Most Valuable Skills to Get a Data Analyst Job in 2024
Every business today wants to catch as much data as it can. Be it big multinational companies in the IT domain or small businesses in any random realm, everyone in the 21st Century knows how important data is.
Although, raw data, until not processed, is of no use. It is only processed data that will give anyone key insights into what they want to infer.
Whether a company wants to know what items are selling more or what items are not selling much and why? Data, most of the time, have all the answers.
Data is also utilized to analyze customer’s behavior, the growth of a company, its performance, its shortcomings, etc. There is a wide range of problems data can solve.
You probably know who is the person who accomplishes this task of pulling out useful information, patterns, and visualizations from data sets.
Yes, the professional who carries out this process is the one we call data analyst. A data analyst does a variety of chores relating to data.
A data scientist also fiddles with data, but a data scientist is generally more skilled and takes a more scientific and sophisticated approach than data analysts like implementing machine learning, data mining, and python for assessing data.
7 Essential Skills to be a Data Analyst
As you see, a data analyst has got a lot of things to do within an organization, so he must be a skilled individual.
In case you are aspiring to become a data analyst or maybe a data scientist, and you should read this article once. In this article, I am going to tell you 7 essential skills you will need to become an efficient data analyst.
Here we go:
1. Statistics
This goes without saying. As a data analyst, you will jumble with the numbers all day. Profound knowledge of statistics and probability is much required if you want to become an efficient data analyst or data scientist in the future.
If you want to remain resourceful to work with any organization, get some definite understanding of statistical mathematics, multivariate A/B testing, predictive modeling, trend analysis, and cluster analysis.
You should know how to implement these theoretical concepts so that you could deliver practical observations.
2. Problem-solving
Why does the employer want you to collect and explore data? They want an answer to their problems and practical questions, and they believe data has it all. You would need to deliver them the solutions and explorations based on the data set you have. This would not be as easy without proper problem-solving skills.
You would need to think critically about what the problem is?
how could you extract meaningful data to provide an explanation for the problem? In short, you would need to use logic, analysis skills, creative thinking to craft a strategy and solve the given problem.
3. Data management and querying
A data analyst should necessarily know how to manage data. Managing involves everything from feeding data, organizing it to manipulating it.
As a data analyst, you will be dealing with data in a high amount, so you will need to know about required Database management systems.
One such popular DBMS which is extensively utilized is SQL. SQL is an excellent tool for data analysts as it allows them to access, manipulate, or extract required data set from large databases. All this is done using queries probably, why SQL is called a structured query language.
Excel is yet another thing you should know about in detail. Apart from SQL, you might also need to know other technologies like Hadoop and Hiveql.
4. Data visualization
Once you are done working on several data sets to pull useful outcomes, its time to deliver your findings to your boss or organization.
Your boss or colleagues may not be as smart as you to understand the data just with numbers. Thus a data analyst should know how to present data in a way anyone could comprehend it.
A data analyst should know how to make use of charts, graphs, and other visualizations to convey the information in the easiest way possible.
Various computer tools are utilized to draw such graphs, charts, and presentations; thus, exceptional knowledge of such tools is necessary.
5. Communication skills
This is again, obvious. As a data analyst needs to explain his studies, explorations, and findings to others, he should be proficient in communicating his ideas.
Although graphs, charts, and visualization play an essential role in making people understand your points, you can’t expect everyone to understand everything without questioning. If they query, it should be a breeze for you to answer them.
You should know all the practical communication skills to be a professional data analyst.
6. Programming
A data analyst does most of his job on a computer system using specialized software and platforms. Still, sometimes a data analyst may need to use programming languages to perform specific tasks.
Yes, a data analyst may need to code, but what programming language will you need as a data analyst? Out of so many programming languages, the one which is often utilized in data analysis in python.
Learning Python will give you an edge and make you a better data analyst. If you wish to get promoted to a post of data scientist from a data analyst, you must have programming knowledge.
7. AI and machine learning
As a professional from the IT domain, a data analyst should be aware of every trending technology. One such trending technology is AI, and machine learning, AI, and machine learning have got great use in the data analysis domain.
Although data analysts are highly capable professionals, sometimes some tasks are so rigorous to do manually. In such cases, machine algorithms can help.
A data analyst who is proficient in Artificial intelligence and machine learning will be no doubt more valuable than others.
Moreover, he could leverage the power of AI and machine learning to simplify processes or reduce workload. Machine learning could help a lot in performing routine and repetitive processes in data analysis.
Data Analyst Job Description
From collecting data to analyzing it to draw out patterns and information using a variety of tools, data analysts perform a variety of complex operations on data. Filtering data, optimizing it, manipulating it, and the list goes on.
A data analyst also often needs to explain his findings through charts, graphs, presentations, etc.
A data analyst in general works on data and figure out a variety of issues to boost the growth of any organization.
Data analyst salary
Data analysts are in good demand these days, and the salaries they get are also pretty impressive. An experienced data analyst could make $80,000 annually. The exact salaries data analyst gets depend on the organization they are working for and the region. It also depends upon their post and responsibilities.
Educational requirements
The next thing that you might be wondering is, what are the education requirements to be a data analyst?
A bachelor’s degree is often required to get an entry-level job, but if you are seeking an upper-level job, aim for a master’s in the relevant field. Relevant fields may be a degree in mathematics, statistics, or computer science.
Conclusion
These were some of the essential and soft skills every data analyst should possess. One skill that you might find missing in the list is data analysis and exploration.
This is the core skill every data analyst should possess. A data analyst should be able to frame problems, analyze the data, and explore the solution of the problem in databases.
Apart from these, knowledge of industry-standard tools is much necessary. SQL, Hadoop, Excel, as I mentioned earlier, are something you need to know about.
These are just a few tools, and data analysts use a variety of tools to accomplish a variety of tasks. Knowledge of these tools will always benefit you in your career as a data analyst.
With the growing amount of data in the hands of companies, the need for Data analysts is at all times high. It’s the best time to take advantage of the opportunities, learn data analysis or data science, and dive into this lucrative career.
A variety of institutions provide certification courses in data analysis and data science, both online and offline. So if you are interested, finding the right platform to learn is the next thing you should do.
I hope this article showed you the path towards your goal. Thanks for reading, and I hope it helps.