A GUIDE TO WHAT YOU SHOULD KNOW

ADVANCING YOUR ANALYTICS CAREER

Table of Contents

What is Analytics? →

Industry Outlook →

The Value of a Master's Degree →

Analytics Careers and Compensation → An Insider’s Perspective →

The Skills Required for Success in Analytics →

Analytics at Northeastern: Fast Facts →

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The proliferation of data across all sectors of the global economy has given rise to one of the most in-demand, booming fields today: analytics.

Data is transforming and powering business everywhere—from hospitals and cities to higher education and corporations. As a result, workforce needs have shifted dramatically. Companies are searching for qualified

candidates who possess both a deep understanding of the mechanics of working with data, and the capacity to identify and communicate the data-driven insights that ultimately influence business decisions.

This has sparked a hot hiring market—and it’s only getting hotter. Currently, there are more than 2.3 million job openings for data-related roles, and the U.S. Bureau of Labor Statistics has indicated 11.5 million data job openings will be created by 2026. And because qualified professionals are difficult to find, these analytics jobs pay quite well.

“The analytics field is growing substantially, and there’s market demand for skilled workers,” says Uwe Hohgrawe, professor and faculty director of

Industry Outlook

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Northeastern University’s Master of Professional Studies in Analytics program. “Businesses are trying to make sense of all this Big Data and how they can use it to be competitive.”

Many of these jobs require candidates with both experience and advanced degrees. Eighty-one percent of all analytics job postings seek workers with three to five years of prior work experience, and 39 percent of analytics roles—the highest-paying ones, in particular—require an advanced degree. In a burgeoning field, this combination of qualifications is not particularly easy to find.

As a result, 47 percent of CIOs report having issues finding qualified data science and analytics professionals. Employers hope, however, that this urgent need for talent with the right skills, education, training, and experience will encourage more professionals to enter the analytics field. Keep reading to learn more about the most in-demand roles, the skills needed for success in the industry, and how you can position yourself to advance in the field.

47 percent of CIOs report having issues finding qualified data science and analytics professionals.(State of the CIO Report, 2020)

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What is Analytics?

To understand the role that data professionals play across industries, it’s important to first understand what analytics is. Analytics brings together theory and practice to identify and communicate data-driven insights that allow managers, stakeholders, and other executives in an organization to make more informed decisions. Experienced data professionals consider their work in a larger context, within their organization and in consideration of various external factors. Analysts are also able to account for the competitive environment, internal and external business interests, and the absence of certain data sets in the data-based recommendations that they make to stakeholders.

There are four types of data analytics that build on each other to bring increasing value to an organization.

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Descriptive analyticsexamine what happened in the past: monthly revenue, quarterly sales, yearly website traffic, etc. These types of findings allow an organization to spot trends.

Diagnostic analyticsconsider why something happened by comparing descriptive data sets to identify dependencies and patterns. This helps an organization determine the cause of a positive or negative outcome.

Prescriptive analyticsattempt to identify what business action to take. While this type of analysis brings significant value in the ability to address potential problems or stay ahead of industry trends, it often requires the use of complex algorithms and advanced technology such as machine learning.

Predictive analyticsseek to determine likely outcomes by detecting tendencies in descriptive and diagnostic analyses. This allows an organization to take proactive action—like reaching out to a customer who is unlikely to renew a contract, for example.

In a survey of more than 2,000 business executives, PwC found that organizations find descriptive analytics to be insufficient for informed, data-driven decision making. As such, diagnostic and predictive analytics are increasingly important to organizations.

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Analytics is a lucrative and high-growth field. Data-literate professionals are valued across all industries, in all corporate divisions, and at all seniority levels. As such, there is a wide range of jobs with impressive salaries that seek people who can analyze, organize, and interpret data.

Analytics Careers and Compensation

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The industries with the greatest demand for analytics professionals:

> Financial services

> Manufacturing

> Software-as-a-Service (SaaS)

> Healthcare

(Robert Half, 2019)

The average salary for data analysts ranges between $81,750 and $138,000, and depends heavily on:

> Industry

> Years of experience

> Level of education

> Possession of in-demand or specialized skills

Learn More | How to Increase Your Salary as a Data Analyst →

Here are some of the top data-related roles employers are looking to fill.

