Lauro: My Data Analyst Career

Hi Lauro, thank you so much for taking the time. Please introduce yourself to our site’s readers.

Hey everyone! Lauro Oshiro here.

I’m a data analyst, located in Brazil. I have been working with business analytics for 7 years, started off as a Business Analyst at an international food industry, then proceeded to a food-tech SaaS startup to work closely as Data Analyst. In nearly 1.5 years, I became Head of Data. I remember working with a ton of SQL queries, python for routine automation, Excel to analyze data and Power BI to help democratize data within the company and to build complex and dynamic data visualizations for our clients as well. Time has passed by and nowadays I’m a Data Analyst with Power BI focus at a consulting company. The projects I’ve been working on lately revolve around a major KPI for Cost Reduction and we’re developing data products for the whole SAZ production units, to help users in high-managing roles to analyze and extract insights on how the production process can be more effective.

Can you share with us how you entered the data analytics industry, and tell us about your first data analyst role?

Sure can!

It kicked off during my undergraduate years. Well, I’m a certified green belt industrial engineer, so I carry a background in business and administration. The Statistical Process Control (SPC) got my attention and deep enthusiasm back then, where I learned there was a way to make use of statistics to evaluate the quality of products and processes. My internship was in a small compounding pharmacy, where I applied some concepts/approaches/tools as Ishikawa Diagram, 5 Whys, Control Charts to find the root-cause of a non-conformity and create an action plan to reduce its occurrence - and of course, the monetary impact it was causing. In the end, I was able to help the company to reduce non-conformity estimated costs in around R$13k!

As it’s not exactly a textbook data analyst experience, it was my very first professional data-related experience, where I was able to do what a data analyst usually does: craft data to positively impact business decisions! It helped me to start my journey as Business Analyst, and then, 2 years later what got me the job as a Data Analyst itself at the startup I mentioned before.

What is it that you're personally finding most exciting about working in data analytics?

The art of crafting business-related data products to impact the health and the development of a company and its clients! That’s it!

You seem to have had a very diverse experience, tell us more about working on projects across different industries (food industry, and now cross-industry at a consulting firm).

Could you tell us a bit more about those experiences, and share how what you do drives insights and business decisions?

Of course! Well, I spoke a little bit of how I got into my Business Analyst job at the great food industry. I worked at a chicken poultry production unit and we produced chicken cuts for Europe, Japan, the Middle East and others… I was the focal point of a key Quality KPI, which was Product Complaints, for both domestic and international markets. Basically there were the quality-related issues of the products and I had to investigate the root-cause and create new action plans for the effect (in other words, to ‘attack the error, the issue itself”) and for the cause (or the circumstances that were enabling these errors to occur) - pretty much what I’ve done before in my previous experience. What differs is that I started to create a database for all of these non-conformities. Then it evolved to an Excel dashboard that I would bring and use to explain to my managers. As soon as I realized, I was helping other areas such as human resources, occupational health and safety and even other business analysts in terms of creating data visualizations. At the time, it was mainly Excel and a little bit of Tableau.

I stayed there for 2 long years and then went to the Startup I mentioned before. If you have worked at a startup, you know how it works… It requires a short learning curve, dynamic and effective approach, because usually there are many plates to be kept spinning simultaneously. I learned SQL on the go and it became my favorite tech skill, at first because I was able to perform my data analysis by myself (not being limited to others extracting data for me), but also because of the ability to, well, query whatever I wanted. I created some sort of query library for my team (BI/Analytics), developing views for other teams too, such as Marketing, Support and Product. I forgot to mention, but I was using A LOT of Excel to perform all the analysis. It helped me until it didn’t - because of the row number limitation, I had to use some other tool and, as I had to both create dataviz and perform the analysis, I started using Power BI, a tool that was already implemented. I turned my manual analysis into an automated pipeline: ETL (using SQL, PowerQuery) and data modeling in Power BI, so I was finally free of spending hours and hours of creating performance materials for the clients, and then I became head of the area. There were so many experiences there, a few that I remember involved:

- Deep dive into logistical reconciliation issues (addressed an internal problem of approximately R$20k using SQL and Excel)

