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Dr. Julian Rasch
Data Scientist
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Data analysts are in high demand as companies increasingly rely on data-based decision-making. If you want to gain a foothold in this area or advance your career as a data analyst, it's important to have a solid foundation for the skills that will be in demand over the coming years. In this blog, we share key capabilities for 2023, including data analytics, security, tools, and programs to help you succeed in this exciting and fast-growing space.
“Without big data, you're blind and deaf and standing in the middle of the highway.” - Geoffrey Moore
While there are many different factors that influence the success of a company, it is obvious that the skills and knowledge of employees influence each and every one of them, which is why it is absolutely crucial to skills to “update” to remain successful..
Progressive digitization and the advent of big data have led to a massive shift in the skills required for many jobs guided. As a result, data analyst skills in particular are becoming increasingly important in every company.
The reason is pretty simple. With a wide range of use cases such as
and many more, data knowledge enables companies to significantly increase their profit margins. One current study has shown that companies can reduce costs by 10 to 50% in many areas such as workforce planning, receivables management, predictive maintenance and supply chain optimization. The same study claims that conversion rates increase by more than 100% when the collected data is used to personalize marketing campaigns!
For your organization to achieve similar results, you must acquire the necessary skills to handle data. This article will first guide you through the key concepts needed to build these skills and then give you concrete tools that are widely used to master them.
There are many definitions of critical thinking, but at their core, these definitions boil down to the ability to understand the logical connections of ideas and information through rational thinking.
Given the seemingly limitless amount of data available, critical thinking empowers a person to see the connections between different topics and ask the right questions.
This list could be continued endlessly, but the essence of critical thinking becomes clear: Ask questions — ask lots of questions. While critical thinking isn't just a skill for analyzing data, it's the basis for everything that's yet to come.
“Where there is data smoke, there are also business fires.” - Thomas Redman
The first skill that is directly recognized as a “data skill” and is crucial in every company that works with data is data cleaning and data preparation. The importance of data cleansing and data preparation is best explained with a simple example:
Imagine a kitchen filled with all the ingredients and tools you need to cook. Through critical thinking, you'll figure out exactly what you want to eat and what recipe you need to actually make the meal. But the kitchen is big and is almost overflowing with groceries, pots, pans, knives, and anything else you need. Data cleansing allows you to simply set aside any superfluous items and ingredients, while data preparation prepares everything perfectly, so all you have to do is start cooking.
But can't you just get started right away and save time?
Data cleansing and data preparation are so important because they make the rest of the work easier. With a properly cleaned and prepared data set, even the simplest algorithm can achieve great success, while on the other hand, an unprepared data set can result in faulty or inadequate solutions that could harm your business. For this reason, data scientists spend up to 80% of their time on this process.
The next step in the process is the actual data evaluation (data analytics), also known as data analysis (data analysis).
Simply put, data analysis is about the processing and statistical evaluation of data sets in order to make recommendations for further measures.
There are four types of data analysis, each based on each other:
The next step after analyzing your data is presenting it, which is often done through visualization. This process is known as data visualization, and it may state the obvious, but it describes the ability to present your results with graphs, charts, and other illustrations.
Auch If it would be very helpful, not everyone can be an expert in data analysis. When trying to introduce more data-based decision-making, this often results in the problem that people who have not received appropriate training and guidance have difficulty understanding the complex information given in a short period of time. Visualizing the results and suggestions for further action enables decision makers to understand the ideas and suggestions in no time at all. With that, the Data visualization is one of the most important data-related skills, because what good are ideas and solutions if no one understands them?
After you've put in so much work to become a data-driven company, there's one last step you need to take. You must make sure that your data is secure. You've probably heard sayings like “Data is the new oil” or “Data is the most valuable currency in the world.” So shouldn't you make sure that you protect the data and knowledge you've acquired through hard work as much as possible?
Because of the many benefits of collecting, analyzing, and ordering measures based on data, cybercrime has become a serious problem in recent years.
What makes it an even bigger problem is the fact that losing data not only harms the company itself but also its customers. Data loss due to security breaches is often associated with a loss of reputation and can even result in huge liabilities caused by the security incident. On average, a single data breach costs companies worldwide 3.86 million dollars, but as the severity increases, these costs rise to more than 100 million dollars.
Of course, these costs are at the extreme end of the scale, but they make it clear how important it is to protect your newfound treasure.
Now that you understand what general data skills are required, we'll now briefly list some of the key skills, tools, and programs:
SQL (Structured Query Language) is still the most common way to query and process data in relational databases, even though it was developed almost 50 years ago. Its popularity hasn't diminished as it is the primary tool for merging, aggregating, and filtering data from relational databases.
NoSQL, the counterpart of SQL, doesn't store data in tabular form, and the records aren't organized in the same relational lines that are used in SQL. This gives structures and frameworks built on NoSQL the ability to take any shape, with the only limitation that no relational lines are used, making it impossible to define a specific framework as a standard way of organizing in NoSQL.
Database management systems (DBMS) are data-holding systems that enable users to perform operations to define, retrieve, manage, and manipulate data in the database. Working with DBMS mainly accounts for the 80% covered in the Data Cleansing and Preparation section.
The most popular DBMS based on SQL include MySQL, Oracle, PostgreSQL, Microsoft SQL Server (Microsoft Access is also included) and SQLite, while MongoDB, CouchDB, HBase, Cassandra, and Redis are the NoSQL counterparts.
Even though professional data skills often go far beyond the simplicity of Excel and other spreadsheets, their effectiveness remains effective with smaller amounts of data. Writing macros and VBA lookups is still widely used, even among the most experienced data analysts, and their popularity outweighs more than 750 million users worldwide.
As mentioned in the definition of data analysis, statistical analysis is performed on data sets to understand, connect, and predict potential outcomes with the underlying data. This, of course, requires statistical knowledge or, better still, the knowledge of how to use a statistical tool in practice.
The two most used programming languages in this area are Python and R. Some prefer R because it was developed specifically for analysis, while others prefer Python because of the exceptionally large number of libraries that deal with artificial intelligence, another topic that is closely linked to data analysis skills and is becoming more and more important.
Nevertheless, knowledge of at least one of the two languages is a great advantage, as their use with the add-ons dplyr for R and Pandas for Python extends to data cleansing and processing. Other good programming languages that you should master include Java, Julia, and MATLAB.
We definitely owe you a few of them, having emphasized the importance of data visualization. Tableau is one of the most used tools for visualizing data in companies. Although it is very easy to use and understand, Tableau has excellent visualization potential that has made it a go-to tool for many companies.
Microsoft Power BI is Microsoft's solution to the data visualization problem. If the basic data visualization capabilities that Excel offers aren't enough for your business, this tool is very useful while remaining within the Microsoft ecosystem. Data can be imported from almost all backend databases, and a variety of visualization features are available to all users.
Other great tools that can be used include Zoho Analytics, Infogram, and DataWrapper.
And a little extra:
Now that we've talked enough about the general tools that will be used by many in 2023, here are the tools mentioned by our data scientists when asked about their favorite tools:
Now that you have a solid understanding of data analysts' key skills for 2023, it's time to take your knowledge to the next level. But what about other professions such as software engineer, developer, but also marketing manager or accounting manager? You can assess for yourself which skills will be required with the help of our e-book. If you want to improve your professional skills and remain competitive in your field.
Find out everything in our Skill report.
edyoucated is funded by leading research institutions such as the Federal Ministry of Education and Research (BMBF), the Federal Institute for Vocational Education and Training (BIBB), Federal Ministry for Economic Affairs and Climate Action (BMWK).
