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Why Are Data Analytic Bootcamps Worth It?

Technology jobs are in high demand, specifically data analysis roles. Why? Companies like Netflix, Amazon, Apple and others use consumer behavior and research to set financial goals. The data created daily is staggering, with 3.5 quintillion bytes estimated in 2023. Data analytics is crucial for gathering, understanding, interpreting and applying data into actionable results. Capitalize on this growing field with the Stony Brook University Data Analytics Bootcamp. 

We've partnered with Microsoft to develop a curriculum that prepares students for success. Our bootcamp will train you to become a professional, business-oriented data analyst within six months. Through 18 structured units, you'll master the fundamentals of data analytics, business concepts like financial and economic analysis, critical thinking and data visualization tools like Excel, SQL, Python, Tableau, Microsoft Power BI and more. 

Most importantly, you'll be paired with an industry expert, giving you access to a wealth of real-world knowledge to add to your technical skills. You'll also complete a capstone project that will showcase your ability to understand and implement the fundamentals of data analysis, including the 5-Step Problem-Solving Approach, SMART principles and advanced data visualization–all things hiring managers look for on candidates' resumes. Stony Brook University also offers optional career units to help you get a job immediately. 

Data Analytic Careers

Data analytics is a very broad career with multiple specializations. It offers excellent pay, job availability and flexibility to work remotely. Through the Stony Brook University Data Analytics Bootcamp, you can prepare for the following data analytics positions and annual median advertised salaries in New York:

  1. Data Analyst: $77,568

  2. Business intelligence analyst: $87,296

  3. Business system analyst: $92,416

  4. Operations analyst: $80,128

  5. Financial analyst: $83,200

Annual Median Advertised Salary. Source: Lightcast; Oct 2022 - Sep 2023; 0-3 years minimum experience required. New York.

Data Analytics Bootcamp Curriculum

We partnered with Microsoft to create a job-focused data analytics curriculum you can complete in six months. Here's a breakdown of the Stony Brook University Data Analytics Bootcamp structure.

Learning Unit Overview

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 and 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

As a data analyst, you help shape a company's strategic or financial goals. Working with your mentor, you'll choose a previously determined data set or find an alternative data set that interests you. The capstone is the course's final project, so you'll utilize everything you've learned as a future business-oriented data analyst. Quick highlights include:

  • Create and state your hypothesis to be proven or disproven.

  • Draw a data hierarchy map and extract data from relational databases using SQL.

  • Organize and clean the data.

  • Use advanced visualization tools you've mastered to create and present the project.

Hyper-Focused Career Units

Offered as a supplemental option, career units are designed to help you get a job upon completing the Stony Brook University Data Analytics Bootcamp. You'll work with a career coach on a job search strategy, build your resume, practice interviewing techniques and learn how to network.

Explore Three Technical Units

Structured Foundations

Structured data is the well-organized framework of quantitative data and is the basis for locating and manipulating data. The goal is to discover data-oriented solutions to a business problem (or theory for class purposes). This is a crucial step in setting you up for success in data analytics.

Here are a few technical lessons included in this unit:

  • Understand and utilize the HDEIP Framework, Five-Step Problem Solving Approach and SMART principles.

  • Become comfortable with creating Mutually Exclusive Collectively Exhaustive (MECE) Issue Trees and Value Driver Trees.

Visualization Tools

As a data storyteller, data visualization is how your data analysis is presented to company leaders and top-level decision-makers. This unit will teach you to use visualization tools, like Tableau and Power BI, to help make your data analysis easy to understand so businesses can adopt, save or request further research or collection.

Data Connectivity

You'll learn how to use programming languages like SQL (Structured Query Language) to understand how the data relates to the problem you're trying to solve. For example, you're trying to figure out what's causing a brick-and-mortar business to underperform. You'd use SQL to analyze raw data from daily foot traffic and sales. 

Student Support From Start To Finish

Personalized support is available to you as soon as you start the course, and even after you graduate. You'll have access to the following:

  • A student advisor: Your advisor will keep you accountable to your units and help with any challenges throughout the program.

  • A personal mentor: Meet regularly with an industry expert for 1:1 mentorship, working with them closely to complete your capstone project.

