Each year, the demand for data analysts exceeds the availability of people with the right skills to fill the vacancy. According to the US Bureau of Labour Statistics, the expected rise in the number of analyst job roles is expected to grow by 23% between the years 2021 to 2031. Skilled data analysts are among the most sought-after professionals in business and information technology. If you are looking to build a career or are considering a career change, a data analyst must have caught your eye, then pursuing a data analytics program can help you develop the in-demand knowledge and skills required to become a data analyst.
With the rapid expansion of data, learning the right skills and transitioning into a career in data analytics can mean job security and stable employment in the fast-growing and high-paying industry. These skills are needed for a new career in a high-growth field.
Data visualization refers to communicating and presenting data via graphs and other illustrations. It is an essential data analytics skill because it facilitates the information in a way that is easily understandable to non-specialists. Data analyst who uses this skill helps organizational leaders identify patterns and understand complex ideas.
Structured Query Language
Structured Query Language, also commonly abbreviated as SQL, is a database coding language widely used in data analytics for extracting, organizing, and managing large datasets stored in relational databases. Without SQL, performing any substantial analysis is impossible, making it a prerequisite for data analysis.
Machine Learning, or ML, is a branch of Artificial Intelligence(AI) that is important in data analytics. ML primarily focuses on building algorithms specifically designed to find trends and patterns in datasets. With time algorithms improves the accuracy of finding patterns. Data analysts use machine learning to create analytical models automatically. Leading organizations that use highly specialized machines to carry out data analysis prefer hiring professionals with knowledge of machine learning.
In data analytics, statistical programming languages, such as R and Python, help perform analysis in a way that no spreadsheet or excel can. A data analyst who can write a program in these languages can efficiently clean, analyze, and visualize large data sets.
Data management is the practice of collecting, organizing, and storing data in an efficient, secure, and cost-effective manner. Large organizations have specific roles dedicated to data management, such as data architects, engineers, information security analysts, database administrators, and data analysts.
Apart from gaining technical skills, data analysts must also have non-industry-specific skills, essentially critical thinking and communication skills.
Sound knowledge of econometrics is important for data analysts looking for employment in the financial sector, particularly in hedge funds and investment banks. With econometrics, data analysts apply mathematical and statistical models to economics and help forecast trends based on historical data.
Probability and statistics
Data analysts with a strong understanding of probability and statistics are most sought after by employers because they can better identify patterns and trends in data, produce reliable and accurate results, and avoid fallacies, biases, and logical errors in their analytics.
Building a career as a data analyst required to learn and master a set of technical and soft skills. Technical skills like data cleaning, MATLAB, R, Python, Linear algebra, and calculus are typically needed. Data analysts must possess soft skills, such as excellent communication, storytelling, problem-solving, critical thinking, etc.
Now you firmly understand the technical and interpersonal skills required to because a data analyst, take the next step and enroll in a dedicated data analyst program to strengthen your knowledge and polish your skills to become a data analyst.