Aug 18, 2021 | Nikita Phavade
1. Hi Lindsay! Tell us more about your domain, Data Analytics. What does it mean to you?
Data analytics is about discovering insights from data that could bring values to the organization in a form of optimization. For example, improving effectiveness in customer acquisition efforts or reduction in operational costs. So, there are two parts of it; insights generation and value generation by taking action on the insights.
The first part includes digging deep into the data by asking micro questions that relate to the bigger objective. This requires technical and statistical skill. Technical skill is to plow through big datasets via SQL Query and Python. Statistical skill is to understand the behaviour behind numbers.
The second part of value generation involves different ways to communicate these findings to stakeholders. It could be in the form of self service analytics via dashboard or ad hoc analytics via presentations. This point requires soft skills from the analyst, specifically data storytelling. For dashboards, creativity is empirical to know how to present the data in a way that will be easy to understand. For presentations and bigger projects, influence and storytelling skill are more prominent to be able to convince stakeholders on testing out the recommendations.
2. What does a day look like for a Data Analyst ?
Well, it started with a cup of coffee, hoping that nothing breaks in the dataflows. LOL. There are no two similar days as a data analyst. Some days, I am challenged with new technical issues in dataflow. Some days, there will be meetings with business stakeholders trying to understand their needs for insights and analytics work that will enable them to make better decisions. Some days are spent in front of a dark screen coding away in Python to complete a Machine Learning project.
3. What are the best parts, and maybe some challenges involved in your work?
The best thing I enjoyed most about my work is the variety. You get to be technical one day and present your insights and recommendations the next day. I also enjoy the creativity of designing dashboards to showcase data. I am constantly challenged and stimulated intellectually with new problems, which makes it interesting.
The difficult part is influencing the stakeholders to take actions on the recommendations. All hard work on discovering data patterns is all gone to waste if it does not bring value to the organisation. Therefore, understanding how to work with different types of stakeholders is also key to bringing impact through data.
4. Data Mining is a buzzword today, but a lot of us are still trying to catch up. With your expertise, what are the upcoming trends you foresee in your domain?
Analytics on demand might be in the near future. We have seen increasingly that companies are automating Machine Learning processes. Similarly with analytics in general, with the tremendous advancement of NLP (Natural Language Processing) and GPT-3, we can enquire any questions about the data by letting the computer learn about all the tables in our database.
5. What message would you like to give someone trying to carve a path in the Data analytics industry?
I believe curiosity and inquisitiveness are the key qualities you should embrace in this industry. Sometimes the problem is so vague or novel that you might know the answer yet. Curiosity will enable you to probe further to understand the questions better. Willingness to learn will empower you with knowledge in new areas that could potentially solve the issue. In terms of technical skills, SQL and Python are two key skills that all aspiring analysts should be comfortable with. These are the enablers for dealing with big data which usually is not as straightforward to mold according to our needs. Being familiar with data structures and schemas will be important too.
6. Lastly, I want to thank you for all the amazing work you do at She Loves Data Community, how has your experience been?
I am currently part of the Data Integration team contributing as a data engineer. I am in charge of bringing in, cleaning, and transforming data from multiple sources so that it is ready for data visualisation. The team aims to understand how much lives we impact and to learn from the past events on what worked and did not work.
It has been a great experience so far. I am surrounded with smart and passionate people with the same goal in mind whom I always learn from. I am always upgrading and being challenged to go beyond the familiar. It has been fulfilling to be part of the journey of women empowerment in the data and analytics industry.