  • A career coach: Get paired with a 1:1 career coach who can help you refine your career goals and develop a plan to achieve them. Optional career curriculum is available throughout the bootcamp.

  • A Slack community: Connect and collaborate with other students for feedback and support.

Online student support

Meet Regularly With an Industry Mentor

The best way to learn how to become a data analyst is from industry professionals. The Stony Brook University Data Analytics Bootcamp pairs you with one of our hand-picked experts in the field for 1:1 weekly mentorship. Meet some of our current mentors:

Mohit Bhatia
Program Manager - Analytics
Hasin Ahmed
Head of Product Design
Julia Kho
Operations Research Developer
Shoumik Goswami
Lead Business Analyst

Is Our Data Analytics Bootcamp Right For You?

If you are a born problem solver with a penchant for critical thinking, you'll fit right into the Stony Brook University Data Analytics Bootcamp. Prerequisites include:

  • Problem-solving and critical thinking skills.

  • Fluency in English (both written and spoken), as determined by interactions with the enrollment team.

Data Analytics Bootcamp FAQs

Is a data analytics bootcamp worth it?

Bootcamps can be a great way to gain the skills you need in order to start a career in data analytics, especially if you want to keep tuition costs low and move into a new career within months rather than years. However, not all programs are created equal, so it’s important to do your research before enrolling. Some things to look for when choosing a data analytics bootcamp include an up-to-date curriculum, what student support will be available, and how the bootcamp will fit into your life.

The Stony Brook University's Data Analytics Bootcamp will have you job ready in as little as six months. It’s 100% online, so you don’t have to put your full-time job on hold. You’ll have the support of a whole team, including your industry mentor. When you graduate, you’ll have earned a credential from a leading university and you’ll have the portfolio to prove your skills. 

What is data analytics?

Data analytics is the process of examining large data sets to uncover hidden patterns, correlations and trends. It's a powerful tool for understanding what is happening within your business, and it can help you make more informed decisions about where to allocate your resources.

Data analytics can be used to improve marketing campaigns, detect fraudulent activity, identify customer needs and preferences and optimize operations. The possibilities are endless, and the benefits are clear.

Are data analysts in high demand?

Data analysts are in high demand, and it's only going to continue to grow in the coming years. Companies are collecting more and more data every day, and they need people who can help make sense of it all.

What does a data analyst do?

A data analyst gathers, cleans and organizes data to identify trends and relationships. They then use this information to make informed business decisions.

Some of the most common tasks of a data analyst include: extracting data from various sources, cleaning and transforming data, identifying patterns and trends, developing models to forecast future trends and presenting findings to stakeholders.

Data analysts must be able to work with large volumes of data, as well as with different types of data (including unstructured data). They must also be able to think critically and analytically to derive insights from complex datasets.

How long does it take to become a data analyst?

It can take months or years to build all of the skills needed to become a data analyst, but a program like the Stony Brook University's Data Analytics Bootcamp can help speed that process up. With curated curriculum and the support of your 1-on-1 expert data analytics mentor, you’ll learn these skills more quickly. 

If you have a background in programming or statistics, you'll be able to learn the necessary skills for data analysis more quickly. But even if you're starting from scratch, with some focused effort you can become proficient in data analysis.

What is the salary of a data analyst?

The median advertised salary for data analysts in New York is $77,568 according to Lightcast (Oct 2022 - Sep 2023; 0-3 years minimum experience required. New York.) Salary can range depending on role, sector, years of experience and location. 

What skills are needed to work in data analytics?

Foundationally, you need to develop the ability to collect, organize and analyze data to work in data analytics. This involves having a basic understanding of statistics and being able to use software to extract insights from data.

You also need strong problem-solving skills. Data analytics is all about identifying patterns and trends in data and coming up with hypotheses about what they mean.

Verbal and written communication skills are important too, as you will often need to communicate your findings to others clearly and concisely. The adoption of your recommendations is reliant upon your communication skills. 

More Questions About the Program?

Speak to our enrollment team by completing an application, email Carolina, our enrollment advisor, or explore more frequently asked questions

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