Data AnalystsAverage Salary: $81,750–$138,000Projected 5-Year Growth: 16%The responsibilities of a data analyst will vary depending on the type of organization and the extent to which a business has adopted data-driven decision-making practices. Generally speaking, though, the responsibilities of a data analyst typically include the following:

> Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems.

> Mining data from primary and secondary sources, then reorganizing said data in a format that can be easily read by either human or machine.

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> Using statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.

> Preparing reports for executive leadership that effectively communicate trends, patterns, and predictions using relevant data.

> Collaborating with programmers, engineers, and organizational leaders to identify opportunities for process improvements, recommend system modifications, and develop policies for data governance.

> Creating appropriate documentation that allows stakeholders to understand the steps of the data analysis process and duplicate or replicate the analysis if necessary.

Business/Functional AnalystsAverage Salary: $80,750–$178,000Projected 5-Year Growth: 17%Business analysts are a subset of management analysts who work to identify problems within business structures and help to develop solutions. They use a variety of tools, techniques, and data to help organizations make more effective business decisions.

In smaller organizations, these job titles may be used interchangeably to describe roles that involve data or system analysis. Larger organizations, however, often employ both data analysts and business analysts, making the differences between the two careers important to understand.

Learn More | Data Analyst vs. Business Analyst: What's the Difference? →

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Data Scientists and Advanced AnalystsAverage Salary: $102,750–$175,000Projected 5-Year Growth: 28%Data scientists take the data visualizations created by data analysts a step further, sifting through data to identify weaknesses, trends, or opportunities for an organization. These professionals design and construct processes and systems for data modeling and production using prototypes, algorithms, predictive models, and custom analysis to extract knowledge or insights from data.

These roles often require a background in math or computer science, along with some study or insight into human behavior to help make informed predictions, and are the most challenging positions to fill compared to the market average.

Learn More | Data Analytics vs. Data Science: A Breakdown →

Data-Driven Decision MakersAverage Salary: $106,250–$293,000 Projected 5-Year Growth: 14%Most professionals understand that without data, bias and false assumptions (among other issues) can cloud judgment and lead to poor decision making. And yet, in a recent survey, 58 percent of respondents said that their companies base at least half of their regular business decisions on gut feel or intuition instead of data.

Thus, there’s a growing demand at the top of organizations for data-driven executives—CEOs, CIOs, COOs, and financial, HR, and marketing managers, for example—who can connect the dots to build successful business, digital, talent acquisition, and marketing strategies using massive amounts of unstructured data.

This subset of professionals needs to know how to use analytics to execute their business strategies effectively. For example, these executives may

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harness the power of analytics to identify customer needs, detect unusual activity in real-time dashboards, or to forecast inventory using predictive analytics. These jobs require hands-on experience with reporting and visualization software to assist in the collection and examination of data. “They need a basic understanding of analytics to enable them to make decisions faster,” Hohgrawe says. “If you know a little more about how a car operates and how the engine works, you’re able to make a decision quicker, for example.”

Learn More | Data-Driven Decision Making for Beginners →

Other Data-Centric Roles

The titles discussed are not the only options for data-driven professionals. There are many other lucrative data-oriented careers that may align well with your interest and skills, including:

Database Manager: $108,000–$183,000

Data Systems Developer: $98,250–$167,750

Data Analyst/Report Writer: $81,750–$138,000

Data Architect: $111,500–$187,750

Data Modeler: $79,000–$164,500

Data Warehouse Analyst: $77,750–$160,000

(All salary data sourced from Robert Half.)

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Data Analytics Job Category Functional Role Sample Occupations

Data Scientists and Advanced Analytics

Create sophisticated analytical models used to build new data sets and derive new insights from data

Data ScientistEconomist

Data Analysts Leverage data analysis and modeling techniques to solve problems and glean insight across functional domains

Data AnalystBusiness Intelligence

Analyst

Data Systems Developers

Design, build, and maintain an organization's data and analytical infrastructure

Systems AnalystDatabase Administrator

Analytics Managers Oversee analytical operations and communicate insights to executives

Chief Analytics OfficerMarketing Analytics

Manager

Functional Analysts Utilize data and analytical models to inform specific functions and business decisions

Business AnalystFinancial Analyst

Data-Driven Decision Makers

Leverage data to inform strategic and operational decisions

IT Project ManagerMarketing Manager

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Sourced from Burning Glass Labor Insight, 2017

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“If you want to break into the area of data analytics, you need to have a passion for data and a passion for facts,” says Alice Mello, assistant teaching professor for the analytics program within Northeastern’s College of Professional Studies. “But it’s not just about crunching numbers. When making sense of data for business, you need to translate it into facts, draw conclusions, and use those conclusions to create and tell stories.”

