When we hear the phrase "data analytics," some of us just nod our head and pretend that we understand what it means. But while the term might sound complicated at first, it's easy to understand when broken down.

Data analytics is the process of transforming data into information and drawing insights from that information. Professionals in this field use processes and algorithms to review raw data, translate it to more digestible forms so that it can be put to use, and to answer business questions using the information. Data science, which is similar to data analytics, seeks to explore raw datasets to develop questions and study areas that can later be answered using data analytics. Let's take a closer look.

A deep dive into data analytics.

Data analysts separate signal from noise, sifting through the glut of information that businesses amass to identify trends and other metrics. Data analysts review and interpret the data to draw conclusions and glean insight about an organization's performance, then leverage those insights to make strategic recommendations on how that organization can solve its problems and optimize its performance.

For example, manufacturing companies live and die on their ability to produce as much quality product as they can in a specific time frame. In an effort to understand production better, data analysts would record runtime and downtime, and analyze all data to determine ways to improve capacity and efficiency.

Four types of data analytics.

There are four main subgroups of the field.

• Descriptive analytics focuses on what happened. These analysts might ask: Have sales gone up or down over the last few months? Are more sales occurring on any particular day of the week? Is the organization's website seeing consistent traffic? Upon gathering the data to answer these questions, the analyst can recommend strategic changes.
• Diagnostic analytics focuses on why things happened. They do the detective work, looking for correlations and causations. These analysts might ask: Were sales of outdoor products lower because of the weather? Did our advertising budget pay off? Why is production down in the morning compared to the afternoon? They try to identify and solve problems using data.
• Predictive analytics focuses on what's going to happen or what's likely to happen. Predictive analysts will ask: Will this year's holiday sales equal those of last year? Will a ballplayer equal his average home run total from the previous five years? They use past data to try to predict what the future will hold. Predictive analytics can also fall into the realm of data science if it is not clear from the outset what insights might be extracted from the data.
• Prescriptive analytics focuses on what should happen or what should be done. Data analysts or data scientists might use data to find that an organization needs to lower production costs by 22 percent in order to improve profitability, for example, or that the only way for a district to handle the growing student population is to add 2.5 students to every classroom.  

Careers in the field.

The IT field is growing—and growing faster than most industries, the Bureau of Labor Statistics says—so there are plenty of career options for people who like to analyze data, review statistics, and devise solutions by crunching numbers. But analyzing data won't confine you to an IT desk. Here are a few of the interesting career paths open to data devotees.

Stock trader.

If you're interested in the stock market, you know that it's all about weighing the percentages. Is a stock worth investing in? Has its value plateaued? Is it about to take a tumble? How are similar stocks performing? A stock trader analyzes data every day and makes critical decisions based on that data that affect client profits. According to PayScale, the average securities trader makes about $66,000 per year.

Climatologist.

Climatologists try to forecast major long-term climate changes by analyzing the patterns of climatic history. They then extrapolate how those impending climate changes will affect the environment and the public. Though they aren't meteorologists, they often work with or as weather forecasters—who knows, maybe you could end up on the Weather Channel. The website environmentalscience.org estimates the median annual salary for a climatologist at $89,260.

Real estate appraiser.

Being a real estate appraiser involves constantly crunching numbers and comparing properties. Real estate appraisers estimate the value of the land, building, or home based on the information they obtain from other local transactions. If you love HGTV, this could be the career for you. You can expect to make about $62,000 per year, PayScale says.

Genetic counselor.

Genetic counselors assess the risk of inherited conditions and then pass their findings along to healthcare providers and doctors. Data analysts are in high demand in the medical field, Forbes writes, because they're uniquely equipped to process the genetic data generated by today's medical devices and consumer genetic tests. The Bureau of Labor Statistics puts the average yearly salary at just over $78,000.

How to get into the field.

To become a data analyst or a data scientist, you'll definitely need a college degree. At the very least, you'll need a bachelor's degree—most likely in data analysis, computer science, math, physics, or some related field. Most of these programs train you in computer programming, basic math, and more advanced math like statistics. Many people eventually get a graduate degree, as it provides them even more knowledge and credibility in the field.

Whichever career you choose in data analytics—and you will have many choices—you're bound to have a long and interesting career.