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Are you sure you want to become a data analyst? Great choice! Because data analysts are currently very popular in the business community and are seen as the star players within an organization. This is because companies are increasingly making decisions based on data. Data is seen as the basis for many innovations and strategies. Because of the responsibility that comes with it, as a data analyst, you are expected to have a number of important skills. Curious about the five most important skills you need to get a job as a data analyst? Then read on!
Without data, you are nowhere as a data analyst. Fortunately, every company has previously collected data and there are a lot of methods to get new data. The image below shows various data collection methods.
Do you want to become an expert in data collection? Then learning web scraping is for you. If you have this skill, you can collect data from the internet quickly and automatically. In this article you will find more information about exactly what web scraping means and how to approach it.
Data cleaning is the process where, as a data analyst, you go through the data in a database and delete and/or update the data that is incomplete or incorrect. Data analysts sometimes spend up to 80 percent of their time on this process. This not only makes it the most time-consuming job, but also one of the most important skills you will need to master to find a job as a data analyst.
Cleaning up the data is not always seen as a 'fun' task, but structuring data can be quite cool. Especially if you work with the right tools and have the right skills, such as the Python programming language. Cleaning up the data will then be a lot easier and this is also a valuable step in the process, which you can't just skip. By cleaning data, you ensure that the collected (raw) data can be analyzed in the right way. If errors are made during this process, wrong conclusions can be drawn from the analysis. For this reason, cleaning and enriching the raw data is the key to gaining valuable insights. From compliance to marketing and from customer service to company turnover, data-driven decisions improve and/or grow the company!
The human brain does not have the capacity to make unorganized and large amounts of data understandable without any visualization. And what good are the valuable trends in data if you can't transfer them to others? Indeed, nothing at all! That's why, as a data analyst, you need to be good at visualizing and presenting your data.
Data visualizations make it easier to discover trends and other patterns and also help present your insights to others. Imagine a data analyst presenting his data to the management team without data visualizations. That would mean that they would have to look at a gigantic spreadsheet full of numbers and get all the information out of it in a short time. This way, there is a good chance that they will never understand the most important results of your research. That's why, as a data analyst, you need to be able to make your findings readable and understandable, both for yourself and others. You do this by using, for example, graphs, reports, dashboards and so on.
I can already hear you thinking, can't I just make a graph in Excel? Indeed, Excel used to be good enough to visualize your data. However, these functionalities are often too limited for today's data analysts. Due to the increased amounts of data that you have to process these days, you need to be able to work with more powerful visualization tools as a data analyst. For example, consider the most powerful of them all: Python, but also tools such as Tableau or Power BI.
SQL, or structured data query language, is the default language used to communicate with databases. This language is often seen as the upgraded version of Excel. With SQL, it is possible to quickly process large data sets, which is not possible or takes a lot of time in Excel. Almost every organization needs a data analyst who has knowledge of SQL.
Out research It appears that Python is the most popular programming language in data science. To give you an idea, as many as 87 percent of the data scientists indicate that they regularly use Python. Nowadays, a data analyst without Python knowledge can be compared to a waiter without a tray; it's incredibly useful to have it and be able to deal with it. Python is so popular because of the simplicity and readability of the language, the support of the community behind it, and the endless possibilities it offers.
By mastering Python, you can use the most important and most powerful programming language in data science. Python is constantly evolving with new releases and updates. It is expected that the popularity of this language will only increase in the coming years. Especially because both business and government are increasingly working with big data and machine learning. As a result, the demand for data analysts and data scientists who can use Python will continue to increase. In short, learning Python is a good investment in your future.
Do you already have (a number of) the five most important skills? Then you are well on your way to being able to work as a data analyst. Is this not the case yet and would you like to master the skills? Then we have the perfect course for you. In the course Data Analytics with Python you will learn all the necessary skills that a data analyst should have. In addition to the five skills mentioned above, you will also learn how to work with various data analytics tools. After completing the course, you will be fully prepared to work as a Junior Data Analyst.
Not sure if working as a data analyst is right for you yet? Then follow the free Webinar: One Hour of Data Analytics, where we delve even deeper into what data analytics is exactly, what you can do with it and whether it's right for you!
