We all can agree different businesses has different needs. But, think about this.
There are two startups with the same business models and technology starting in the same year. They approach the same market and are targeting at an almost similar audience. They get the same amount of seed funding and even run similar marketing campaigns. But when it comes to growth, one takes the lead and the other remains stagnant (or worse, turn into the follower). Why so?
The answer is actually pretty simple: data. What distinguishes them from each other is their ability to slice and dice data to increase sales and hack the growth of their business.
People say if you enjoy working with numbers and are comfortable with graphs and their stats, then data analyst may be the best career choice for you. But, is it that simple?
Here’s what you need to know towards becoming a data analyst:
What does, exactly, data analysts do?
As a data analyst, your main goal is to maximize the business performance to achieve the growth targets in revenue and profitability. The role of data analyst is crucial because you’ll help the company to make a more data-driven decision. And it’s no secret – big data is the future of everything.
In this job, you’ll work closely with business development manager, marketing executive, and product manager. You’ll help the business development team with their quarterly plan or overall business strategies, the marketing team with their campaign effectiveness, the product team with their development. In the startup scene, you will also work closely with the founders to help them get better insights about the business.
Basically, you’ll help each team member in the company do their job more efficiently. In return, you’ll pick up a good deal of expertise in the industry along the way. If you love learning and solving different puzzles – data analyst is definitely a viable career path for you.
How to think like pro Data Analyst?
In his book “Thinking with Data,” Max Shron argues that the first step of analyzing a data set boils down to three things: vision, mock-up, and argument sketch. If you’re looking to become a data analyst, you must start to think like a data scientist. You have to know what problem that one is actually trying to solve and how you intend to approach & analyze the results.
When it comes to data analysis, it’s critical to start with a solid foundation. In his essay “Are You Solving the Right Problem,” Dwayne Spradlin (2012) wrote that most companies aren’t sufficiently rigorous in defining the problems they’re attempting to solve. Instead, they speed toward a solution, fearing that if they spend too much time defining the problem, they will get a late start. Unfortunately, this approach more than often wastes not only their time but also money and even reduce the chances of their success.
Before the data mining process, it’s important for you to write down very detailed objectives. Further after writing the plan, you need to build predictive models or mock-ups. Modeling, in this case, is the act of building set questions where you know the answer and then applying it to another situation that you don’t. And after that, you need to create argument sketch to identify all of the possible risks. By approaching this method, you’ll be able to measure and manage every result. No more unpredicted failures.
How was a typical day in the life of data analyst?
Data analysts spend most of their time in the office setting. You’ll be in charge of managing the progress and overall business performance. Your day-to-day responsibilities will be related to data mining. This includes constructing a database and keeping track of various types of information. Also, solving different kinds of puzzles from your team. You’ll challenge yourself to solve the problems in the quickest time possible.
Now that you have a clear idea of what a data analyst do, and how important they are for the business growth, it’s time for you to build a portfolio that shows your skills to future employers. Have no degree in mathematics, engineering, or IT? Don’t worry! You can start from any industry you like – your knowledge and experience in problem-solving always count. Yet, remember some coding skills will make you stand out and more marketable in this career path.
P.s. This post originally appeared on the Glints Singapore website (as a basic guide for data career) and has been updated here for comprehensiveness.