Here are some of the top technical and soft skills analysts should hone to advance their careers.

IN THIS CHAPTER

→ Technical Skills

→ Soft Skills

The Skills Required for Success in Analytics

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TECHNICAL SKILLS For those in data-driven roles, the pressure to stay up to date on technical abilities and programming languages is vital in order to land or maintain a position in the industry. Today, nearly 70 percent of U.S. executives say they will prefer job candidates with data skills, and the demand for analysts will only continue to grow as we digitize our physical world.

1 | SQL SQL, or Structured Query Language, is the ubiquitous industry-standard database language and is possibly the most important skill for data analysts to know. The language is often thought of as the “graduated” version of Excel; it is able to handle large data sets that Excel simply can’t.

Almost every organization needs someone who knows SQL—whether to manage and store data, relate multiple databases (like the ones Amazon uses to recommend products you may be interested in), or build or change those database structures altogether. Each month, thousands of job postings requiring SQL skills are posted, and the median salary for someone with advanced SQL skills sits well over $75,000. While even non-techies can benefit from learning this tool, if you’re looking to work with Big Data, learning SQL is the first step.

Learn More | 5 Reasons SQL is the Need-to-Know Skill for Data Analysts →

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2 | Statistical Programming (R and Python)Data has become more complex, segmented, detailed, and, sometimes, overwhelming. In response to that, analytical tools, such as Python, Hadoop, Tableau, and SQL, are becoming increasingly sophisticated. The ability to keep up with today’s latest technologies and master them is critical.

Although Excel is a useful tool for analysts, anything Excel can do, R or Python can do better—and 10 times faster. Like SQL, R and Python can handle what Excel can’t. They are powerful statistical programming languages used to perform advanced analyses and predictive analytics on big data sets. And they’re both industry standard. To work as a data analyst, you’ll need to go beyond SQL and master at least one of these languages.

3 | Data VisualizationBeing able to tell a compelling story with data is crucial to getting your point across and keeping your audience engaged. If your findings can’t be easily and quickly identified, then you’re going to have a difficult time getting through to others. For this reason, data visualization can have a make-or-break effect when it comes to the impact of your data.

Analysts use eye-catching, high-quality charts and graphs to present their findings in a clear and concise way. Tableau’s visualization software is considered an industry-standard analytics tool, as it is refreshingly user-friendly. Learning coveted data visualization techniques and software will help data professionals stand out among the competition.

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4 | Machine LearningAs artificial intelligence and predictive analytics are two of the hottest topics in the field of data science, an understanding of machine learning has been identified as a key component of an analyst’s tool kit. While not every analyst works with machine learning, the tools and concepts are important to know in order to get ahead in the field. You’ll need to have your statistical programming skills down first to advance in this area, however. An out-of-the-box tool like Orange can also help you start building machine learning models.

In-Demand Technical Skills and Expertise> .NET

> Angular

> Apache Spark

> Artificial Intelligence

> Augmented Reality

> Blockchain

> C#

> Cloud and SaaS

> Golang

> Hadoop

> Java

> JavaScript

> Machine Learning

> Microsoft SQL Server

> PHP

> Python

> R

> ReactJS and React Native

> Ruby on Rails

> SAS

> Swift

> Virtual Reality

> Virtualization (Amazon Web Services, Microsoft Hyper-V and VMware)

(List from Robert Half)

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SOFT SKILLS The necessary technical skills that businesses desire in analytics professionals vary based on the job and responsibilities, but all require problem-solving, communication, creativity, and teamwork. “Anyone can learn statistics, but the differentiators are the soft skills: business analytics agility; how you manage projects; process management; communicating with different stakeholders; cultural sensitivity; leadership skills,” Hohgrawe says. “These are what really make a difference in a company today, and it’s what organizations are looking for in their new hires.”