- Investigation and development/improvement of anti-fraud solutions (avoiding false positives while ensuring high-value purchases from customers, utilizing SQL, Excel, Power BI, and Python)

- Creation of queries for various automated processes (SQL, Python)

- Exploratory and diagnostic analysis to assess sales performance (SQL, Power BI)

- Various ad-hoc studies with in-depth analyses for specific clients, including evaluating Loyalty Program performance, Return on promotional campaigns, and Product adherence (SQL, Excel, Google Analytics, Power BI)

Finally, nowadays I’m working specifically with Microsoft related products. A little bit of Databricks for data engineering, powered by Data Factory for the maintenance of some data pipelines, so I can get data necessary to create advanced Power BI reports, while also working with Power BI Online Services. I’m leading a big project on a major KPI for Cost Management. It started as a pilot for domestic units, but nowadays there are more than 10 reports that I have developed, in which I do the technical support and maintenance, that have spread across South America units for both Operational (detailed view from within a single operational unit), Unit-Level (managers can assess distinct units under their supervision) and Managerial (for directors).

What would you say are the must have data analyst skills to thrive in today’s environment?

A great ‘starter-pack’ would be Excel and SQL. But they would not last much. A better data-viz tool like Tableau, Power BI, Looker should improve report creation. Then, I’d say Python for the data analysis per se, Pandas, Numpy, Matplotlib, Seaborn, Scikit-Learn, but also others to have a better interaction between different sources, platforms, APIs.

How did you start improving your skills as a data analyst? What are you currently doing to keep up with the ever changing data analytics industry?

I’m not sure I was a great example of ‘how to improve’, because most of what I learned was ‘on the go’ - skills I had to quickly learn/sharpen up to be able to deal with the complex problems I was facing. But for professionals in Brazil, I’d strongly recommend these guys: Universidade dos Dados (data analysis, business intelligence, data science), Téo Me Why (hands-on data analysis, data science and data engineering) and Jornada dos Dados (data engineering with real-life and hands-on approach). As for Business Intelligence: YouTube and ChatGPT (:

Can you share what factors are most important to you in a data-focused career and why? Do you have a vision of what you'd like your career growth to look like?

Allow me to be a bit less technical here. A great data-focused career requires great self-awareness, knowing what path fits better to what you want for yourself. The data world is growing fast and more and more specific skills are being required. So you can get pretty much lost in the middle if you don’t know what you want. Cheshire Cat would say: if you don’t know where you’re going, any road can take you there.

So yes, I do have a vision of what I want. I’m expanding my skills to data-viz as of now, but I see myself going deeper into machine learning in the future.

What recommendations would you give to someone who is looking to join the data industry and get their first full-time data analyst position?

I described a lot of technical skills, tools, and approaches… but you can never be effective if you don’t understand the business. I’m not talking about the data business, but the business where you are going to apply all your data-related knowledge. Data analysis is about problem-solving and using data tools, etc., is just the way we all found it makes sense (personally and professionally) to get there.

Anything you'd like to highlight, or add? Something that is not specified above but you hear a lot, or would be helpful for people to know?

They say good advice should be sold, not freely given. But I’d love to share my last 2 cents about your career. I mentioned self-awareness before. It’s not only for starters, but a constant and key soft skill for your own good. Sometimes we believe we are stuck, or even thinking we don’t know much (well, I’d say this is always true), but if we don’t know what skills are being required and how value they are, we can find ourselves stuck in a place where our earnings are not enough and with an overload of work. In short: evaluate how your skills align with industry and job market expectations. Don't underestimate yourself.

An extra one: How do you see the increased availability of AI tools such as ChatGPT, Bard etc., impacting the typical data analyst role / or of someone in data analytics? Are you using AI tools to augment your thinking, analysis and overall work?

Paraphrasing Odin from the Thor movie: 'You’re not the god of hammers, you’re the god of thunder.' A tool is just a tool, and in good hands, it can deliver great results.

This has been great, thank you again, Lauro. Where could people see more of your work, and connect with you?

For data-related content, my Linkedin is https://www.linkedin.com/in/lauro-kenji-oshiro/.

Let’s connect and improve our network!