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Drilling down into the Salaries & Travel Reimbursements area of the site, much information is quickly at your fingertips.  For this analysis effort, only the following Organization data was retrieved.

Fiscal YearOrganization TypeOrganizationRecords
2010Local Boards of EducationATLANTA INDEPENDENT SCHOOL SYSTEM9,201
2010Local Boards of EducationCOBB COUNTY SCHOOL DISTRICT20,377
2010State Agencies, Boards, Authorities and CommissionsPUBLIC SAFETY, DEPARTMENT OF1,914
2010Local Boards of EducationFULTON COUNTY BOARD OF EDUCATION15,408
2011Local Boards of EducationFULTON COUNTY BOARD OF EDUCATION15,200
2012Local Boards of EducationFULTON COUNTY BOARD OF EDUCATION14,843

Quite obviously these 76,943 (very well-formed) records do not meet Gartner's 3Vs definition of "big data", but they do allow us to exercise the Hadoop & Big Data tooling to perform some level of data analysis.  I also did the following little bit of manual pre-processing (that would normally happen in the ELT space) prior to concatenating these six files together.

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Please see Format & Sample Data for Open Georgia for a visual representation of what the data looked like at the end of this preparation phase.  I ended up with a (tiny by Hadoop standards for sure) 7.6 MB file I called salaryTravelReport.csv that shrunk down to 1.2 MB when zipped.  If you don't want to perform these, or similar, steps to get this data (and possibly much more) then feel free to download salaryTravelReport.csv.zip, unwind it, and then store it on HDFS yourself.

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titleClean Dataset

I decided for further analysis of this file, such as done in use spark to calculate salary statistics for georgia educators (the fourth book of the trilogy), I would use the code from use pig to calculate salary statistics for georgia educators (second of a three-part series) that actually cleans up the dataset's comma problems.  I saved the results of that which is the 76,943 tab-delimited records that are zipped up into cleanSalaryTravelReport.tsv.zip (1.2 MB).