STARTING OUT NEW DIGITAL SKILLS (3)

Being a Data Analyst

It’s SOUNDS time again this month on Talk with Willy. If you missed the older posts on graphic design and on SEO, I suggest you take a moment and just visit them. There’s a lot to pick in those posts, especially if you’re like us, you just want to read, learn new things and try out what catches your fancy. In this post, we talk about one of the most exciting and newly prioritised career path that has recently emerged. In this post, we talk about data analytics.

In this post, we explore what data analysis is, what it takes to be a data analyst, and why you might want to consider, maybe really consider starting a career in data analytics.

Everybody needs data literacy, because data is everywhere. It's the new currency, it's the language of the business. We need to be able to speak that – Piyanka Jain

In our daily lives as individuals, 8 billion people make life and marketing choices and carry out activities. These actions and decisions may seem unrelated to each other, but careful investigation will reveal that they are actually not as unrelated as we may think. There are relationships in the trends of our daily lives that if properly utilised, could be major game changers in the marketplace.

It is here that analytics comes in, studying and processing these seemingly countless data (subsequently called big data), and making sense out of them no matter how confusing and pointless they may initially appear.

So, what is data analytics?

Data analytics can be defined as the process in which raw data is processed, examined, and scrutinised in a bid to observe and record significant trends and gain meaningful insight. Such insights can be your business information, product innovations, market trends, etc.

The collected data can initially exist in three ways:

1. Structured,
2. Semi-structured
3. Unstructured.

This seemingly easy process looks easy when the processed information is displayed as graphs and charts. Unknown to the viewer though is that several tools and frameworks are used in the analysis process.

There is a high requirement for professionals who can help organizations convert raw data into meaningful information, which in turn can help the growth of the business. There are several job roles in the field of data analytics, and among the job pool, becoming a data analyst offers the most amazing career opportunities. So what’s next is understanding how to become a data analyst, and here’s how!  

Some Facts You Should Know

1. The average annual salary of a data analyst in the United States is $62,500 (over ₦40 million)
2. There are less than 1 million data analysts globally
3. Over $215 billion was spent on data analytics last year alone (2021)
4. You can be a data analyst in 6 months*
5. So far, less than 0.5% of all the data we create is ever used
6. Companies generate around 2,000,000,000,000,000,000 of data everyday (good luck calling the number)

Types of Data Analytics 

According to Oracle, there are four types of data analytics. They are:

1. Predictive data analytics (predictive modelling and statistical modelling)
2. Prescriptive data analytics (optimisation and random testing)
   
   
   
3. Diagnostic data analytics (discover and alerts and query and drill downs)
4. Descriptive data analytics (ad hoc reporting and canned reports)

You can read more about this classification system here.

Being a Data Analyst

A data analyst is a person who collects, processes, and performs analysis of data, usually big data. It is the duty of the analyst to mine, process, sort, interpret and finally present data as information for relevant action to be carried out in response to the visible feedback.

As is our custom here, we cover our 5 Musts for the skill discussed, but I recommend that you check out this post by Coursera on Being a Data Analyst

5 Must-Haves for a Data Analyst

I know you already know the format for those who followed the first two posts. For the sake of our first readers, let’s check out the requirements for being a data analyst and see if it’s a good fit for you. Like we always do, you would find certain similar or generic requirements for all skills, especially in terms of mindset and attitude, but the professional requirements are different.

To be a data analyst, you must;

1. Get a Passion

Breathing and eating are probably the only two things everyone was made to do and share with others. Data analytics can be fun, but it is not for the weak of heart and skill. As has been said already, it is a puzzle-solving process that requires you to be good at maths, statistics, data entry and processing, and database management.

All these are imperative when learning and as you eventually practice.

2. Get a Device

You cannot be a data analyst with your phone alone. I repeat; you cannot do that. You would need a good computer that can run your various programs and carry out required tasks. A fine suggestion would be seen in our graphic design posts.

3. Get Proficient in Relevant Software

You are already aware that you need to be good with numbers and programming to an extent to take up a career in data analytics. The ideal candidates for this are graduates or students with some background in Computer Science, Statistics, or Information Systems.

Even if you don’t have a background in any of these fields, you can start out today and push to get some foundation knowledge relevant to the field.

1. Structured Query Language (SQL)
2. Python
3. Matlab
4. IBM SPSS
5. Tableau
6. Statistics
7. Microsoft Excel

4. Get Learning Materials

One thing you should always look forward to in data analytics is practice. Practice, practice, practice, and more practice. In data analytics, it is in handling live projects that you build serious experience and make rapid progress.

You should also check for relevant available courses online that are quite hands-on. Get their notes, and books, and join communities to share ideas and challenges as a data analyst.

5. Get a Tutor

Another thing to repeat from last week: You might take free classes online and that’s fine, we even have a post on where you can learn digital skills for free online, but you absolutely NEED a tutor. A tutor isn’t just a teacher; a tutor is a mentor, a coach, and an expert in the field who is there to hold your hand as you learn.

Free online classes are not tailored to a particular audience, they are for anyone and it’s a good place to start. A tutor is one who especially attends to your needs, personally tracks your progress, and of course, helps you learn in the best way possible.

Speaking as one who has witnessed it first hand, I have seen that it is almost impossible to learn data analytics alone when it comes to being practical. I never got past the first module by myself, I quit, it was too much to take.

If you’d really want to go far as a data analyst, you need a tutor to scale through in a timely and effective manner.

You can have physical or online classes with your tutor, and it is best you take as many paid courses as possible from such a person, because that’s where the true and absolute value lies. You can ask anyone who has taken free and paid courses, and they would tell you the difference.

To know more about the steps to being a data analyst, check out this post on Coursera.

So, now you know more about data analytics than you probably did before you read this post. I tried to be as thorough and as simple as possible, but if it still didn’t work for you, that’s probably a sign that this isn’t what you should give much thought to. It might make more sense in the future, or it might not. Whatever the case, check our other SOUNDS posts to see if there’s something that catches your attention better.

You can always drop your suggestions, questions, or opinion in the Comments section.

Until I bring you another post next week, stay smart.