The first steps to becoming a data analyst can be daunting.

But I know from experience that there are very few career paths which are quite as varied or rewarding. You’re going to learn an awful lot in your career. Indeed, you cant afford to stop learning new technologies & techniques.

But there are some fundamentals, some basics you need to know no matter who you are. So below are the essential skills any aspiring Data professional must know.


Learn to love Google

Don’t laugh. This is probably the worst kept secret among every top-level developer and analyst you’ve ever met.

I can’t tell you how many junior analysts I’ve trained who felt silly for relying on Google too much, but they really shouldn’t! Google is your absolute best friend. Before you learn anything else learn how to lean on it.

That question you have in your head? Write it out word for word and someone else has had the same thought, and someone, somewhere has answered it. For nearly every skill I’m about to talk you through, Google will be the primary tool you’ll use to get better at it.

Check out the Google Garage for free digital skills training.



Domain Knowledge

You may think it strange that the first skill I recommend to new data analysts isn’t ‘technical’. But as a leader for 15 years I can say with confidence, the best team members know ‘business’ well. The reality is that working with data means providing value to people who want to do one, or both, of two things.

In private organisations either ‘make more money’ and ‘spend less’ , and in public bodies, ‘Do more’ and ‘Spend Less’.

But the ways in which organisations do these two things is almost limitless. I’ll list a few below.

‘Make more money’ / ‘Do more’
• Optimise Marketing Spend
• Target Sales Efforts
• Improved Product Development

‘Spend Less’
• Increase Operations Efficiency
• Reduce IT spend
• Optimise Head-count

At the beginning of your career if tasked with analysing data in the areas above, where would you start? If you were anything like me you’d rely on your manager or the specialists in each area. Its obvious that you need to lean on their domain experience to get the job done, but don’t be reactive! Don’t wait for marketing to ask a question to start learning about marketing so you can answer it. Be proactive!

When you start as a data, analytics or insight professional spend every spare moment learning about the business. Ask to shadow team members across different departments. Ask to attend appropriate meetings so you can learn what matters to different teams. Immerse yourself in team specific newsletters and insights generated by other areas. Google your industry and read, read, read!

If you want to add value for your customers, you need to think like them.



Every job specification you see mentions Python or one of its equivalents. Youuve probably ordered “Learning spark: lightning fast big data analysis” from Amazon or slugging your way through “The data warehouse toolkit” because you think you have to.  But if you are beginning then I would still recommend mastering Excel.

This may be the nerdiest thing I’ve ever said, but for me, Excel is one of, if not the greatest software ever made. Other than email, I’m not sure if there is a piece of software which has had as big an impact on business. I love it!

And the reality is no matter what your job title or the specialisation you get into, you are going to be using Excel. A lot! Sure, in time you are going to become a Python expert. But Excel is where the fundamentals of data manipulation and analysis are learnt.

There is still no tool available which is as easy and useful in doing quick and dirty analysis / visualisation and so trust me, master it.

Learn Vlookups and Hlookups. Make Index and Match Second Nature. Immerse yourself in Pivot Tables. Understand If Statements and other useful Excel Functions. Begin learning Power Query.

Excel is where the ability to conceptualise data analysis & manipulation techniques is born. These skills make further learning of SQL, Python etc easier to understand. Don’t underestimate Excel’s importance.



I’ve trained and managed 40+ data professionals of varying experience and specialisations. And the skill gap which has the biggest negative impact on their advancement was SQL. I loved SQL tutoring, because it made my life easier as a manager and moved my staff’s career for the better.

Ask anyone who knows SQL and they will tell you…”its simple”. And believe me it is. However, ask some people who don’t know it , and they struggle with beginning the journey. Perhaps because they worry its a leap in understanding.

But the truth is, SQL is not some intermediate skill you can get around to knowing, its actually one of the basics. Its fundamental to your ability to Extract and Transform data for further analysis. Its also essential in many automation tasks you may want to complete.

But don’t worry. Once you’re able to conceptualise data manipulation (from mastering Excel) learning SQL is much easier. Its something which takes practice and direct real-world exposure. so take every opportunity to use it in your current organisation.

Be sure to cover Sum, Average, Count and other arithmetic functions. You are going to need to know Group by, Order By, Where, Having Clauses. Case Statements are also essential along with learning Joins and Unions.

These are the basics and will cover 75% of everything you will regularly use, even later in your career.



I’m not sure how many other people recommend PowerPoint as part of learning Data Analysis. But I recommend this one not because it makes you a better data analyst. But because (unfortunately) you are likely going to be using it a lot.

When you deliver an insight, some data, or a visualisation at least half of the time its going to end up in a PowerPoint. And when you are starting out, guess whose going to be building that Slide Deck?!

Practicing and becoming expert in PowerPoint has two benefits. Its going to save you lots of time in the long run. Because now you’re an expert, you wont be messing around resizing images and realigning text. Secondly, the quality and impact of your presentations will increase. Which benefits the last and perhaps most dreaded skill you need to learn!


Public Speaking

First the good news. Because you’re going to be doing interesting and important work you’re going to have a great career.

Now the bad news. Because you’re going to be doing interesting and important work you’re going to have to stand up and talk about it!

Public speaking is hard. But the truth is that its an unavoidable part of your job if you are to go as far as you can in pretty much any career, but especially in data. At some point in your career you are going to come across scenarios such as:

  • Having to defend your numbers or method in a meeting
  • Debate with a group of stakeholders about the interpretation of data
  • Stand up in front of a large group to explain your findings
  • If you want to lead…present, present and present some more.

Listen, I hate public speaking. I’m an introvert by nature but I would never have gotten where I have, if I didn’t ignore my true nature and fight through the fear. That fear never disappears, but it does get a lot easier. You just need to jump right in. That’s what I did, and now I’m not bad at public speaking, and some have even told me I’m actually quite good!

You can absolutely build a successful career without public speaking, many people do. But it makes life so much easier if you immerse yourself in it as much as you can, as early as you can. Its hard, but its worth it.


So there you have it! That’s my list of the basic skills anyone starting out in Data needs to develop. You’re going to learn an awful lot in your career, you can be sure of that, but these are the skills you’ll need to give yourself the best possible start!

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