Hi I was wondering if there's any women on here who are Data Analysts that can explain what their day to day is like and how they went about becoming a Data Analyst!
laxmiarte·Sep 01, 2021laxmiarte·Sep 01, 2021Hi Leila,I do a lot of analytics and data visualization work. I'd say my day is split pretty evenly between data ETL work (basically getting the data ready for analysis by pulling, loading, and cleaning it) and data visualization work (i.e.: designing dashboards to present the data for decision making).I spent many years at Verizon, where I did a lot of large scale data architecture and implementation work. Think designing a database that would scale to many millions of users. Along the way I also started working on analyzing the large quantities of data being collected using SQL, Python and SSRS. Over the last 4-5 years, I created my own business where I do this exact sort of work, but at my own company Data Clartiti. I hope this helps..
virgofromearth·Sep 01, 2021virgofromearth·Sep 01, 2021Hi Laxmi, Thank you so much for your response this is very helpful! What specific software do you tend to use on a daily basis like (SQL software, BI tool) and how did you enter into data analysis? Did you learn through school or was it more self taught?
laxmiarte·Sep 01, 2021laxmiarte·Sep 01, 2021Happy to help..I use the following tools most often:- SQL - BI tools: PowerBI, Tableau, Google Data Studio- Azure Data FactoryData analysis and databases was something I learned in grad school. The BI tools were self taught. I'd say having an understanding of how databases work both logically and physically has served me well. BI tools these days are quite simple to pick up. I have a video on my Youtube channel called How to build a PowerBI report in 5 mins. Link : https://www.youtube.com/watch?v=vxwcvfDQcywcheers!
virgofromearth·Sep 01, 2021virgofromearth·Sep 01, 2021Awesome! Thank you so much, I’ll check out your video. Also, do you have a Linkedin I can connect with you on?
laxmiarte·Sep 01, 2021laxmiarte·Sep 01, 2021Sure. Its https://www.linkedin.com/in/laxmiarte/
I’ve also been looking into roles in Data Analytics and just started the Google Data Analytics Professional Certificate: https://www.coursera.org/professional-certificates/google-data-analyticsIt’s designed to prepare you for an entry-level Data Analyst role, gets into SQL and R, and partners with several tech companies to recognize the cert. The reviews I’ve read on it says it more basic/foundational, but I figured everyone has to start somewhere :)
Hey Allison!I also started the Google Data Analytics Certificate. I did some research on whether or not it was completely worth it but so far it’s been pretty helpful. I had some knowledge of SQL and Excel but I think knowing the basics/foundations is still useful as I haven’t been learning about data analysis for that long. How are you enjoying the course so far and when do you think you’ll complete it?
That's awesome! Yeah, I'm still working through Course 1 but liking it a lot so far. I need structure to learn, so I appreciate how well laid out the curriculum is and that they walk you through it from the beginning. I've taken R courses before in my grad program, but felt like I was just thrown into the code without explaining the what/why of the analysis. Hoping to finish the cert by December, but also been doing DataCamp on the side for extra SQL practice. Would love to hear how it's going for you and your data analytics journey too!
I’m also on course 1! and I’m the same way when it comes to learning I prefer a lot of structures and the videos help a lot since I’m not too keen on just learning by reading. And oh no that sounds rough I can understand how that was probably confusing hopefully the structure in this course will help you understand R a bit better! I’m kind of eh about them using R because I feel like most data analysts use Python but the more languages you know the better lol. And ah I didn’t know they had Datacamps! How is that going for you? I started learning about data analysis back in July and learned SQL and kind of got a better understanding of Excel through self teaching. It wasn’t that hard to learn again, not a lot of structure so I kind of struggled but doing guided projects/independent projects definitely helps a lot.
That’s so great! Yeah I definitely recommend DataCamp then - it’s similar to Codeacademy but their courses are geared for Data Science and include more practical applications that I personally wanted (e.g. Marketing Analytics, Python for Finance). I think they have a whole Excel course too! Best of luck with your data journey! 😊
Thank you so much!!! Same for you I hope everything goes well in your data journey ❤️
I'm a Data Scientist on a Product Analytics team at a large tech company. My typical day:20-50% meetings: -- "Housekeeping" meetings - team meetings or 1:1s with my boss to discuss project updates, ask questions, etc. -- Project-focused meetings with my stakeholders/internal clients to discuss what they are working on and how I can support it. Answer their questions around analytics tagging (so we can collect the right data), discuss what they need from me (dashboards so they can self-serve their own data? a deeper analysis?), discuss which metrics to use to measure success for new features, discuss A/B tests they can run for new features or improvements, present my insights and recommendations from their last ask. 50-80% hands-on work: -- Researching for my projects - reviewing similar projects done by my colleagues, figuring out what is the business problem/use case we're solving for, which data source should I use, and often talking to someone to understand where it's stored/how it's structured/which metrics to use -- Getting my data - SQL queries. Always takes longer than you think! -- Analyzing the data - exploring it, looking at correlations, rates, and visualizations, maybe some predictive modeling - whatever will answer my original questions. I usually use Python but sometimes I'll use R or Tableau. If it's a simple project, I might use Excel if that's quicker and the dataset isn't too big. -- Summarizing my analysis into a PowerPoint or Confluence article with an explanation of my work and my insights and recommendations.
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