Marsha Lulu is passionate about data analytics and has specialised in digital publishing and social media analytics. Her role revolves around understanding East Africa’s digital audiences with analytics and transforming it into actionable insights and recommendations for the BBC East African digital teams. She has over eight years’ experience in data and analytics and has worked at various organisations in Kenya and England.
How did you end up in this career?
It is perhaps a cliché to say I have always known what I want to do with my life, but that is really the case. When I first studied Database Technologies during my BEng. Software Engineering course at the University of Sheffield and later Database Systems and Administration in my MSc. Information Technology for Management at Coventry University, I fell in love with data storage systems. I specifically felt drawn to the extraction and transformation of data with Structured Query Language (SQL) programming.
I immediately knew that I wanted to dedicate my life to working with data. Since then, I have had the opportunity to work with data end to end for over 10 years, at numerous data related positions across various industries. I have since worked my way up to a leadership position as a Growth Editor, at world’s largest media house, British Broadcasting Corporation (BBC).
In a nutshell, what does your job entail?
I translate data into plain English and discover useful information. Every business collects data, whether its sales figures, audience research or operational costs. A data analyst's job is to take that data and use it to help organisations make informed (better) business decisions.
What personal attributes would make one successful at this job?
One needs to be a good communicator – that is, be able to tell a story with data, yet keep it simple and actionable for non-technical audiences. Secondly, one needs to be a people’s person—a good analyst must be comfortable in networking and collaborating with a whole range of people at different levels of an organisation.
Lastly, one should be creative with data and pay attention to detail to avoid mistakes/errors, which could be detrimental.
Apart from going to the University for a Degree and a Masters, what else does it take to be a good data analyst?
You have to be passionate about data and constantly evangelise to the unconverted about the power of data analytics. It’s equally important to keep abreast with the latest analytic trends, tools and skills.
Did you actively choose to go to study abroad? What informed this decision?
Yes, and that was because at the time software engineering as a course was not available on the continent.
What kind of university student would you say you were?
Like any other student, I worked hard and played hard too. Well, my time was clearly mapped out for me because I worked part-time which means, my time in university was not exactly typical because I did not have much free time to speak of.
What courses would you suggest for someone who wants to become a data analyst?
These days there are undergraduate, postgraduate and short courses in Data Analysis, Business Analytics and Data Science.
What has been the most challenging job for you so far? Why?
Every role comes with its challenges. I found it difficult in my former roles, to convince the organisation(s) I worked for to manipulate data through deep dives and use insights to make informed decisions.
That has improved, with more organisations realising the value of data. But I believe these challenges have made the person I am today.
How important would you say mentorship is, in the life of an aspiring data analyst? What are the best places to meet mentors?
Mentors in the field are hard to come by, however, everyone I have worked with has been a mentor in one way or another. I acquired most of my skills on the job that is from compelling Power-point presentations, to just enough statistics, to influencing others and data story-telling.
How does data analytics transform business from a digital angle?
It simple, businesses or individuals are less likely to make the wrong, usually expensive decisions when they use data. What can be better than that?
From your observation, what is the women representation in this field?
I am not sure, from where I sit but a quick analysis from my network of friends and work colleagues, I’d comfortably say this field is mostly male dominated.
Is this an area that you’d recommend to a young person?
Certainly, it’s still a niche field.