A high emphasis is given to data in today’s world and understandably so. The report shows that there are over 2.7 Zettabytes of data present in the world of the internet today. And, one shocking study revealed that businesses lose 20-35% of their operating revenue due to low data quality.
What is the solution? Big Data is the solution to this problem and businesses are using Big Data to get most out of their collected data. Akamai, the leading content delivery network, currently analyzes more than 75 million events per day to maximize the return on advertisement investments for businesses.
Due to the enormous potential of Big Data and the ever-increasing volume of data, the market size of Big Data is growing. Experts estimate that the business data doubles every 1-2 years.
Businesses need data scientists and data analysts to analyze data. The recent survey found that around 50% of small and medium enterprises intend to hire data analyst by 2021.
What are some of the critical skills to be an on-demand data analyst?
Data analysts must have some essential skills to perform their tasks. Here are some of the skills that you should sharpen to land a job or to raise your rate.
SQL a.k.a. Structured Query Language is a common database language. Almost every huge corporation use this language to store, manage, and relate two or more than two data sets. A great example of the utilization of SQL is Amazon. It makes use of SQL to recommend products to its visitors.
Anyone who masters this skill gets an average salary of around $96k. There is a massive demand for SQL professionals in the job market.
- Statistical Programming
To be a master of data analysis, you must have a grasp of statistical programming. And when the talk is about statistical coding and programming, generally a question arises why pick Python For Data Science?
Python is currently the most popular programming language for data science as compared to R due to its several unique features and capabilities. Nevertheless, you can either choose Python or R for this purpose.
Mastering R or Python allows you to carry out advanced prediction analysis of data sets at a much faster rate. SQL, Excel, and SAS programs are not capable of performing tasks that these languages can perform.
- Microsoft Excel
Microsoft Excel is like given when it comes to the skill that you need to master. Excel is much more than just a spreadsheet. We use statistical programming for enormous data sets, while smaller data sets require Excel.
Startups usually go with Excel. You can carry out some advanced analysis like VBA lookups or writing Macros with Excel.
- Critical Thinking
To find out key insights from the collected data, you need to decide what queries to ask. See some top analysts and observe how they make connections between different data sets and events. There are plenty of books and courses that can help you, but you must spend time on learning how to think critically.
- Data Visualization and Presentation
It is crucial to tell a story that the audience would love to hear from your extracted insights. However, telling a compelling story to your audience can be quite tricky without visuals. The way you visualize data can make or break the acceptance of your findings.
You should know what types of graphs and charts to use to communicate your findings to your audience effectively. Understanding the basics of psychology can help you choose the visuals that others would love to see.
Regarding presentation, it is true that not every single person can present well in front of the stage. However, it is not an impossible task to gain this skill. There are tons of resources, both online and offline, to help you improve your craft. With that said, you need to practice.
- Machine Learning
There is a visible connection between machine learning, data science, and predictive modeling. It is true that you as a data analyst may not work with machine learning. However, having this skill in your arsenal will give a massive boost to your portfolio.
Learning something has never been easier. All you need to do is take online or offline Machine Learning courses. Check out what machine learning course resonates best with data science before pursuing it, though. At first, learn a statistical programming language and then learn how to use that language for machine learning.
Over to You
There is no need to be overwhelmed by the list of skills that you need to learn. Just master one at a time to get started. Furthermore, you can learn as you go. Most of the top performers in the world today were not impressive from the get-go. They made tons of mistakes and learned from them.
The most important thing here is to keep on learning. The world is changing at a rapid pace, and it is essential to be updated. IBM predicts that there will be a steady rise in the salary of data scientists. So, the demand will not go away anytime sooner. Just work on the skills that I have listed above to significantly increase your chances to land a job or to raise your rate.