How I Transitioned into Data Analytics from Web Development

Recently, I’ve had too many people ask about my transition into Data Analytics and I figured it’s best to write this blog to document my journey. In this maiden blog post, I’ll be sharing with you why I decided to learn Data Analytics and how I pivoted into Data Analytics from Web Development. In another post, I will share with you how I started, what the journey has been, some learning resources to get you started, and also general ideas on how to master your craft and improve your skills in data analytics.

How it started

I studied Computer Science at Federal Polytechnic Bauchi, then later at the University of Jos, Nigeria, and got a specialization in Web Development. I’ve always liked working on databases and I enjoyed the idea of being able to create something that awesome through which I could store up data, retrieve, and manipulate it as I wanted. But not until the end of 2016 that I gave thought to the buzz of big data and data analytics which was fueled by the huge amount of data now being generated and the need to gain actionable insights from these data.

Having worked a lot as a freelancer helping many local entrepreneurs transcend from analog to digital ways of doing business and also helping modern entrepreneurs launch their personal brands so that they can grow income and create a bigger impact with their work, I’ve seen the wonders of data and how valuable insights from it can drastically change the trajectory of any business.

I build most Small and Medium Enterprise (SME) websites on WordPress followed by an immediate integration of site analytics and search engine optimization. I like the data gathered from the first week of the website launch to the progress reached by the sixth month. The insights from these data always help a great deal in maintaining and scaling the website. And that was partly my motivation into becoming a Data Analyst.

Factors such as website traffic and user behavior while on-site were very important to me as a web developer – whether it’s measuring the search volume of keywords, examining reasons behind the bounce rate, or analyzing the number of website visits in a given month.

I enjoy working with numbers and statistics which makes it fun for me to identify trends and patterns in data. I work with tools such as Tableau, SQL, Microsoft Excel, Google Analytics, and Python to do this. I know which tools are best suited to which types of data. I work by condensing large pieces of information into small, bitesize chunks that let stakeholders digest it quickly.

With a background as a web developer, I know what developers need from analysts. I collaborate with Web developers and other team members on projects by providing insights, answering tough analytical questions, and creating reports in a concise way to help simplify the needs of other team members. I also help developers to understand when their goals are being met. This is a crucial factor where these teammates collaborate. If a business has a target to increase traffic by 30% quarter over quarter, it is my job as an analyst to report on the figures. This information can then be used by a developer – perhaps in collaboration with other team members such as a UX designer or business manager – to know whether or not they are on track or reached this target. Understanding the overall performance of any website or app is essential to its growth.

I study the performances of websites and apps and present insights to developers helping them to make decisions about how the website should be built and maintained. Data is also often used to plan around future performance and is key in defining growth objectives for a business, as a Data Analyst, I am responsible for keeping everyone informed in relation to their progress towards these goals and objectives.

The Advantage

My knowledge of SQL and other programming skills gives me a leg up over most other analysts. Most analysts I have seen can use excel and some basic BI tools but can’t string together solutions to more complex problems and get stuck doing manual work a lot that could be done better.

A background in a few programming languages opens possibilities for me to create unique solutions that others won’t know how to do. I’ve realized there is frequently a need from organizations for people who can spin up technical solutions when IT inevitably is unable to provide support for some project the business wants.

Conclusion

Overall, data work or tech, maybe even life itself if we’re being philosophical, is definitely about constant learning. There will always be new tools and new novel algorithms to learn about and study, but the biggest thing that everyone needs to figure out early on is how to learn and to be bold enough to move when the time is right.

Are you interested in learning more about Data Analytics? Share your thoughts in the comment section below.