The demand for data scientists and analysts with the right skills is huge. You can transition to a career in data science or analytics and get stable employment in a top paying industry if you develop all the necessary data analysis skill sets. According to the United States Bureau of Labor Statistics, total job openings for skilled data analysts are predicted to grow by 23% by 2031, which signifies that more than 5% of average job growth will occur worldwide. But do you know what skills are in high demand in the data world? The following article will help you prepare and transition to a lucrative career in data analysis by developing these necessary skill sets.
1.SQL
SQL stands for a structured query language, a standard language that helps data analysts communicate with different databases. Almost all data analysts have to use this programming language for accessing data from the database of the company; therefore, if you want to get a secure job for data analysis, you need to develop SQL skills in the first step. SQL helps with data analysis, organizing and querying data stored in relational databases, and even assists professionals in modifying the data schema or structures. If you want to develop fluency in SQL, you can undergo a data analytics specialization course from a good institution where you can work on SQL projects and learn how to analyze and explore data.
2.Cleaning and preparing data
As per research, cleaning and preparing data constitute 80% of the overall work of a data analyst. Therefore cleaning and preparing data is a vital skill set that every data analyst must possess. Data analysts have to retrieve data from different sources, prepare it for categorical and numerical analysis and then clean it to resolve inconsistent missing data, which can impact the overall data analysis. Data cleaning might not be exciting work in data analytics. But preparing data can be challenging and fun; if you want to hone your data cleaning and data preparation skill sets, you can join beginner-friendly courses.
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3.Statistical programming
Data analysts have to develop statistical programming skills to get a good job. Statistical programming languages such as Python or R enable these professionals to perform data analysis, clean, visualize, and analyze huge data sets efficiently. Both these programming languages are open source; therefore, novice and beginner data analysts can work with them easily. Both programming languages help in data analysis; however, R programming language is designed especially for data analytics operations. In comparison, Python is an easier language for both data science and analytics work. Statistical programming languages will help you build complex programs and visualize data efficiently.
4.Machine learning
Developing machine learning skills is not required for a data analyst job. However, you can get a competitive edge over others if you can develop machine learning skills, work with big datasets, and give predictions accurately.
5.Statistics and probability
Data analysts must build a strong foundation in statistics and probability for identifying trends and patterns in data, eliminate logical fallacies and bias errors in data analysis, and offer reliable and accurate results to the organization. Developing probability and statistics skill sets will help professionals collect, interpret, and present data properly.
6.Data management
It is important for data analysts to possess data management skills. This refers to the process of gathering, organizing, and storing data efficiently and in a secure cost-effective procedure. Almost all companies and organizations require data management systems, and so they employ data architects, database administrators, information security analysts, and data analysts to manage the data efficiently. Data management skills will help analysts understand how databases work and store data in the cloud and physical environments.
7.Data Visualizations
Data analysts are required to design, clean, and visualize charts to help others understand their data findings. Data visualization skills are key data analysis skills. Without these skills, professionals cannot interpret data and communicate their findings with stakeholders. Improving data visualization skills means learning about Tableau and other visualization software that helps to transform data analysis into data models, dashboards, business intelligence reports, etc.
7.Problem-Solving
Data analysts need critical problem-solving skill sets to efficiently understand and overcome key business challenges. Solving problems is an important skill that hiring managers will recognize and appreciate. This is important as the company and business may have resource constraints that can force these professionals to think critically and solve problems logically.
8.Data analyzing and data exploration.
Analyzing data is an important skill every data analyst must possess. Analyzing data includes taking business questions and analyzing important and relevant data to answer specific questions. An important part of the data analysis task is data exploration, which includes researching for interesting relationships or trends in data to drive more value to the business. By detecting patterns and trends in data, analysts can find golden opportunities for the company or business to increase their growth and decrease their costs.
10.Domain Knowledge
Data analysts must have domain knowledge about the industry and the company they are working for. If you do not understand the domain knowledge, you will fail to analyze data and execute your job properly. You can learn about the domain knowledge on a practical job. For instance, if you’re working for an online store, then you need to understand the key metrics of an ecommerce business.
How can you include your data analyst skills on your CV or resume?
Data analysts must possess various technical and non-technical skills to make data-driven decisions for the organization. Therefore investing time and effort in these skills is important for a successful data analyst career path. You can learn all the above-mentioned data analysis skills by regularly practicing, learning from your past mistakes, practicing with real-world data projects, undergoing a data analytics course program, joining an online data community, etcetera. You must mention all the data analysts’ skills on your resume to increase your hiring chances and stand out from the crowd. You must also discuss your skills in the interview you mentioned on your resume. You can build a data analyst job portfolio after enrolling in a professional certification course program imparted by an accredited institution. You can learn about cleaning, and organizing data with data analytics tools like R and SQL, visualizing data with Tableau, and gaining hands on experience.
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