Data analytics is a rapidly advancing field that considers a set of information to help leaders develop informed decisions and strategies in organizations of all types. It is a growing discipline used in every industry from finance to healthcare, retail, and hospitality. As a data analyst, your primary challenge is not just to make sense of numbers, but to figure out ways to analyze and use quantitative and qualitative information as rapidly as it is collected.

As the ability to gather information -- and lots of it -- advances, what a data analyst does is increasingly valuable in the workplace. Their insights allow companies to make better decisions about their business and consumers. With information playing such an important role in business practices, having the skills and knowledge to understand and use potentially massive amounts of data will help you succeed in a career in this field.

What is Data Analytics in Simple Words?

Data analytics focuses on the collection, inspection, cleaning, summarization, and interpretation of related information. The way information is collected and changing rapidly, companies in most sectors need employees who are up to date with the most current ways of handling these numbers and keep an eye out for future needs.
Dr Susan McKenzie, senior associate dean at Southern New Hampshire University, said organizations are collecting, analyzing, and leveraging more data than ever before to ensure that their decisions are data-driven.

The growth of information leads to big data, which refers to the tremendous amount of accumulated data. “The era of big data has arrived and has changed the role of analytics in every aspect of our lives,” McKenzie said.
"This creates (expands) the need for traditional data-handling tools and storage to process and store data based on volume, speed, structure, accuracy, and value."

A subset of data science, data analytics is a mathematical world. McKenzie said a foundation in statistics and data modeling tools is critical for this line of work, both of which are components of data analytics programs.

What are the 4 Types of Analytics?

According to Mackenzie, the four types of analytics are descriptive, predictive, diagnostic, and prescriptive, each serving a different purpose for the data professional:

DESCRIPTIVE
PREDICTIVE
DIAGNOSTIC
PRESCRIPTIVE

Since all four types of analytics have varying goals and outcomes, analysts must approach them with different tools and mindsets.

What is an Example of Data Analytics?

While data analytics supports everyday business operations, the COVID-19 pandemic has attracted national attention in how it informs decisions. During the winter and spring, public health sector analysts monitor how fast local, state and nationally trained professionals can vaccinate the public – and the number of vaccinations produced – to inform and adjust timelines.

"So, there was evidence in the data. Somebody had to interpret all that information, so they were tracking the data coming in: who's coming, how many are coming, what are the side effects, right?" McKenzie said. "There are all kinds of information that needs to be processed in order to make a decision, and in this case, that decision had an impact on a vast amount of people today."

Their findings have also helped leaders develop re-opening plans and offered the general public insight into the local, regional, national and global impact of this disease.

What is the Role of Data Analytics?

Data analytics today plays an informative role in all industries, contributing to effective business decisions and operations. "The goal of data analytics is to discover information to aid decision-making, ultimately leading to informed conclusions," McKenzie said.

Analysts act as the liaison between data and business leaders, interpreting what certain trends and patterns are for the organization and then communicating it in a way that leaders and other decision-makers can understand.

Often, analysts are required to interpret data to people who do not share the same mathematical background, making strong communication skills necessary. McKenzie said, "It's about taking the data you have ... to clean up, clarify, and transform the data into something that makes sense.""And it's preferable to be a visual representation.” Typically, the ability to construct visuals such as charts and tables can be helpful for the average person to process the information.

Synthesis of fast-accumulating data can help companies gain a foothold even against their competitors. They can take advantage of data analytics when they use it to make smarter and smarter decisions. "The power of deep data analysis can transform an industry overnight," McKenzie said.

Is Data Analytics a Good Career?

The growing importance of data analytics lends itself to a greater demand for industry professionals who have quantitative and qualitative data analysis skills and who can manage information efficiently.
"Our world has changed because, with the addition of data, we have to understand that it is as simple as incorporating it into every aspect of what we do," McKenzie said.
“Every job, every company, every role played in a company has to deal with data in some way, shape or form, and we desperately need people who understand how to clean, categorize and store meaningful information. have to change."

Analyst positions such as Market Research Analyst and Operations Analyst are on the rise. The US Bureau of Labor Statistics (BLS) reported that jobs for market research analysts are projected to increase by 18% by 2029, and operations analysts are predicted to grow by 25%.BLS also reports that mathematicians and statisticians, who made a median annual salary of $93,290 in 2020, are expected to increase by 33% during the same period.

While specific job titles can vary by industry, additional roles someone working in data analytics might hold include:

Data analytics analyst
Data specialist
Data manager
Data analytics engineer
Business analyst

If handling, analyzing, and interpreting data interests you, you may want to consider your career goals and determine what skills and education will be needed. "Depending on your interest and commitment to the field, an associate in data analytics or a bachelor's in data analytics is a good place to start," McKenzie said.
If you are already working with data in your current position or want to take your career into this field, a Master in Data Analytics or a Master in Business Analytics may be a strategic next step. When you choose to pursue these degrees, you are not limited to positions. Related fields, such as data science, data mining, and data architecture, use similar strategies that could benefit from a deeper understanding of data analytics.