In a field as constantly evolving as data science, one career track that’s relatively easy to understand is that of the data analyst. After all, a data analyst does exactly what the job describes: analyze data. Analyzing data is something we all do every day. Every one of us constantly learning and taking in new information (data), and then coming to many conclusions and making multiple decisions as a result (analysis).
So in the simplest terms a data analyst is required to do
exactly that – gather information, organize it, and make informed (or
findings-based) decisions as a result. Worded more as one might see on a job
description; a data analyst is responsible for understanding the trends and
insights that are revealed in massive data sets, translating that info into
behaviors-based conclusions or projections, communicating these to
stakeholders, and ultimately influencing if not determining an organization’s
decisions and directions. Data analysts are often hired by companies to help
inform or improve business practices. This guide walks through the necessary
steps to become a data analyst, and contains detailed job description, salary
information, and future job outlook.
What is a data analyst?
A data analyst takes data and uses it to help companies make
better business decisions. A data analyst acquires information about specific
topics and then interprets, analyzes, and presents findings in comprehensive
reports. Many different types of businesses use data analysts to help collect
and analyze data. As experts, data analysts are often called on to use their
skills and tools to provide competitive analysts and identify trends within
industries.
A data analyst is similar to a data
scientist but they’re not
precisely the same job, but are often not responsible for creating the
algorithms used for data discovery and acquisition. Rather than creating their
own data projects, data analysts often find themselves tackling specific
business tasks using existing tools, systems, and data sets. Both careers share
a common goal: to discover how to use information to answer questions and solve
problems for the benefit of their business/industry.
What does a data analyst do?
Data analysts translate numbers, trends, and trajectories
into digestible and accessible information. Businesses collect data (i.e.,
sales figures, inventories, market research, profit margins, logistics, and
transportation costs). A data analyst’s job is to take that data and use it to
help companies make better business decisions. Often, the main goal of a data analyst
is to solve issues that cost the company money and to help make decisions for
expanding the business.
Some examples of a data analyst basic job functions include:
- Estimating
market shares
- Establishing
a price of new materials for the market
- Reducing
transportation costs
- Timing
of sales
- Figuring
out when to hire or reduce the workforce
Data analysts are responsible for collecting, manipulating,
and analyzing data. Data analysts use systematic techniques, standard formulas
and methods to analyze the relevant information. They then typically prepare
reports detailing the results from their analysis.
Data analysts might perform basic statistics such as
variations and averages for a particular product over a certain time period.
They also predict yields and interpret the underlying frequency distribution of
a set of continuous data. They use the standard methods of collection,
analysis, and reporting when completing their tasks. Data analysts always
protect the organization’s data, making sure that the data results produce
consistent, reusable guidance.
The three steps to launching a data analyst career
Step 1: Earn a bachelor’s degree in information
technology, computer science, or statistics
To best set yourself up for success in the field of data
analysis, consider earning your bachelor’s
degree in the field. A specific degree
in data analysis is obviously best either information technology or
computer science, while minoring in (or at least studying) applied statistics
or data analysis. Also take computer science classes that emphasize project
management and database management. Find an advisor or career counselor that is
familiar with a data analyst career path.
Step 2: Gain data analyst experience
It is difficult to gain employment as a data analyst if you
do not have any experience. Interning while in school is a good way to gain
valuable experience and will help with insights about additional skill
development and training. Even still, most people in technical careers start at
entry level positions in this case including positions such as a statistical
assistant or technician. These jobs will provide valuable on-the-job training
and experience. Take as many in-house training classes as possible, especially
ones focused on and incorporating analytical software programs and big data
management. Experience, knowledge, and willingness to learn will help you rise
to the level you desire and the qualifications sought after among hiring
professionals.
Step 3: Advancing your career – consider a master’s
degree or certificate program
An advanced degree will offer more job opportunities and
ways to advance your career. Employers want candidates to have an array of
knowledge and be familiar with the latest technologies and tools. Consider a
master’s degree in data science, data analytics, or big data management. These
programs will generally provide exposure to the newest software programs from
experts in field. Many universities partner with corporations to create team
assignments, internships, and capstone projects: which will gain invaluable
real-world experience while earning an advanced degree.
Nervous about the cost or commitment required in pursuing a
full master’s degree? Certificate programs are another viable option and a
useful academic launchpad. These certifications are meant to give you a
comprehensive overview of the subject in a comparatively short amount of time.
There are outliers and variations, but essentially you can expect to earn a
certificate in roughly 12 months. You don’t necessarily need a certificate in
data analytics and visualization specifically, as you’re also able to pursue
certifications in business analytics, predictive analytics, data visualization,
and several other options.
