What Does Data Analytics Mean?
As the name suggests, data analytics is the process of analyzing data. Raw data is interpreted to make sense of the information presented in order to come to a conclusion.
The process involves looking for patterns and other categorical information to better organize the raw data that has been collected. It involves the processes of inquiring, collecting, organizing, analyzing, and interpreting what was found.
Also read: 5 Benefits of Using Reporting and Analytics Tools in Small Businesses
Here’s a simple breakdown of data analytics, data analysts, and what a career in this field may look like.
Types of Data Analyses
There are three major categories of data analytics: descriptive, predictive, and prescriptive, though sometimes diagnostic and inferential are also considered categories of data analysis.
Descriptive Analysis
This is the most commonly used way to analyze data, as it is the foundation of understanding any type of data. The descriptive analysis looks at past data to describe what has happened in the past.
Predictive Analysis
While descriptive data analysis looks at what has already happened, the predictive analysis looks at what is likely to happen, predicting future events. Though descriptive analysis is most commonly used, predictive analysis is also commonly used to help with things like risk assessment and sales forecasting.
Prescriptive Analysis
The predictive analysis predicts what could happen in the future, but predictive analysis predicts what should happen in the future. It takes the other analyses into account to determine what needs to be done based on these predictions. This type isn’t used as often as the first two, though artificial intelligence (AI) is a good example of predictive analytics.
Diagnostic Analysis
Diagnostic analytics can be best described as a substep of descriptive analytics. After what has already happened has been analyzed, diagnostic analytics seeks to understand why it happened the way it did. This seeks to solve problems and improve previous techniques.
A Career as a Data Analyst
Data Analysts vs. Data Scientists
Data analysts are sometimes referred to as data scientists, but there are some key differences in their job descriptions and abilities. For example, being a data analyst doesn’t require you to be an expert in automation, creating algorithms, machine learning, or software development, whereas being a data scientist does.
Instead, data analysts are experts in data visualization, linear regression, and storytelling. Though there are other skill sets that both jobs require, they are two different disciplines.
Careers/What Does a Data Analyst Do?
Data analysts are responsible for interpreting and organizing the data of companies and other organizations. This helps businesses understand what’s going on with their company and helps them to make better decisions in future business endeavors. Some of the job titles that data analysts go by are:
- Business intelligence analysts, who analyze the data of businesses.
- Marketing analysts analyze information from websites and social media advertisements for companies.
- Operations analysts work with data relating to manufacturing, distribution, and reporting systems.
- Project managers aren’t true experts in data analysis, but they have some knowledge of it as it relates to tracking employee productivity.
- Information Technology (IT) systems analysts, who solve the problems that may arise in data analytics.
Data analysts and other job titles related to it have pretty stressful jobs, but the stress is comparable to the stress of other jobs. The major stressors are the workload and the tight deadlines, but they are compensated a lot better than many other stressful professions.
The average salary of a data analyst is around $70,000 per year. Of course, salaries may look different depending on the location of your job and which concentration you choose to pursue.
How to Become a Data Analyst
Most of the time, data analysts need to hold a Bachelor’s degree in computer science, statistics, or another discipline in mathematics, or even economics or finance, depending on the concentration they choose. Some data analysts have also completed a Master’s degree in data science or a related field.
Many employers of data analysts also seek candidates who have experience in the field, so it’s a good idea to pursue internships throughout your course of study. However, it is possible to be hired without any prior experience, but job training will be more extensive to ensure that you follow the proper procedures.
Also read: Data Analyst: What it is and How It’s Work
Learn Data Analytics on Your Own
Oftentimes, one can become employed in an entry-level position if he or she holds a certificate in data analytics. Certification can be earned through companies like Microsoft or Cloudera, but you can also look into affordable educational programs like data analytics bootcamps to learn all of the skills and information it takes to become a data analyst.
These bootcamps will teach you the same things as you would learn attending a college or university for data analytics. You’ll be able to gain valuable experience and possibly work your way up to a senior-level position, where at least five years of experience is needed, but annual salaries are closer to $100,000.
If you’re a natural at analyzing patterns and organizing things in your everyday life, then a career as a data analyst may be the perfect fit for you. If you’re intrigued, but still on the fence, consider trying a data analysis bootcamp instead of enrolling in a university program.
These bootcamps are significantly less expensive than actual college programs, though they will teach you the same things, just at a quicker pace. You are still eligible for employment as a data analyst with a certificate, and you’re also able to work your way up.
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