"My journey so far", by a data analytics student

"My journey so far", by a data analytics student

Here, as a first blog, I decided to log my background and tell you about my journey in the shortest format.

Gitanjali Mule's photo
Gitanjali Mule
·Nov 11, 2021·

5 min read

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Background

Hi, my name is Gitanjali. I am a student at University of Texas at San Antonio for Master of Science in Data Analytics. I learned R, Python, SAS, Tableau as a part of curriculum for the courses. Prior to that I had intermediate knowledge of web development and web application, mostly in Ruby on Rails, HTML, CSS, JavaScript, React. But to be honest MS is a whole new experience for me. I did my master's in business administration (marketing) and bachelor's in engineering (electronics and telecommunication) from India, worked as a digital marketing manager in India for about 1+ year and moved to USA in 2017, learned web application development online courses and then finally decided to pursue career combine all the skill set I have.

Master of Science Journey

R.jpg I started my MS journey in Fall 2020 with courses like data visualization, data foundation, algorithms etc. Though I had some programming experience, I was getting into statistics and probability after 10 years. Learning statistical concepts is particularly important for data analysis, especially if you want to start building machine learning model. Stats is the foundation for that. So, learning statistical concept took most of time in the first semester of MS but soon after I got a good hang of stats. Keynote while learning stats is it should make sense to you. What you are learning, if you can explain it in lay man's words then you have understood the concept.

After that doing the tasks in R and Python was the challenge. There are many libraries and packages that are already built by some awesome people for you to use and do the work. The key is knowing what to do, once you know what you want to do with the data then you can figure out how to do it. google, Bing are your companions to unstuck you. I google/Bing almost every alternate thing that I am unsure of, most of the time you will find the answer in first 2-3 links. Googling is an important skill to possess. I took a break in Spring 2021 for personal reasons but kept watching and reading data science material online.

In Fall 2021, I started the semester with Data Analytics Application and Deep Learning on Cloud Platforms courses. Former subject is based on case study-based learning approach. Each week you must solve a case study using the knowledge of all the subjects you have learned so far. you will build predictive model linear regression or for classification, clustering and many more such concepts. and the deep learning course starts introducing you to neural networks. We had to use online platform such as google Collaboratory to build our models.

Hands-on Data Analysis

In this same semester I got an internship for a nonprofit organization called CERI based in San Antonio, Texas as Marketing Analytics Intern. There were about to rebrand their organization in terms of marketing and digital presence, and they wanted to measure their marketing efforts using various tools and online platform such as google analytics, salesforce etc. When I started this internship, my major assignments were to track website visitor, create dashboard/reports about the web analytics using google analytics. Soon I found out that creating reports in data studio is much better than doing the same in google analytics. It was easy for my manager and others to view and interpret data. I was able to customize the report by adding logos, branding material, images, texts, and links if necessary. So, I highly recommend using Google Data Studio if you want to create reports/ dashboard for google analytics data. Learning data studio won't take much time and it is easy to play around plus it is completely free.

ceri-website-logo-orange.png CERI is remarkably high on email marketing, and they use salesforce to conduct email marketing campaigns. Salesforce gives many of the data that helps for analysis of the campaign. for example, date sent, date opened, unique clicks in the email, when the email was delivered etc. Though my manager wanted me to do the reports in salesforce, the learning curve for salesforce, I found, very steep. So, I end up doing the reports using Tableau and R in RStudio. I will have more details on my work on these two platforms in my upcoming blogs. But take away of my work, and my recommendation for further such positions, do it in r or tableau. I understand the employer wants to have a ready material that they can use in future without being dependent on their employees, but these tools saves so much time and it is so easy. Please use tableau, R, or python for data analysis, for creating dashboards or reports. these are the best tools.

What's Next

What I am next up to? Well, I started with this writing and logging my journey now. I will be posting lot of information about machine learning, data analysis, data cleaning, also some case studies; in short, all the hands-on experience I have will be logged here. So, follow me on Hashnode. learn more about the journey of a data analytics student to professional. I have one more semester left of this course and an internship in summer 2022. I will be graduated in Fall 2022. There is lot to learn and lot to implement. We are going to have some real fun in this journey. Connect with me on twitter and linked in and follow me on Hashnode.

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