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Why enroll in a data analytics bootcamp?

Each day, new data is being created, and Forrester Research estimates that between 60% to 73% of enterprise data is not being used for data analytics. Businesses are recognizing that not utilizing this data puts them at a competitive disadvantage and are looking to data analysts to tap into this data and distill actionable business insights to drive decision making. 

The Data Analytics Bootcamp with University of Maryland Global Campus in the DMV area, offers an immersive, robust curriculum that will assist you in developing analytical and technical skills needed for success, whether you want to make a full career change to a data analyst position or bring a stronger data-driven approach to business decisions in your current role. 

Within the curriculum, you’ll master analytics and visualization tools like SQL, Microsoft Power BI, ableay, Excel, and Python. You’ll be able to demonstrate your skills through 20+ hands-on mini projects as well as a capstone project, ultimately creating a tangible portfolio that can be shared with prospective employers. 

While you progress through the fully online program, you’ll never be doing it alone. Students enjoy support from their student advisor, as well as 1:1 video calls with a personal mentor regularly who has experience in the data analytics industry. Lastly, this bootcamp also includes career support through dedicated career units and a 1:1 career coach. 

Explore the data analytics curriculum, careers, and support below. 

Data analytics careers

Data analytics skills can be applied to roles in a wide range of industries. Some examples of data analyst roles and average salary include: 

  • Data analyst: $68,316 (Indeed)

  • Operations analyst: $59,122 (Payscale)

  • Business intelligence analyst: $70,960 (Payscale)

  • Healthcare consultant: $79,504 (Payscale)

  • Financial analyst: $62,774 (Payscale)

  • Business systems analyst: $70,672 (Payscale)

Data Analytics Curriculum

Curriculum breakdown

The bootcamp itself is structured into 18 learning units which include: 

  1. Program Overview

  2. Structured Foundations

  3. Your Job Search Strategy

  4. Microsoft Excel for Business Analytics

  5. Financial Analysis

  6. Effective Networking: Building Your Network

  7. Economics for Data Analysis

  8. Statistics for Data Analysis

  9. Informational Interviews

  10. Visualization Tools

  11. The Art of Storytelling

  12. Find the Right Job Title & Companies

  13. Data Connectivity

  14. Preparing for and Getting Interviews

  15. Data Analysis in Python

  16. Capstone

  17. Effective Interviewing for Data Analysts

  18. Bootcamp Conclusion and Congrats!

Capstone project

At this point in the bootcamp, you’ve learned the skills needed to become a business-oriented data analyst. 

  • You’ll have mastered how to effectively structure your hypotheses and how to draw a data hierarchy map to connect exclusively to the data sources you need. 

  • Additionally, you’ll have the ability to extract data from a relational database using SQL and clean the data using Python. 

  • Lastly, you’ll have mastered the different presentation personas and will be able to present your analysis either via PowerPoint or Tableau to create a compelling narrative! 

As your final submission, you’ll employ all of these skills to create a capstone project.

You’ll work with your mentor to choose a data set to focus on for this final project. Each of the datasets provided reflect a different industry. If none of the datasets match your interests, you’ll be able to have a discussion with your mentor about using an alternative data set that you find on your own. The premise of this project will again focus on providing recommendations to executives that will showcase your business analysis skills and help to shape the organization’s strategic or financial drivers.

Career units

Optional career units are offered throughout the curriculum, so you’re building a job search strategy far before the end of the bootcamp. Receive guidance on building your resume and cover letter, networking, interviewing, and salary negotiation.

Preview three of the course’s technical units

Structured Foundations

The structured foundations approach is the foundation you’ll use to come up with a data-oriented solution to any business problem.

No matter what industry you’re in, if you're able to master the ability to frame problems in a structured, data-driven way, you’ll always come out on top.

  • Develop an understanding of the HDEIP Framework and the Five-Step Problem Solving Approaches

  • Learn how to use SMART principles to create a problem statement worksheet

  • Become comfortable creating Mutually Exclusive Collectively Exhaustive (MECE) Issue Trees

  • Develop an understanding of Value Driver Trees

Visualization Tools

Visualization Tools such as Power BI are critical tools used in the Presentation Phase of the HDEIP Framework. While upfront analysis is very important work, ultimately, how this information is presented, visualized, and consumed determines whether your analysis will be adopted or shelved. In this unit, students will learn how to use Power BI and Tableau to craft powerful, impactful stories.

In this unit, you’ll:

  1. Develop an advanced ability to use two visualization tools: Tableau and Power BI

  2. Practice using functions data analysts use on a daily basis

Data Connectivity

While working through this section of the course, you’ll learn how to leverage Structured Query Language (SQL) to query relational database management systems. In other words, you use queries to understand the data contained in databases. Here’s one example. Let’s say you’re a data analyst assessing underperforming malls. You’d write a query to analyze daily foot traffic data stored in the malls’ databases.

In this unit, you’ll:

  • Develop the ability to explain the nuances of a database and how it relates to set theory

  • Write best practice queries in SQL

  • Practice using SQL with real data to extract insights to be presented to an audience

Student support

You’ll be able to complete the 100% online Data Analytics Bootcamp on your own schedule, but you’ll also have the support of a full team behind you! 

You’ll be supported by your:

  • Student advisor: From day one, your advisor will help keep you accountable to your learning goals and will provide tips to clear any roadblocks you may encounter. 

