Data analysts work with data—information—using various methods to identify solutions or more efficient ways of conducting business for an assortment of industries. Data is information regarding any number of business functions. Data analysts will gather this information, organize it, and use mathematical methods to analyze its meaning. Some data analysts may work for small businesses, evaluating small sets of data, while others can work for larger organizations, mining and analyzing large sets of data.
Why Become A Data Analyst
Data analysts respond to specific inquires and problems within their current roles. By using a number of existing methods, they collect and analyze the data to solve the specific problem. Their responsibilities require less expertise and responsibilities of data scientists, who can create their own projects, algorithms, and tools.
Regardless of data analysts’ workloads, their jobs require specific skills. Data analysts should have a balance of both technical skills and personal attributes relevant to the job:
Aptitude for statistics, machine learning, and descriptive analysis
Computer skills: querying, scripting, and statistical languages
Able to define and understand a problem
Ability to present results
Knowledgeable of industry
Data Analyst Work Environment
A variety of industries need to utilize their data to inform them of better business practices and to solve current problems. Data analysts can work for a number of different industries, performing different types of tasks or looking at different types of data. These industries include the government (local, state, and federal), private businesses (both big and small), e-commerce, finance, insurance, healthcare, science, social networking, telecommunications, manufacturing, politics, and other small sectors, such as the use of smart appliances and utilities.
Data analysts work in an office setting and rarely work in the field, although this aspect of the job may be necessary to understanding the problem. Their primary function is to use mathematical, analytical, and technical methods to create solutions and come up with more efficient ways to conduct business. Their job is typically fulltime, during normal business hours. They can work independently or in teams, as it is often necessary to work with other professionals with varying skill sets.
The median annual salary of a data analyst is $78,630 (2015). Pay depends on skill level, experience, and industry. Top paying industries include the following:
Federal government: $108,500
Scientific and technical: $83,690
Finance and insurance: $75,730
Data Analyst Career Outlook
According to the United States Bureau of Labor Statistics (BLS), the job outlook for operations research analysts is expected to grow approximately 30 percent from 2014 to 2024. This growth is much larger than that of the average for all occupations, which is at 7 percent.
This growth is due to a number of technological trends: Data mining is a booming field since the advent of many modern technologies. Organizations want to use this data to save money, increase profits, and improve their business model. The field of data analytics, itself, is expected to improve through this growth, constantly coming up with new and improved tools for data collection and analysis.
In addition to private entities, the government’s need for data analysts is growing exponentially. The military, policy makers, and research and development agencies will need to utilize the services of data analysts to improve their functioning.
Data Analyst Degree
Many entry-level jobs are available with a bachelor’s degree. Management, supervisory, and other jobs with more responsibilities will require a master’s degree.
Step 1: Obtain a bachelor’s degree. A bachelor’s degree in mathematics, computer science, statistics, information management, economics, or finance will help pave the way for a career in data analytics. It is important for employment in entry-level positions to have a deep understanding of these types of subjects, in addition to English and communications. Personal knowledge of software programs is also a benefit.
Step 2: Obtain a master’s degree. Although it is not necessary, many employers seek employees with a master’s degree, especially if one aspires toward eventual employment as a data scientist (a similar but more advanced profession). A master’s in a similar program to those mentioned above should be adequate for such an occupation. It may also be beneficial to take courses specific to the industry for which one wishes to work.