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Data analysis assistant vs crime data specialist

The differences between data analysis assistants and crime data specialists can be seen in a few details. Each job has different responsibilities and duties. It typically takes 2-4 years to become both a data analysis assistant and a crime data specialist. Additionally, a crime data specialist has an average salary of $84,026, which is higher than the $79,428 average annual salary of a data analysis assistant.

The top three skills for a data analysis assistant include data analysis, R and analyze data. The most important skills for a crime data specialist are SQL, background checks, and R.

Data analysis assistant vs crime data specialist overview

Data Analysis AssistantCrime Data Specialist
Yearly salary$79,428$84,026
Hourly rate$38.19$40.40
Growth rate19%11%
Number of jobs71,39968,456
Job satisfaction--
Most common degreeBachelor's Degree, 67%Bachelor's Degree, 100%
Average age4242
Years of experience44

Data analysis assistant vs crime data specialist salary

Data analysis assistants and crime data specialists have different pay scales, as shown below.

Data Analysis AssistantCrime Data Specialist
Average salary$79,428$84,026
Salary rangeBetween $51,000 And $122,000Between $58,000 And $121,000
Highest paying City--
Highest paying state--
Best paying company--
Best paying industry--

Differences between data analysis assistant and crime data specialist education

There are a few differences between a data analysis assistant and a crime data specialist in terms of educational background:

Data Analysis AssistantCrime Data Specialist
Most common degreeBachelor's Degree, 67%Bachelor's Degree, 100%
Most common majorBusinessCriminal Justice
Most common collegeUniversity of PennsylvaniaBoston University

Data analysis assistant vs crime data specialist demographics

Here are the differences between data analysis assistants' and crime data specialists' demographics:

Data Analysis AssistantCrime Data Specialist
Average age4242
Gender ratioMale, 45.8% Female, 54.2%Male, 11.1% Female, 88.9%
Race ratioBlack or African American, 11.3% Unknown, 2.9% Hispanic or Latino, 13.4% Asian, 13.2% White, 58.5% American Indian and Alaska Native, 0.5%Black or African American, 8.7% Unknown, 3.0% Hispanic or Latino, 12.8% Asian, 10.6% White, 64.3% American Indian and Alaska Native, 0.5%
LGBT Percentage11%11%

Differences between data analysis assistant and crime data specialist duties and responsibilities

Data analysis assistant example responsibilities.

  • Provide clinical staff with customize population health analytic solutions for tracking specific clinical quality measure and managing high risk patients.
  • Perform statistical analysis of successful NCAA basketball teams utilizing SAS.
  • Develop computer programs using software such as SAS and STATA.
  • Create macros and used VBA to update them as necessary.
  • Create SSIS packages to perform ETL operations and create OLAP cube within SSAS, efforts result in improve business processes.
  • Create statistical data reports utilizing SPSS to display efficiency and effectiveness of health expos.
  • Show more

Crime data specialist example responsibilities.

  • Manage customer information in customer management systems CIV.
  • Enter demographics and accounting information on criminal arrest fingerprints and on civil fingerprint cards into the CCIC system.
  • Implement and optimize advanced convergence routing networks with heavy use of EIGRP, DMVPN, ACL's, and VRF.
  • Migrate data using replication and virtualization techniques.
  • Perform maintenance and administrative support for install systems to maintain combat readiness.
  • Extract data from a variety of relational databases, manipulate, explore data using quantitative, statistical and visualization tools.
  • Show more

Data analysis assistant vs crime data specialist skills

Common data analysis assistant skills
  • Data Analysis, 24%
  • R, 14%
  • Analyze Data, 6%
  • Technical Support, 6%
  • Behavior Analysis, 5%
  • Tableau, 4%
Common crime data specialist skills
  • SQL, 85%
  • Background Checks, 9%
  • R, 6%

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