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7 Signs That You'll Be An Amazing Coder

Data analytics is one of the hottest industries of 2020, and many are thinking of learning coding or switching jobs to become a data analyst.

If you're one of these people, read more to find out if you have the traits to succeed as a data analyst, business analyst, data scientist, and other similar coding or analytics related roles.

1. You are detail-oriented (or don't hate double checking your work)

data analysts looking at charts and graphs generated with data visualisation techniques

When coding, errors can be caused by different factors; the smallest mistakes (e.g. a missing semicolon, extra space, or improper capitalisation) can create issues for your code, and others (like poor code formatting and management), can slowly accumulate and cause bigger problems down the road.

The nature of coding and programming thus gives detail-oriented individuals a natural advantage when coding and/or analysing data.

But that doesn't mean that you can't be a Data Analyst or Programmer unless you're detail-oriented.

You just need to get used to double checking your work and keeping an eye out for common coding mistakes made by programmers.

Ultimately, this minimises the time wasted and frustrations from your coding project, and is a good practice to have regardless of the programming language you use.

2. You like working with numbers

data analyst looking at spreadsheet

Since much of the data we work with are numerical or will be converted to numerical values, working closely with numbers is inevitable.

If you're someone who loved math in school, like handling data (e.g. through Excel) or just don't mind working with numbers, that's great – data analytics will probably be a great fit!

Worried because you don't have a background in statistics? The good news is, data analysts don't actually need to be masters statistics or math.

Yes, you read that right.

Beginner or entry-level data analysts will only need to understand basic statistical concepts, like probability and regression, to start; the nature of the role does not require intensive statistical knowledge.

However, those looking to pursue specialisations or become an expert coder will eventually need to understand and apply statistical concepts well to thrive in such positions.

3. You're a great storyteller (or are willing to be better at it)

data storytellers

Many people think data analysts just need to find the meaning in data.

That is only half true.

Of course, you'll need to have a complete understanding of the data. To do this, data analysts often use Descriptive Analytics, Diagnostic Analytics, Predictive Analytics and Prescriptive Analytics.

In layman terms, these are the manipulation and analysis of data to:

  • Explain what happened

  • Understand why it happened

  • Predict what can happen, and

  • Find out what stakeholders can do next

But that's not all.

Often, coding and/or analysing data well is not enough – you will also need to communicate your findings in an engaging way that allows your audience to understand key points easily.

That is because your findings – regardless of how interesting and significant they are to the world – cannot reach their full effectiveness unless they are easily understood by your main audience.

You thus have no choice but to be great data storytellers if they want to thrive in their role.

4. You love solving puzzles and being a detective

solving puzzles as a data analyst

Companies use data analytics and coding to achieve different objectives, like identifying new opportunities, improving processes, increasing customer loyalty and more.

This is why as a programmer, your main goal isn't to write code – it is to solve problems.

To do this, you need to coax your data to get the information needed to help decision makers and/or stakeholders meet certain business objectives.

Let's put it this way: You need to complete the main puzzle, which is the completed report or analysis that stakeholders will review and use to make decisions.

When you receive raw data, all you get is the scrambled puzzle, and other than arranging all pieces, you may also need to find some missing pieces.

Here's where the detective work comes in.

How do you place all these puzzle pieces in the right spot, and where on earth can you find the missing pieces needed to complete your puzzle?

You'll need to answer some crucial questions, like:

  • What data do you need to collect?

  • What data analytics tools and techniques should you use to get the insights needed from your data?

  • What types of data visualisation techniques will be the most effective at communicating your data to stakeholders?

  • What problems will you face throughout the process (e.g. when coding or visualising data), and how do you solve them?

  • How do you ensure the highest chances of success and profits for your company?

By answering these questions, you slowly collect the missing pieces, and by completing each step of the process, you are a step closer to solving the puzzle – and reaching your objective.

5. You believe in lifelong learning

lifelong learning ladies studying data analytics

Data science, data analytics, and coding are constantly evolving industries, and even coding experts have to continuously learn to stay at the top of their game.

As a coder, you can be a lifelong learner in a variety of ways, such as incorporating best practices when coding, reading about top research-backed skills and competencies that data analysts should have, and even learning a new coding language.

Even if you choose not to join the industry, adopting a mindset of lifelong learning will be highly beneficial to both your personal and professional lives.

Through continuous learning and self-improvement, you can protect yourself from economic recessions, gain a sense of fulfilment, increase your creativity, and even become more socially engaged.

6. You are (or want to be) resilient

data analytics project in progress

At some point in your coding journey, you will reach a point where, no matter what you do, you just can't find the error.

Sometimes, you'll need to ask for help from coding communities (e.g. online, friends, or, if applicable, classmates from previous data analytics courses), or you'll need to just take a break and go back to it again.

For some, this takes days. Others, months.

Now imagine what it'll be like when you add on other issues like poor quality data, overly demanding stakeholders, and tight deadlines.

In a role where challenges and obstacles are common, resilience is a crucial trait and a great sign of success.

If you're not? Work towards becoming more resilient.

Regardless of industry, the resilient are more likely to succeed because of their ability to handle stress and treat adversity as a learning opportunities; it is a great trait to have even if you choose not to pursue data analytics or coding.

7. You are interested in coding

data analyst having fun with data

In our opinion, an interest in coding is the most important sign that you'll succeed; it is so important that we'll tell you to go ahead with learning how to code even if you don't have any of the other traits above.

Do what you love, and you’ll never work another day in your life.

Many may be enticed to be a data analyst or learn coding for the money – data analytics is a very lucrative industry – but it will be extremely draining to do a job you won't enjoy just for the money.

But does that mean that you shouldn't pursue coding if you have no interest in it?

Well... Not really. In the digital age, everyone needs to learn coding and data analytics; with the huge volumes of data that the world generates, you'll eventually need to learn some basic coding and data analytics skills to stay relevant in the digital age.

The good news is it doesn't have to be an all-or-nothing scenario – you're free to pursue incorporate coding and data analytics skills in your current job scope too!

For example, you love your job in recruitment and Human Resources. Instead of switching to a data analyst role, you can use HR Analytics or People Analytics, or the use of data analytics for the HR function, to improve performance in your current role.

By pursuing a hybrid role like the above, you ensure that you can continue doing what you love with a much lower risk of being obsolete with technological disruptions.

At Gen Infiniti Academy, we help graduates gain technological capabilities and internationally recognised certificates that allow them to thrive despite technological disruptions. Find out how you can differentiate and brand yourself as a digitally ready employee with our data analytics course.


Written by: Chloe Thio (Gen Infiniti Academy)

Illustrations by Freepik Stories.

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