About this Video

• Video Title: How I became a Data Analyst (No CS Degree nor Exp) | How Data Analytics changed my life
• Channel: HouseCalledDewberryII
• Speakers: Ma
• Duration: 00:13:48

Introduction

This video details the speaker's journey to becoming a data analyst without a computer science degree or prior experience. The speaker aims to show viewers that a career change into data analytics is possible, even with a non-traditional background, highlighting the path taken and the challenges overcome.

Key Takeaways

• The speaker transitioned from disliked jobs in customer service, banking, and insurance to a data analyst role.
• A significant life event (homelessness) fueled the decision to pursue data analytics.
• A 12-week boot camp (Cury Incorporated) provided the necessary skills in SQL, data warehousing, data transformation, and reporting.
• The job search took three months, involving multiple applications and interviews.
• The speaker's career in data analytics led to significant financial success and property ownership.

Here's a breakdown of the speaker's steps, follow-up points, and specific skills learned, organized by the sections of her narrative:

Section 1: Early Career & The Spark

• Steps: Worked in customer service (hated it), retail banking (customer-facing, disliked), and insurance (adjuster, intensely disliked due to customer complaints and low pay). This dissatisfaction motivated her to seek a career change.
• Follow-up points: None explicitly stated in this section.
• Skills learned: None directly related to data analytics; primarily customer service and handling difficult situations.

Section 2: Discovering Data Analytics and Initial Doubt

• Steps: Learned about data analytics from her best friend's husband in 2012. Initially doubted her ability to pursue this field.
• Follow-up points: None explicitly stated in this section.
• Skills learned: None directly mentioned, although the seed of interest was planted.

Section 3: The Catalyst for Change (Homelessness)

• Steps: Experienced homelessness in 2013 due to a confluence of unfortunate circumstances (father's death, sister's own financial struggles). This hardship solidified her determination to improve her financial situation.
• Follow-up points: This section emphasizes the stark reality of her situation, highlighting the desperation that propelled her career change. She describes paycheck-to-paycheck living, utility cutoffs, and difficult choices between essential bills and childcare.
• Skills learned: No new skills learned, but the experience served as powerful motivation.

Section 4: The Cury Incorporated Boot Camp

• Steps: In February 2016, she enrolled in a 12-week data analytics boot camp at Cury Incorporated, using her tax return money to purchase a laptop.
• Follow-up points: The boot camp was a key element of her success. The intensive, short-term nature was crucial for someone without the time or resources for a traditional education.
• Skills learned:
  • First 6 weeks: SQL (creating and maintaining tables, databases, user-defined functions, CTEs, joins). Coding fundamentals.
  • Next 3 weeks: ETL (Extract, Transform, Load) data warehousing, relational databases, data extraction (Excel, HTML), data cleaning and manipulation.
  • Final 3 weeks: Data visualization, reporting (techniques not specified, but likely included common BI tools).

Section 5: The Job Search

• Steps: The job search began in August 2016 and lasted three months. She applied for many positions, had an initial unsuccessful interview, and received some recruiter inquiries. She emphasizes the importance of applying even after setbacks.
• Follow-up points: Be persistent in applying. Aim to meet at least 80% of the requirements in job descriptions. Be aware of job scams.
• Skills learned: Interview skills (improved over time). Recognizing and avoiding job scams.

Section 6: The Interview Process

• Steps: Four interview rounds for her first data analyst position:
  • Round 1 (30 minutes): Manager interview focusing on SQL, reporting, and work environment preferences.
  • Round 2 (1 hour): Technical interview with seniors and the manager, diving deeper into technical SQL skills (parameters, stored procedures, CTEs, joins, views).
  • Round 3 (30 minutes): Interview with IT director, business analyst manager, and QA manager – less technical, focusing on personality fit.
  • Round 4 (30 minutes): Interview with CEO, CFO, and president – focusing on cultural fit.
• Follow-up points: Detailed breakdown of interview rounds is provided as a valuable guide for viewers.
• Skills learned: Practical experience navigating a multi-stage interview process.

Section 7: Success and Beyond

• Steps: Landed the job in November 2016, doubling her salary. Worked there for two years. Moved on to a Business Intelligence Developer role. Invested in real estate (commercial and residential properties).
• Follow-up points: Data analytics transformed her life positively, allowing her financial independence and property ownership. Her only regret was not starting sooner.
• Skills learned: Business intelligence development (explicitly mentioned). Real estate investment (implicitly mentioned).

Additional Follow-up Points (Throughout the Video):

• Importance of learning Excel and SQL.
• Mastering a BI reporting tool (SSRS, Power BI, Tableau, Qlik).
• Creating a strong resume (using tools like ChatGPT to enhance, but being mindful of detection). She mentions having a resume template available.
• Information on scams is available in another video.

This detailed breakdown organizes the speaker's journey into manageable sections, making her key insights and learnings more accessible.