Having the necessary skills is essential for securing desired positions in the field of data analytics in the fast-paced business environment of today. Professionals with these skills are in great demand as businesses continue to use data to inform strategic choices and obtain a competitive edge.
In this article, we look at the expertise that can lead to a prosperous career in this fast-paced industry by examining the in-demand data analysis skills in 2024.
Skills for Data Analytics Professionals
LinkedIn’s 2024 Most In-Demand Skills list and The CompTIA research list data analytics as one of the top 10 in-demand skills in 2024. Let’s have a detailed look at the technical and soft skills needed to enter and succeed in the data analytics field.
Technical Skills for data analysts
1. SQL
The standard language used to communicate with databases is Structured Query Language, which is also called SQL. This means that if you know SQL, you can manipulate data in relational databases by updating, ordering, and querying them as well as modifying (schema) the database structures.
For most people who want to analyze data for companies using their databases, they must be familiar with SQL; it’s probably the first thing they will want to learn before getting hired. Many times companies screen candidates on their technical skills related to SQL during an interview of a Data Analyst.
A bright side though is that learning this language is relatively easy. So if you are ready to learn SQL, Techcanvass has a perfect offering, which is the fundamental course on SQL. The course covers SQL basics, simple Joins including Outer and Inner joins, SQL functions, and much more. The objective of the course is to make you learn and understand the Basics of SQL efficiently with hands-on practice sessions.
2. Python and R
Programming languages such as Python or R enable one to perform complex analysis and apply algorithms. Programming in these languages allows you to clean, analyze, and visualize large datasets more efficiently.
Both are open source and it’s a good idea to learn at least one of them. Arguably, there is a debate about which language suits data analysis better. Both languages can do similar data science tasks. The design of R was for analytics alone while Python is more general and usually easier to learn especially if it is your maiden language.
3. Probability and Statistics
Mathematical science, the gathering, analysis, interpretation, and presentation of data is referred to as statistics. It is something that sounds like the kind of thing a data analyst does.
You can employ the concepts of probability and statistics to:
- Detect patterns in data.
- Avoid bias, fallacy, and logical error while analyzing it.
- Give precise and reliable outcomes.
4. Data Management
Data management is about collecting, organizing, and efficiently storing data with security considerations and within budget limits. Although this may include positions like data architects/engineers, database administrators, or information security analysts on some companies’ organizational charts, many times it falls under the purview of the data analyst himself/herself.
Different firms have different systems that they use to manage their data. Having a general understanding of how databases work in physical as well as cloud environments can be beneficial when developing your abilities.
5. Data Visualization
One should point out that drawing insights from data is only one part of the process of data analysis. A second crucial aspect is using these insights to create a better understanding for making sound decisions in business. That’s where data visualization comes in. As a Data Analyst, you can use charts, graphs, maps, and other visual representations of data to explain your findings easily.
Therefore, learning visualization software such as Tableau or Power BI can enhance your abilities as a Data Analyst.
Are you looking to learn Tableau or Power BI? We bring to you the Tableau fundamentals course and Microsoft Power BI Certification course.
6. Artificial Intelligence and Machine Learning
The World Economic Forum Future of Jobs 2023 (Page number 6, second column) report states that “AI and machine learning specialists top the list of fast-growing jobs.”
Data science has seen Artificial intelligence and machine learning as two of the biggest trends. The skills involve coming up with algorithms that allow big data sets to uncover patterns over time while improving their degree of precision.
Explore – What is artificial intelligence? And What is machine learning?
Not all Data Analysts have to be Machine Learning experts though. However, you could gain an edge among your peers by developing those capabilities and setting your sights on becoming a data scientist later in life.
7. Econometrics
In econometrics, analysts employ statistical and mathematical models based on historical economic information that helps them predict future trends. Knowledge in econometrics assists financial sector job seekers especially those within investment banking and hedge funds who are also interested in Data Analyst positions.
Soft Skills for Data Analysts
LinkedIn’s 2024 Most In-Demand Skills list includes the following skills as three of the most
8. Problem Solving
We are living in a world, characterized by innovation, AI like new tech trends, and ever-increasing customer demand. Leaders, strategists, and employees will be expected to address and solve problems than ever before.
Problem solving is a five-step process. The steps are:
- Define the problem.
- Generate ideas.
- Evaluate and select solution(s)
- Implement
- Evaluate and improve.
Having the ability to solve problems using critical thinking and analytical reasoning is a skill to master.
9. Communication
Communication is key to solving problems. Helping the clients understand and find the root cause of the problem, beyond the symptoms, can be achieved through communicating effectively. Communication also matters in helping the clients translate complex trends and data into actionable insights.
Communication skill is about the verbal skills alone or how good you are in verbal communication? So, what does communication skills mean? Communication skills include the following skills:
- Active listening
- Adaptability based on stakeholders
- Confidence
- Presentation Skills
- Giving and receiving feedback
- Empathy
- Respect
10. Teamwork
The Success of any initiative depends on teamwork. Teamwork is all about a group of people working together to achieve a common goal, small or big.
Teams are made up of human beings and making the teamwork towards a common goal is key. As a Data Analyst, you should strive towards achieving the optimum teamwork.
How do you identify if you are working with a great team? Here are a few characteristics:
- There is clarity and fairness in decision-making.
- Team members feel free to share ideas or share their feedback
- Mistakes are not treated as disasters, if not often repeated. Rather these are treated as humane.
- Team members are willing to help each other, whenever needed or whenever they can.
Summing it up
In conclusion, mastering the in-demand skills outlined in this article is crucial for anyone aspiring to excel in the field of data analytics in 2024 and beyond. By honing your technical abilities, such as data analysis and machine learning, and cultivating soft skills like communication and problem-solving, you can differentiate yourself as an asset to any organization.
We can help you in mastering these skills specially the technical skills. Our Data Analytics certification course is a hands-on training covering all the skills. Most importantly, the course includes case studies and real-life projects to get you practical experience and make you confident.
