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Data Analytics Associate Degree

IT Data Analytics Associate Degree

Visualize Your Success

with the new Data Analytics associate degree

Imagine playing a key part in a company's success and future – and feeling valued in your role.

In data analytics, you collect, clean, analyze, and visualize data, transforming it into meaningful information that drives business decisions. You tell the data's story through visualizations and presentations.

As organizations increasingly embrace technology and data, you could become an analyst in any one of a variety of fields including advanced manufacturing, education, information technology, marketing, health care, insurance, finance, and many more.

Below are examples of data analyst responsibilities in different fields:

  • Advanced manufacturing – You may work in predictive maintenance, using data from machine learning to predict when equipment will need upkeep and repairs. That can save the company time and money by reducing machine downtime.
  • Logistics – You may work to deliver analytics to operations and the business to lower total transportation cost by extracting data and building visualizations/analytical models to support business needs.
  • Insurance – You would ensure analysis and reporting accuracy and integrity and provide insights into performance trends. You would communicate findings to various stakeholders and leadership with recommendations for actions to address business changes, trends, and issues.
  • Health care – You could track and analyze patient care. You would create data visualizations that enable decision makers to determine future next steps for patient care.

Program Code: 101563

As businesses are collecting more data there is an increased need to interpret, analyze, and present that data to the key stakeholders who make the business decisions. The Data Analyst program prepares learners to use techniques to combine, clarify and interpret patterns and trends, and provide visualizations of the data using best practices and relevant technologies.

Follow Your Path

Data Analytics is in the top 10 in-demand jobs according to Microsoft who utilized the job postings data from LinkedIn. As more businesses are connecting their machines with their ERPs the businesses need to make more intentional decisions. As part of Industry 4.0 manufacturing, marketing, and financial areas, businesses are looking for people who can gather, analyze and interpret patterns and trends, and provide visualizations of the data to the right person who can make informed decisions. Businesses are looking at machine monitoring, safety wearables, providing proactive customer service, and staying fiscally viable. All of this comes with big data that needs to be analyzed to guide business decisions. UWGB is looking to offer a Data Analytics bachelor’s degree in the future.

Employment Potential

Data Analyst Data Engineer Business Intelligence Analyst Consultant (Analytics) Data Analyst Specialist Data Analyst Assistant Junior Data Scientist Junior Data Analyst

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    Requirements for Program Entry

    • Apply at www.nwtc.edu/apply
    • Submit high school, GED, or HSED transcripts and college transcripts (if applicable) to transcripts@nwtc.edu
    • Tip! Our admission advisors will assist you through every step. Have questions? Connect with NWTC Admissions at start@nwtc.edu or 920-498-5444.
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    Curriculum
    Curriculum: Students following the study plan below will complete the Data Analytics Associate Degree in the number of semesters shown.
    First Semester
    Semester Total
    14
    Second Semester
    Semester Total
    16
    Third Semester
    Semester Total
    15
    Fourth Semester
    Semester Total
    14
    Total Credits
    59

    Curriculum Note: The credit for 10-890-101, College 101 is an Institutional Requirement for graduation. Consequently, it is not part of the program requirements, but must be passed with a C.

    Program Outcomes

    • Develop functional knowledge in the rapidly growing field of data analytics.
    • Build and apply critical thinking skills when integrating datasets from multiple sources.
    • Develop techniques for communicating data through visualization and storytelling.
    • Use relevant technologies to gather, analyze and interpret patterns and trends in data.
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