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15 Key Data Analyst Skills You Need to Get Hired
Research shows that the big data and business analytics market will jump from 215.7 billion US dollars in 2021 to $274.3 billion in 2022. The staggering growth was expected, given the 2.5 quintillion bytes of data generated daily.
The rapid expansion gives an opportunity to develop data analysis skills to enter the field. Digital transformation is on the rise, and competent data analysts are in high demand.
Businesses need talented individuals to manage their data and drive helpful insights. Know the 15 key data analyst skills you need to get hired and earn a spot in the booming industry below.
You need a significant amount of training and effort to reap the rewards of a career in data analytics.
You must have specialised technical skills to impress a hiring manager and thrive in the growing industry. Therefore, knowing what a data analyst does is crucial to gaining and honing your skills.
A data analyst is responsible for converting raw data into meaningful information. Plus, they’re also required to get rid of unnecessary data, access data quality, and share the reports with a firm’s stakeholders.
All these tasks require you to have a set of hard skills. The primary ones to focus on include the following.
Regardless of how proficient a data analyst is and the advanced technology they have at their disposal, they must know how to work with a reliable tool like Microsoft Excel to manage data.
You might not find Excel in the job description of some hiring services; many businesses use it nonetheless. The platform automates certain features to optimise your data analysis tasks.
For instance, VBA, its programming language, helps run pre-recorded and macro commands. If used effectively, the platform’s programming language can save the time you otherwise invest in manual and repetitive tasks like project management and payroll.
Therefore, knowing how Excel works helps you expedite tasks as a data analyst.
2. Data Visualisation
Data visualisation means your ability to present valuable insights in the form of charts, graphs, and illustrations. The purpose is to help people understand the insights extracted from the data.
Not everyone working in a company is trained in data analysis or has technical knowledge. Even more, you’d need to work on your data visualisation skills big time if a company's decision-makers are non-technical.
An organisation’s decision-makers must understand complicated ideas at first glance. So, you have the power to convey helpful information and shape a company’s future as a data analyst, but only if you know how to present the data intriguingly.
It wouldn’t be wrong to say that your data visualisation skills can help you achieve more than a data analyst does traditionally. It’s because it gives you the ability to observe the data differently, uniquely, and creatively.
The deeper you dig into the data, the more value you can provide to the company. So, you may empower a business more than your fellow data analyst because of your excellent data visualisation skills.
You must be familiar with a few database languages as a beginner in the data analytics field. Although firms do not expect you to be fluent right off the bat, you must know the fundamentals.
Structured Query Language (SQL) was established in 1970. Although relatively old, SQL remains a popular database language today.
It helps handle and examine data in relational databases. However, because the data analytics industry is constantly transforming, one may wonder what’s the point of investing in an old-school database language.
Josh Devlin, a Data scientist, argues that data analysts might wonder why they should invest time learning an old-school language like SQL rather than mastering more trending languages like Python/R.
However, the professional follows his words by mentioning that overlooking the importance of SQL will make it challenging to land a job in a data-related field.
In all honesty, most companies today use SQL, given its practicality and effectiveness. Besides, there’s no chance of its popularity fading any time soon.
So, make sure you get grips with SQL before applying for data analyst jobs.
4. Data Cleaning
Research unfolds that data cleaning comprises 80% of the work of most data experts. Although daunting, time-consuming, and somewhat boring, data cleaning remains integral to a data analyst job.
A data analyst harvests data from one or several sources and prepares it for analysis. Of course, the retrieved data is in raw form and unorganised. They must clean it to make it more structured and understandable.
You can derive surprisingly valuable insights from the simplest algorithms when you have a properly cleaned dataset.
Uncleaned data, on the other hand, can lead to miscalculations due to wrong patterns.
As a result, it may negatively impact a business’ decisions. So, you must hone your data cleaning skills, and every company expects you to be proficient with data cleaning.
5. Statistical Knowledge
Statistics and probability are other key skills required as a data analyst. This knowledge will guide you through data analysis and exploration and enable you to convert it.
Besides, statistical knowledge helps you check your data analysis for validity. For instance, you can determine if the driven data is accurate or not. This helps you avoid errors and miscalculations associated with data analysis.
How much statistical knowledge you must have varies depending on the data type, company, and particular role.
For instance, if an organisation relies on probabilistic analysis, you’d need to have an in-depth understanding of statistics and relevant knowledge.
6. Machine Learning
Although machine learning isn’t a skill like learning data visualisation and SQL, you must understand it to stand out from the crowd and earn a spot in a competitive data analysis landscape.
Machine learning has become one of the most critical developments in data science, and businesses rely on it to improve data accuracy.
Although you do not need to master ML as a data analyst, understanding the basics will give you a competitive edge in your career.
Knowing how Python works should be your priority as a to-be data analyst. Python earned a top spot in IEEE Spectrum’s 2019 roaster of leading programming languages for the right reasons.
The programming language has an impressive amount of libraries. Most of them are AI-based, which is a plus. Studies unfold that AI software has an astounding year-over-year growth. The market is expected to reach $387.45 billion in 2022.
Therefore, understanding Python has become a necessity in an AI-concerned workspace. It will help you stay abreast with the current trends and see how you can implement them for a company’s success.
Additionally, you can look into NumPy and Pandas to further your understanding of Python and how you can utilise it in data analytics.
8. Data Management
Data management requires you to collect, organise, and store data to make it more effective and secure.
Although a few companies hire engineers and data architects to handle data management, others may assign related tasks to data analysts. Therefore, having data management knowledge doesn’t hurt, as it may help you scale.
