Let’s face it: Ever since businesses and individuals figured out the importance of data and the impact it has on an industry, the demand for data analysts and data scientists has grown. Business owners and entrepreneurs are now realizing the importance of data scientists because, apart from the growing awareness about this field, the competition for businesses is increasing. According to statistics, there are a number of job openings for this position, and it is expected to grow in the future.
But the main question is: What skills are the most in demand for a data analyst?
Here, in this short read, you will get to learn the in-demand skills a data scientist and data analyst should possess from the professionals. We have done the research so you, as a future data analyst or someone who is interested in this field, can learn and start developing these skills for your career. Let’s get right into it.
What is a Data Analyst?
What is a data analyst? A data analyst is an individual (or a team of data analysts) who helps businesses gain insights from data to provide the business with informed and better decisions. There is a complete procedure that a data analyst typically moves through in order for the business to achieve its motive.
- Data analysts first identify the data that needs to be analyzed, which allows them to stay focused on the business’s main pain points.
- Next, specific data is collected and organized, and this data can consist of structured, unstructured, numerical, or qualitative data.
- Once the data is organized and collected, it is ready for cleaning, which is important for preparing the analysis.
- The organized data is analyzed.
- The analyzed data is converted into results to facilitate the interpretation of patterns, predictions, and understanding of the business’s position in the competitive market.
Data analysis can take different forms depending on the types of questions that need to be answered. However, the purpose of a data analyst is to make the process of interpreting and understanding data easier. Data is stored in many ways, and it can be confusing to the average person. This is why most businesses and individuals tend to hire professional data scientists who work with all kinds of data.
Learn more: How Power BI Revolutionizes Industries (6 Examples)
Top Skills for Data Analysts
Now, we will discuss the list of skills a data analyst should have. These skills are important for data analysts to have in order for them to be on top of their game in this field. Since the demand for data analysts is increasing, here is what you should know.
1. Statistical Programming
Statistical programming is a language similar to Python or R. This allows you to perform advanced analyses in many ways that may be difficult to do with Excel. For a data analyst, being able to write programs in these languages indicates that they can visualize large data sets easily and effectively and to further clean and analyze that data.
Both of these programming languages are open source, and learning at least one of them will benefit a data analyst. However, there is a debate about which language is better for a data analyst to learn. Here, we say that either language can accomplish similar data scientist tasks. While R is designed specifically for analytics, Python is the preferred or popular choice of the two and tends to be comparatively simpler and easy to learn, especially if it is your first attempt.
More to know: What to Know Before You Start Microsoft Business Central Online.
2. SQL
SQL, also known as Structured Query Language, is the standard language used to communicate with databases. Knowing this is compulsory. Through SQL, you can update and organize the quarry data stored in relational databases and warehouses, and then you can modify those into data structures, also known as schema.
Most data analysts need to use SQL in order to access data from the company or firm’s database. It is one of the most important skills to learn to get a job in this field. It is common for data analysts’ interviews to include technical screening with SQL.
More to know: How AI is Shaping the Business World.
3. Statistics and Probability
While statistics and probability can be defined as one of the fields in mathematics, they are some of the most important skills for a data analyst to possess since all of their work revolves around numerical data, while partially, they can be qualitative data. Through this skill, data analysts can easily understand, interpret, and draw insightful conclusions from the data they have to work with.
A strong grasp of these concepts will allow a data analyst to clean, collect, and prepare data for thorough analysis. This will further allow them to assess the probability of findings, identify trends and patterns, and make sound decisions based on data-driven facts and evidence. For a data analyst, an understanding of statistics and probability theory is essential. This allows data analysts to effectively communicate their findings to those who hired them and the stakeholders, building trust and providing relevant information.
A helpful read for beginners: What is Power BI for Beginners?
4. Machine Learning
Machine learning is one of the many branches of Artificial Intelligence (AI), and it has become one of the most used and important developments in the world of data science. This skill focuses on creating strong algorithms designed to find specific patterns in big data sets, which improves accuracy over time. The more data a machine learning algorithm processes, the more efficient it becomes, allowing for more accurate probable outcomes and predictions.
While data analysts are not normally expected to have a master’s skill in machine learning, it is important to have basic knowledge about it. Additionally, developing your machine-learning skills could give you a competitive advantage and help you build stranger roots as a professional data scientist.
5. Data Management
Data management is a practice that refers to collecting, storing, and organizing data in a way that is efficient, relevant, secure, and cost-effective. Most organizations have roles that are completely dedicated to data management, such as engineers, data architects, data administrators, and informed security analysts.
Different companies use different management systems, so it is important for a data analyst to be aware of these systems. As you develop a strong skill set, this will help you broaden your understanding of how databases and different kinds of databases work on a physical level and in a cloud environment.
More to know: Where BI fits into your Data Strategy? Learn More about BI vs. BA.
6. Econometrics
Econometrics is the study of quantitative (numerical) analysis of economic data. It is an important skill set for data analysts who work in economics or any similar field. Econometrics provides data analysts with the strategies and tools necessary for analyzing complex economic data. This allows them to further identify patterns and study the relationships to make informed decisions and predictive statements based on factual evidence.
With econometrics, data analysts can provide valuable insights into the field of economic-related research, such as policymaking and business decision-making.
7. Statistical Visualization
Last but not least, statistical visualization. This is one of the fundamental parts of telling a story based on factual evidence rather than a simple word. It lets businesses make more informed decisions. This is where statistical visualization comes in. As a data analyst, your world relies on the power of graphs and statistical visuals. It is your duty to create simplified and easy-to-interpret graphs that the average person can understand.
As a data analyst, your skills in graphs and data visualization should be on the spot. Using data visualization tools such as Power BI can allow data analysts and scientists to create interactive dashboards, visualizations, data models, and BI reports.
Related read: A Guide for Creating Strong Power BI Dashboard Design.
Over to You
Now that you are aware of the important skills and sets of skills that data analysts and data scientists possess, you can kickstart your interests in this field. However, it is important to keep in mind that several businesses and industries demand fast-working data analysts, and usually, when the burden is kept on a single data analyst, it can be very challenging.
Suppose you are a business that is considering hiring a professional agency such as BiExpertz. In that case, you will gain a team of professional data analysts and scientists who know their way around data and everything related to statistical visualizations. Our team is fast and effective in getting all your data set, regardless of any industry you are in. Get started with us today and gain the benefits of using Power Business Intelligence tools and integrate those into your data strategy today.
FAQs
Is SQL enough for a data analyst?
While most data analysts use SQL to do their work, it is preferred that they know the basics of other statements, such as Excel.
What makes a good data analyst?
There are some skill sets a data analyst should be good with, such as:
- Numbers
- Programming language
- Problem-solving skills
- Attention to detail and accuracy
- Machine learning
- Econometrics
- Statistics and Probability
What is the main goal of a data analyst?
The main goal of a data analyst is to clean, collect, interpret, and create interactive and simple charts to answer and solve the customer’s pain points. They work in several industries, such as businesses, finance, criminal justice, healthcare, and more.