Data analysts collect data, clean and analyze it in order to assist businesses with making informed decisions. Data analysts will continue to be in demand as the business world relies more on data. There are several ways to enter this field.
It is a good idea to research what data analysts do before you begin training. You must also be comfortable working with numbers, and you should have a keen eye for accuracy. Here are some easy ways to get started in data analysis.
Foundational Education
It is important that you develop foundational knowledge if you are new to the world of data analytics. You can get an overview of the entire course to ensure you are ready for work or that it is a good match.
Some analyst jobs require a Bachelor’s Degree. Things have begun to change. If you have a degree in computer science, math, statistics or a closely related field, then data analysis skills can be added to your resume. You can learn the same skills using alternative methods, such as bootcamps or self-study. You can also choose a fully-packaged course to become a Data Analyst that includes all of these essential skills.
Building Technical Skills
To be able to do a job as a data analyst, you need a set of technical skills. These skills can be learned through the programs we listed above. These skills include Python or R programming and statistics, Structured Query Language, data visualization, cleaning and preparation.
You can find out what skills you should have by looking at job ads for data analysts. The majority of recruiters list both the technical skills that these analysts need to have and the role they will play, along with any soft skills needed for the job. Soft skills include communication, problem-solving and interpersonal skills.
Why Technical Skills
You can learn a lot about data management by acquiring a variety of technical skills. Let’s look at the most important.
Microsoft Excel and Google Sheets are two of the most important spreadsheet programs for data analysis, manipulation, and visualisation. These are the main software tools you will use as a data analyst.
Python: Python libraries such as NumPy and Matplotlib, are used for various data analysis and machine learning tasks. Before you can begin to analyze data, it is important that you understand these libraries.
This programming language was designed specifically for data analysis and visualization. It has specific capabilities for analyzing data and obtaining specific information out of jumbled up information.
Data Visualization is the process of presenting data in a manner that is easy-to-understand, shows relationships between variables and is easy-to interpret. Tableau and Power BI are the two main data visualization tools. You may find other programs out there that perform the same function, but they are all quite similar.
SQL is a language for managing and querying data in relational database. It is the most popular language for databases.
Gain Experience
You need to be able to work with data, and achieve the desired results. There are plenty of opportunities that provide practical experience.
You can start by analyzing the business data of a friend to get a good recommendation. You can also find organizations in your area that are looking for volunteers. You can apply to freelance data analysis tasks on platforms such as Upwork, Fiverr, People Per Hour and Upwork when you feel confident about your skills. Check if any organizations near you offer internships.
Online coursework and challenges are a great way to gain experience. These datasets can be found on platforms such as Kaggle. You can use them to sharpen your skills.
Get Certified
Consider obtaining one of the many certifications available to improve your skills in data analysis and make you stand out from other analysts. Some of these certifications are even free. These are some of the most popular:
Google Data Analytics Professional certificate: This certification is provided by Google. This certificate provides the foundational skills for data analysis. These include data visualization and analysis, as well as the ability to use tools such Google Analytics and SQL.
IBM Data Analyst Professional Certificate – This IBM certification examines data analysis in terms of analysis skills, machine learning, and visualization. This certification also shows you’re good with tools such as Jupyter Notebooks, Python and SQL.
Microsoft Certified: Power BI Data Analyst Associate (MCPDAA), SAS Statistical Business Analyst Professional Certificate (SBAPC), Certified Analytics Professionals (CAP), and CompTIA Data+ are also popular. As time passes, strive to achieve as many certifications possible.
Data analysis is dynamic, just like every other field. You need to keep improving your skills by working with various types of data. You can start at any age.