To use one example, the University of Washington offers
a Certificate
in Data Visualization either online or at their Downtown Seattle
campus. In about nine months, and over three courses you’ll learn Data
Visualization Theory, Data Visualization Presentation, and Decision Making
Through Data Visualization. You’ll reply on the most widely used tools to
produce your visualizations (Microsoft Excel and Tableau) and additionally,
you’ll become skilled at recognizing and visually implementing the design of
data patterns based on “visual
cognition and perception.”
Data analyst job description
- Figure
out what questions are being asked and figure out if those questions can
be answered by data.
- Determine
technical issues with collecting and analyzing data, and design reports.
- Identify
new sources of data and methods to improve data collection, analysis, and
reporting.
- Collect,
analyze, and report data to meet business needs.
- Distinguish
trends and patterns.
- Report
data in a comprehensive and repeatable way.
Skills needed to become a data analyst
Like business analysts, data analysts often possess sharp
technical skills complimented by strong industry knowledge. They have a
complete understanding of relationships that exist among the organization’s
various databases and data sources. They obtain information using complex query
statements and advanced database tools and techniques.
Analytical skills: Data analysts work
with large amounts of data, including: facts, figures, and number analysis.
They need to see through the data and analyze it to find conclusions.
Communication skills: Data analysts
present their findings, and translate the data in understandable ways, be that
in written documents, visual presentations, or verbally to a team of executives
in a meeting. They need to write and speak clearly and be able to communicate
complex ideas into easily understood terms.
Data visualization: A large
component of effectively communicating the findings and insights that data
analyst’s present is data visualization. As a data analyst, you’re going to
have access to large quantities of data housed in data bases that it’s likely
that many of the people you’re going to be talking to about your findings may
have never even seen and wouldn’t understand if they did. Skilled data
visualization can help that. By deciding on the right graphs to use,
which charts work best for which audience, and how to scale the visualizations
of your data, you’re setting the stage for how the story is being told.
Choosing colors and graph designs may seem purely cosmetic, but there’s science
involved in what our eyes are drawn to and how our minds process the images we
see.
Creative and critical thinking: Data
analysts must look at the numbers, trends, and data in order to formulate
conclusions. Working with hard data obviously involves heavy critical thinking
skills, but creativity and a curious mind can be just as important. By looking
at the numbers through a creative lens, a good data analyst can generate
compelling research insights that other companies or organizations might not
have.
Attention to detail: Data is precise.
Data analysts have to make sure they are attentive in their analysis to come to
correct conclusions.
Math skills: Data analysts require highly
developed math skills, particularly in statistics, to process numerical data.
Technical skills/tools: There are many
technical skills and computer programs that a data analyst must have in order
to be proficient. A few of these include: SQL, XML,
JavaScript, R, Python, SAS, Hadoop, and
other machine learning programs.
Microsoft Excel: One of the most
important programs to have in your toolbox as a data analyst is actually one
with which almost everyone in today’s workforce is familiar, Microsoft Office’s
iconic spreadsheet software, Excel. Data analysts should have an expert handle
on Excel and understand advanced modeling and analytics techniques available on
the platform. This will mean quite a bit more than sorting and filtering, and
focuses on slightly more complex functions like VLOOKUP. You might be amazed at
just how
much you can accomplish in data analysis with a relatively basic
administrative platform.
Data analyst salary
The average salary for operations and research analysts
(including data analysts) is $86,200 per year according to the Bureau of
Labor Statistics (BLS) as of May 2020. There are many additional
factors that affect the salary, including educational level, years of
experience, certifications, and involvement in professional organizations. For
the first five to ten years in this position, pay increases somewhat, but any
additional experience does not have a big effect on pay. Most people move on to
other jobs, such as data engineers, data architects, or data scientists once
they have more than 10 years of experience in this career. The highest paying states for
data analysts were listed as California, New York, New Jersey, Virginia, and
the District of Columbia.
Data analyst job outlook
According to the BLS, employment of operations and research analysts (including data analysts) is projected to grow 25 percent from 2019 to 2029, which BLS rates as much faster than the average for all occupations. The metropolitan areas with the highest rate of employment for data analysts include New York City, Washington D.C., Chicago, Dallas-Fort Worth, and Los Angeles. Computer scientists are likely to enjoy excellent job prospects, because many companies report difficulties finding these highly skilled workers. Many companies are still trying to staff with the talent shortage in full force, and expect to see even more teams getting on board this year as they hurry to catch up to the rest of the market.
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