Analytics PRESENTED BY: GOURAV ANVEKAR RANJAN MELANTA KUNAL SAVLANI
  2. 2. Agenda  Introduction  BI Tools/Techniques Used  Data Normalization  Analysis  Comparison  Business Value  Conclusion
  3. 3. Introduction
  4. 4. Introduction  The dataset is based on job market metrics like salaries, job industries, occupation, countries etc.  Contains historical data from year 1983 to 1999  Contains wage data of 132 countries  Data source EconomicsWebInstitute.org
  5. 5. Dataset Snapshot
  6. 6. BI Tools/Techniques Used  Tableau  Microsoft Excel Pivot table  Google Data Visualization API
  7. 7. Data Normalization  Cleaning the dataset  Removed entries with inappropriate values (1%)  Removed entries with NULL values (0.5%)  Consolidated dataset from different year ranges  Normalized dataset to meet single standard of comparison  Wage rate was standardized to USD  Exchange rate was taken care for country to country and time to time
  8. 8. Analysis
  9. 9. Average Wages Vs Country
  10. 10. Average Wages Vs Country
  11. 11. Average Wages Vs Year
  12. 12. Average Wages Vs Occupation 0.00 500.00 1000.00 1500.00 2000.00 2500.00 3000.00 Airtransportpilot Governmentexecutive… Accountant Dentist(general) Governmentexecutive… Journalist Electronicsdraughtsman Technicaleducation… Supervisororgeneral… Miner Metalmelter Roadtransportservices… Ship'ssteward(passenger) Constructionalsteelerector Buildingelectrician Benchmoulder(metal) Electricpowerlineman Butcher Postofficecounterclerk Forestsupervisor Deep-seafisherman Quarryman Grainmiller Telephoneswitchboard… Aircraftaccidentfire-fighter Urbanmotortruckdriver Ambulancedriver Cook Sawmillsawyer Labourer Logger Furnitureupholsterer Fieldcropfarmworker Sewing-machineoperator Plantationsupervisor Average Wage Vs Occupation
  13. 13. Comparison
  14. 14. Average Wage Comparison
  15. 15. Average Wage Comparison - Accountant 0 500 1000 1500 2000 2500 3000 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Average Wage Comparison - Accountant United States China India
  16. 16. Data Visualization
  17. 17. Conclusion
  18. 18. Business Value  The analysis can be used by  Job boards like glassdoor, LinkedIn etc. to recommend potential employers to candidates based on their profile and the job industries  University career services department to help students target specific occupation by considering average salary metrics by locations, growing trends etc.  This analysis can further be extended to make future predictions in job trends
  19. 19. Conclusion  The world has seen major shifts in the changing job markets  Worlds largest economies have shown significant rise in the average salaries in many job industries  Results will help us compare the historical data and hence carry out predictive analysis to save cost and build better solution useful to various organizations
  20. 20. Questions
  21. 21. Thank you

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