How to Become a Data Analyst and a Data Scientist in 2021?

Organizations have incurred a spike in the amount of data inflow to their servers and databases. This has necessitated employing data experts to scrutinize and analyze unstructured data and create more comprehensible data forms. To become a data scientist or a data analyst, there are skills that an individual needs to learn.

What is data analytics?

Data analytics is the procedure of collecting and processing raw data by applying arithmetical algorithms to draw meaningful intuitions that aid in a company’s decision-making process. Therefore, a data analyst is a person who scrutinizes the unstructured data and provides the way forward for the company.

The data collected is raw and unstructured since it is collected from vast sources. The data analyst is responsible for classifying the data into comprehensible forms. For instance, let us consider a business selling a product online. When customers purchase the product, they tend to leave comments depending on their satisfaction with it. The comments vary from critical to good comments. The data analyst then collects and analyses this information then provides feedback on how to boost the sales or maintain the lead in providing satisfactory products.

Skills required

Technical skills

The most crucial skill to become a data analyst is know-how in programming languages. All websites, applications, servers must be programmed to operate in a particular manner. Currently, there are over 750 programming languages that have been developed in the Tech World. Languages such as Python, JavaScript, Swift, Java, and C++ are commonly used because of their simplicity and ease of operation.

A data analyst is also expected to have the ability to use SQL programming language. This is essential for executing database operations such as extraction, addition, and deletion of data from servers. SQL is more efficient in the execution of complex queries related to databases than other programming languages. 

Education background

To become a data analyst, an individual should pursue a Computer Science, Statistics, Economics, or Data Science course to impart basic data operations knowledge. Also, individuals are encouraged to pursue online training of skills that are not taught in the classroom environment, such as using Hadoop.

Soft Skills

Data analysts should learn how to communicate effectively since they are part of a firm’s core decision-makers. They must learn to evaluate clients’ interests and deliver exactly what they demand in the first attempt. The report delivered by a data analyst is a reflection of a business’ place in the market. Individuals should also be updated with the latest web development trends and are willing to learn new operation skills.

Who is a data scientist?

A data scientist aims to gather and analyze bulky batches of raw structured and unstructured data from vast sources to develop predictive algorithms in more interpretable forms. These data experts forecast the changes that a company will incur in its sales if a certain verdict is made at the moment. For instance, when a business’ goal is to make a certain amount of sales at the end of a year, a data scientist will be required to analyze the sales of the previous years and make suggestions on a realistic value of sales that may be sold by the end of the year.

Skills required

Education background

Most companies recommend degree-holders in Data Science, Computer Science, and Actuarial Science to work with them. A few recommend those who have pursued Masters and Ph.D. in the stated courses with more experience in the data science field. Knowledge from classwork is insufficient to embark on all data science projects; hence, individuals must learn new operational skills such as Big Data querying from online short courses.

Technical skills

Knowledge of programming languages is a basic requirement for all data experts. Python is a core programming language that everyone aspiring to become a data scientist should learn R programming is a skillet that a data expert should learn since it can easily solve all analytical problems.

Machine learning and Artificial Intelligence are significant techniques that data scientists should learn since, technically, all innovations base their development on AI. Also, the bulky data sets will require people who are proficient in Machine Learning.

Soft skills

Before embarking on a data science project, an individual should have sufficient information regarding the sector he is working with. He must understand what a firm requires and if he can provide positive feedback on the task. He should also communicate with the company effectively by giving them a clear break-down of their requirements.

Bottom line

An increase in the demand for data experts has been witnessed in the past few years. With everything being done online, firms will keep looking for data analysts and scientists to make significant changes in their industries. For those seeking a new career path, data science is a suitable course to invest in. At the end of the day, all companies will require at least one data expert.