Different organisations use varying data management systems. So, as you acquire your skill, it’ll help you understand how databases work in the cloud and physical environments.
9. Domain Knowledge
Domain knowledge refers to the knowledge of the industry you work with or plan to work for. A company naturally expects you to know how a specific industry operates.
For instance, if you plan to work with an e-commerce brand, you must understand e-commerce.
Likewise, you need to know how the systems function if you plan to analyse data for mechanical systems.
While you can always hone domain knowledge at the job, acquiring knowledge beforehand will make you a more passionate candidate and an enthusiastic employee.
Nothing intrigues companies more than when applicants demonstrate knowledge about the company they’re willing to work with. So, ensure to nail your first impression.
Technical talent alone doesn’t guarantee your success as a data analyst. You also need a handful of soft skills to land a reliable data analyst job.
According to BBC news, companies today crave soft skills; the case isn’t any different for the firm you want to work with.
Here are some non-technical industry-specific skills you need to be a successful data analyst.
10. Attention to Detail
A data analyst job requires you to search for a needle in a haystack. You must be good at noticing small things that others overlook.
The tiniest details can point toward a significant message. The key is to find valuable insights hidden in large datasets. Humans are excellent at understanding the intentions behind an unclear question.
Computers, however, aren’t skilled at interpreting vague problems. Here’s where companies require data analysts with great attention to detail skills to spot problems and offer solutions.
11. Communication Skills
What’s the point of extracting insightful data if you fail to explain it to others? To help companies improve their strategies, you must actively communicate with stakeholders and the management team.
You are required to explain the meaningful insights to those who hold technical expertise and those who don’t.
The ability to address technical points and provide in-depth explanations demonstrates your communication skills. Albert Einstein quotes, “If you can’t explain it to a six-year-old, you don’t understand it yourself.”
While we cannot take the quote precisely, it sheds light on the importance of making things more understandable.
12. Problem Solving Skills
Most data analytics is about problem-solving and understanding the right questions. As such, you must have effective problem-solving skills to thrive as a data analyst.
You'll get the required answers if you ask sensible questions related to a product, business, or industry.
Data analysts are presented with a problem - why aren’t we getting more customers? - and are required to investigate the root cause of the issue.
You must have the ability to logically think through a situation and come up with appropriate solutions. You’ll likely perform the task well if you know the subtleties of the data.
For instance, what could be the reason a company isn’t getting more customers? Is it because of substandard product quality or compromised customer service? Digging into various problems will help you get an answer to your question.
You do not work alone as a data analyst. Instead, your job requires you to collaborate with people in various positions.
For instance, you may work with data scientists to determine the types of problems that could be solved through data analysis. You may also work with web developers to discover if their brand’s website is appropriately designed to capture the desired data.
Plus, you must also collaborate with the management team and business leaders to share how the latest data insights can help a company improve.
Therefore, working on your teamwork skills will help you gain acknowledgement at the workplace and make your analytics-related tasks more efficient.
14. Critical Thinking
A glance at the data is not enough. You must understand its implications beyond the figures. Critical thinkers can identify patterns, analyse the data, and retrieve actionable information from the available data.
It enables you to go the extra mile and apply your understanding instead of simple processing.
Becoming a critical thinker can be challenging. However, you can sharpen your skills by challenging yourself.
Think beyond the usual when doing an analytical task. For instance, ask yourself about the meaning behind the pattern you see. Likewise, question the shortcomings of the data, and so on.
So, ensure you pay attention to honing your critical thinking skills if you desire to further your career as a data analyst.
An inquisitive mindset inspires data analysts to look for answers to address business issues. This lets them go beyond the initial assumptions.
Intellectual curiosity helps present solutions to known problems and unmask hidden insights. Consequently, data analysts extract quality knowledge from the data.
If you’re someone who looks to the other side of the picture and is naturally curious, it’ll help you in your data analyst career.
Acquiring Skills as a Data Analyst
After knowing the most sought-after data analyst skills, you’ll naturally wonder how to acquire them. Glassdoor, a popular Job search site, suggests the following ways.
Take an online course. You can learn anything from technical skills like python programming to soft skills like critical thinking by taking a reliable online course.
Get a mentor. A mentor could be a friend or a professional data analyst who can tailor the learning to make them fit your unique needs. This will help you polish your soft and hard skills efficiently.
Practice with a friend. You can always improve your communication and teamwork skills with your friends. They’ll offer you friendly advice on how you can improve your skills.
Ask others for feedback. Connect with your existing colleagues, teachers, and peers to learn about your strengths and weaknesses. Think about your shortcomings and implement the feedback to hone your skills.
Which Skills are Important as a Data Analyst?
A blend of soft and hard skills is critical to landing a suitable data analyst job. You must have SQL knowledge, data visualisation, machine learning, and Python programming skills. Besides, a handful of non-technical skills like critical thinking and communication are also crucial.
How to Develop Data Analysis Skills?
You can develop your data analysis skills by practising with real data projects and setting aside time to polish your skills. Besides, join an online data community to learn from experts in the field.
Getting a data analyst job without essential skills is tricky. Therefore, we listed 15 key data analyst skills you need to get hired.
You need a combination of soft and hard skills to boost your value and prove your worth as an aspiring candidate.
Besides, a relevant course on your resume will surely capture your employer’s attention.
UCD Professional Academy offers several data analytics courses to teach fundamentals and help you gain an in-depth understanding of data analytics. A course taught by field experts increases the likelihood of standing out from other applicants and advancing your career.