  • Industry mentor: You’ll be matched with a personal mentor with robust experience, and you’ll meet regularly with them 1:1 to discuss and receive feedback on your projects. You’ll work closely with your mentor on your capstone project. 

  • Career coach: As you work through optional career curriculum, you’ll be able to speak with your career coach. 

  • Slack community: Meet and network with fellow students, share feedback and build camaraderie. 

University of Maryland Global Campus

Experience 1-on-1 mentorship from an industry expert

Only one of every 12 mentor applicants get hired. Develop your skills faster with the support of your mentor.

  • Regular 1:1 video calls: Refine your projects, get help addressing any roadblocks, and discuss your professional goals with someone already in the industry.

  • Accountability: Your mentor will keep you on track so you can achieve your learning goals. 

  • Unlimited mentor calls: Get additional 1:1 help from other cybersecurity expert mentors in our community, at no extra cost.

Chris Hui
Senior Data Scientist
Leslie Chen
Business Associate
Ryan George
Data Analyst
Venkatraman Prabhu
Sr. Product Manager

Is this DMV-Based Data Analytics Bootcamp right for you?

This bootcamp is designed for students with two years of work experience plus an aptitude towards problem solving and critical thinking.


  • Strong critical thinking and problem-solving skills

  • Fluency in English (written and spoken), as determined by initial interactions with the Enrollment team


What is data analytics?

Data analytics is the process of examining data sets in order to draw conclusions about the information they contain. Typically, data analytics is used to find patterns and trends, and to make predictions about future events. Data analytics can be applied to any type of data, including financial data, customer data, sales data, and web traffic data. There are a variety of methods that can be used for data analytics, including statistical analysis, machine learning, and rigorous modeling. The goal of data analytics is to extract valuable insights from data that can be used to improve decision-making. When used effectively, data analytics can help businesses to optimize their operations, reduce costs, and increase profits.

Is Data Analytics a good career in the Washington metropolitan area?

Yes, Data Analytics is a promising career in the Washington metropolitan area, which includes Washington, D.C., Maryland, and Virginia. This region has a thriving job market for data analysts, as it hosts numerous government agencies, private companies, and non-profit organizations that require data-driven decision-making. Additionally, the Washington metropolitan area has a high concentration of industries such as healthcare, finance, and technology, which rely heavily on data analytics for strategic planning and operational efficiency. Data analysts in the region can expect competitive salaries, opportunities for professional growth, and exposure to diverse projects. As a data analyst in the Washington metropolitan area, you'll have the opportunity to contribute to the growth of various sectors while building a rewarding career.

What does a data analyst do?

A data analyst is responsible for collected data and using it to generate insights that can improve business operations. This involves using statistical methods to identify trends and relationships between different factors.

Data analysts also develop visualizations, such as charts and graphs, to help communicate their findings. In addition, they may develop algorithms to automate certain tasks, such as identifying outliers in data sets.

Data analysts typically work with teams of other professionals, such as engineers and marketing experts, to ensure that the data they collect is used effectively. With the ever-growing importance of big data, the role of data analyst is becoming increasingly vital in a wide range of industries.

What skills are needed to work in data analytics?

Data analysts are inquisitive, creative thinkers with logical and rational thinking processes. They combine curiosity and inventiveness with logical and rational thought patterns. 

They must also be able to read and interpret statistical data, understand linear algebra and calculus, data visualization, and have a working knowledge of programming languages like Python as well as databases such as SQL. 

Finally, data analysts must be excellent communicators in order to communicate their key findings in compelling presentations.

What type of jobs can you do after a data analytics bootcamp?

This bootcamp can prepare you for a variety of data analyst roles including:

  • Data analyst

  • Operations analyst

  • Business intelligence analyst

  • Healthcare consultant

  • Financial analyst

  • Business systems analyst

Data analysts can progress into roles including: 

  • Business intelligence analyst

  • Intelligence analyst

  • Competitive intelligence analyst

  • Market intelligence consultant

  • Strategist

  • Strategic business and technology intelligence consultant

How long does it take to become a data analyst?

It can take anywhere from 6 months to a few years to become a data analyst, depending heavily on your path to acquire data analytics skills. Our bootcamp combines theory with hands-on practice and projects, prepping to make you job-ready upon graduation in six months, on average.

What is the salary of a data analyst?

Data analysts earn an average of $68,316 annually, according to Indeed. Data analyst salary can vary based on level of experience, geographic location, and a number of other factors. 

Are data analysts in high demand?

Data analysts play a vital role in helping organizations to understand their data and make better decisions. As a result, there is high demand for data analysts with the skills and knowledge to turn data into insights. 

The U.S. Bureau of Labor and Statistics estimates that operations research analysts, which include data analysts, can expect a 25% growth rate in employment from 2020 to 2030, much faster than the average growth rate of 8% for all occupations. 

Is a data analytics bootcamp worth it?

A data analytics bootcamp is worth it, especially if you want to avoid costly tuition and move into the field within months rather than years. In the Data Analytics Bootcamp at University of Maryland Global Campus, you’ll learn the technical skills you need within six months. While studying 100% online, you’ll have the support of a whole student support team behind you. Upon graduation, you’ll have a portfolio that proves your expertise and a credential from a leading university. 

More questions about the program?

Complete the “Apply Now” form to schedule a call with our Enrollment team, email Carolina, our Enrollment Advisor, who will help you think through the decision, or explore more frequently asked questions.

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