Recently having enrolled in several online learning courses – primarily for professional development – I had a long look at my options before making a final decision about what path I’d head down. Two years ago I explored the idea of getting an MBA, but the price for that level of education has almost tripled in the previous ten years and I had no desire to take on student loan debt in my late 30s.
I considered looking at what courses local Junior Colleges had available, but it turned out that most evening classes were geared toward ESL or baseline computer operation, neither of which would improve my workplace skills. Eventually I discovered edX, an online collection of courses and classes geared toward making education, particularly professional development, more accessible. Very impressed with their catalog, I signed up.
Starting tomorrow I’ll be taking my second course from them, the first in a long series taught by Microsoft employees about business analytics. With any luck I’ll be able to pass them quickly – while each module is designed to take 6-8 hours per week for 4-6 weeks, my work has been generous enough to let me schedule some study time during otherwise quiet periods in the office. With 10 modules and a final project, my goal will be to accomplish the professional certificate by next Summer.
I enjoy learning a great deal, and enjoy listening to knowledgeable, passionate people talk about their favorite subjects. Studying is another matter – I love astronomy but don’t want to memorize the taxonomy and temperature limits of different main-sequence stars, if that makes sense. It’s been a long while since I had to write constructed, practical essays, and though I think it will be a challenge to kickstart myself back into that mode, there’s also enough motivating factors that will help drive me forward.
Business Analytics is all about the study of data; internal process reports, customer feedback, inventory, and sales process. I’m most interested in gathering and examining a company’s real productivity metrics and helping them streamline or bolster their processes in the areas which need the most help. A simple example explores the sales process:
If a company is investing a lot of time and capital into sales and marketing, but their overall customer base isn’t increasing, what could be the cause?
Instead of throwing more money at the problem blindly, I would want to investigate where in the sales process things are breaking down. Are enough initial calls being made to generate enough appointments? What’s the close ratio once in a meeting with a decision maker? Do these metrics vary across target industries or times of year?
Having the right information, and almost more importantly having the ability to analyze it, means a company can solve the right problem to get to their end goal, instead of trying a blanket approach which may only be half as effective while spending twice as much.
Looking at all of the data available to me in my company’s internal process systems, I like the idea of being able to make presentations about how best to help them move forward, backed with corroborating metrics and a certified understanding of how to most accurately interpret them. Luckily I didn’t have to sign up for all 10 modules ahead of time, so if it turns out hat data analytics isn’t for me, I’m not out a lot of money or half a year of my life.
I don’t think I’ll be posting too many updates in this blog about my progress, mainly because I think we’ve all had our fill of other people talking about their journeys through academia – the ironic contrast of that statement and the existence of this post notwithstanding.
Here’s hoping I will be able to expand my own horizons and help my company reach greater heights through the proper analysis of the data available to me. If nothing else, I hope the new knowledge I gain can help me leverage a position within the company that’s more suited to my likes and personal goals.
Current Course Status:
- Career Development: Business and Data Analysis Skills (Fullbridge) – Passed 95/100
- DAT101x: Introduction to Data Science (Microsoft) – Passed 100/100
- Analyzing and Visualizing Data with Excel (Microsoft) – Enrolled
- Ethics and Law in Data and Analytics (Microsoft) – Passed 89/100
- Analytics Storytelling for Impact (Microsoft) – Scheduled
- Querying Data with Transact-SQL (Microsoft) – Planned
- Introduction to R for Data Science (Microsoft) – Scheduled
- Essential Math for Machine Learning: R Edition (Microsoft) – On the Horizon
- Data Science Research Methods: R Edition (Microsoft) – On the Horizon
- Principles of Machine Learning: R Edition (Microsoft) – On the Horizon
- Analyzing Big Data with Microsoft R (Microsoft) – On the Horizon
- Microsoft Professional Capstone: Data Science – Final Exam