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!

During the capstone, collaborate with your mentor to select a data set from an appealing industry. Your objective: analyze the data, offer strategic suggestions to executives, and influence financial or strategic aspects. Develop, test, and present your hypothesis, along with your findings, to your mentor.

To create your capstone project, you’ll employ several skills you’ve learned in the bootcamp:

• Creating hypotheses and drawing a data hierarchy map. 

• Extracting data from relational databases using SQL.

• Cleaning data using Python.

• Mastering presentation personas.

Shape your portfolio with this capstone project—a cornerstone you can present to potential employers.

Optional career units are offered at strategic points within the curriculum. 

You’ll also have access to a 1-on-1 career coach who can help you create a tailored job search strategy. With your coach, you can discuss topics like:

• Targeted jobs and titles.

• Winning job search tactics.

• Mastering networking for interviews.

• Crafting standout resume, LinkedIn, and cover letter.

• Acing interviews, technical and non-technical.

• Expert negotiation guidance.

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. Nonetheless, it's crucial to recognize that not all programs hold the same level of quality. Therefore, conducting thorough research before you decide to enroll is of paramount importance. There are certain factors that warrant your attention while selecting a data analytics bootcamp. These encompass ensuring the curriculum is current, evaluating the extent of student support that will be accessible, and gauging how well the bootcamp's schedule aligns with your daily commitments.

The NIU CPE Data Analytics Bootcamp, created and delivered by Springboard, 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 be backed by a full team, including your industry mentor. Upon completion, you'll hold a credential from a top-tier university and a demonstrable portfolio of your skills.

Data analytics is the art of deciphering insights from information. It involves mining, interpreting, and transforming data into actionable knowledge, driving informed decisions and innovation.

Enhancing decision-making, data analytics empowers businesses to optimize operations, understand customer behavior, personalize marketing strategies, forecast trends, manage resources efficiently, and identify areas for growth.

Absolutely, the demand for data analysts is soaring. Businesses across industries are actively seeking these professionals to translate data into valuable insights, driving informed decisions and gaining a competitive edge.The Bureau of Labor and Statistics (BLS) expects the field to grow at 23% between 2021 and 2031, significantly outpacing the national average of 5%. 

As a data analyst, you wield the power of information. Your role involves collecting, cleaning, and organizing data, extracting meaningful patterns and trends. With these insights, you help businesses make smarter decisions, solve problems, and uncover opportunities for growth. Your expertise transforms raw data into a strategic asset, driving success and innovation.

The journey to becoming a proficient data analyst can vary. Generally, it takes several months to a couple of years of dedicated learning and practical experience. This period involves acquiring skills in data manipulation, analysis, visualization, and programming. Factors such as prior knowledge, the intensity of learning, and the resources you use will influence the timeline. Education programs, self-study avenues, and bootcamps like this one can help expedite the process.

The NIU CPE Data Analytics Bootcamp, created and delivered by Springboard, offers curated curriculum and the support of your 1-on-1 expert data analytics mentor. 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.

On average, data analysts earn an annual salary of $65,112 (Payscale). Salary can range depending on role, sector, years of experience and location. 

To thrive in data analytics, a blend of technical and soft skills is essential. Proficiency in programming languages like Python or R, data manipulation and analysis using tools like SQL and Excel, statistical knowledge, and data visualization expertise are crucial. Additionally, critical thinking, problem-solving, attention to detail, and effective communication skills are vital to interpret and convey insights. An adaptable mindset and a curiosity to explore and learn from data are also integral to excel in this dynamic field.