1 | Critical Thinking Using data to find answers to your questions means figuring out what to ask in the first place, which can often be tricky. It is the role of a data analyst to uncover and synthesize connections that are not always so clear. There are a number of tips you can try to help improve your critical thinking skills. For example, asking yourself basic questions about the issue at hand can help you stay grounded when searching for a solution, rather than getting carried away with an explanation that is more complex than it needs to be.

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2 | Effective CommunicationIt is critically important to be able to clearly and effectively translate technical results and data solutions and persuade different audiences, says Hohgrawe.

“It’s not enough to simply identify and extract the data. Companies want people who can translate the data, apply it to business problems, and effectively communicate actionable recommendations to nontechnical stakeholders.” By being an effective communicator, you can also better promote yourself, showcase your work, and ensure that your accomplishments are being noticed and recognized by relevant stakeholders, including management.

Learn More | How to Communicate More Effectively with Data →

3 | Presentation SkillsThose who work with data are typically skilled in analysis and interpretation, yet many analytical individuals struggle with the act of sharing their findings with others in a way that is not only informative, but also engaging. The need for high-level presentation skills, however, is critical in the modern workplace; 70 percent of employees report that advancement in their field is contingent on these abilities, and data analysts are no exception.

“One of the key skill sets that you have to learn as you study data analytics is the distillation and presentation of the data,” says Tom Goulding, professor for the Master of Professional Studies in Analytics program within Northeastern’s College of Professional Studies. “It’s one of the most important skills because if you can’t [communicate the implications of the data effectively], then the data you’ve analyzed isn’t useful to anybody.”

Learn More | How to Tell Stories with Data →

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4 | Networking and Teamwork SkillsRandy Bartlett, author of A Practitioner’s Guide To Business Analytics, says it’s important to continuously cultivate your professional network in the analytics community. Connect with key stakeholders, including senior-level management, whenever possible; you can use them to test new approaches, which could result in a mentor relationship or friendship that could help you prepare for your next career move. He also suggests developing your listening skills—one of the most critical success factors for professionals in analytics—and being open and welcoming to diversity and inclusion of styles, ideas, and perspectives.

— Uwe Hohgrawe Faculty director, MPS in Analytics

“Anyone can learn statistics, but the differentiators are the soft skills. These are what really make the difference in a company today.”

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The Value of A Master’s Degree

This increased reliance on data across industries for decision making has created a growing demand for professionals with the knowledge and practical skills needed to interpret, analyze, and present data in a way that is concise, efficient, and impactful. However, this unique combination of knowledge and skills is not often obtained with only a bachelor’s degree. To achieve the level of understanding needed to succeed in this demanding field, many professionals who desire a high-paying career in analytics choose to pursue a master’s degree.

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Increased Marketability For one, data professionals with advanced degrees have more job opportunities. In fact, 39 percent of data science and analytics roles—the highest-paying ones, in particular—require an advanced degree. Burning Glass Labor Insight also reports that there are approximately 394,715 graduate-level jobs available for those with the proper advanced training—an increase of more than 32 percent in the last two years.

Even for jobs that do not require a degree, Bartlett adds that many hiring managers would prefer it—making an advanced credential increasingly important if you want to stand out and be competitive.

A Shortcut to Hands-On ExperienceEighty-one percent of all analytics job postings seek workers with three to five years of prior work experience. By enrolling in a degree program that offers or requires a practical, hands-on learning experience, professionals can gain hands-on experience in a risk-free environment.

“The most significant message that a master’s degree sends to an employer is that the candidate has taken the necessary steps to obtain the practical skills and experiences they will need in order to succeed in this demanding industry,” Bartlett says.

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Individuals who participate in Northeastern’s Master of Professional Studies in Analytics, for example, graduate having had the opportunity to not only learn from working professionals across multiple industries—including financial technology, healthcare, and pharma—but to also practice their skills through a variety of hands-on experiential learning opportunities with one of the well-known organizations that make up Northeastern’s expansive network.

Learn More | Is a Master’s in Analytics Worth It? →

“[Northeastern’s] program helps students establish confidence in their abilities to master analytics at the intersection of technology and business application,” Bartlett says. “Through experiential learning opportunities [like hands-on case studies, co-ops, and hackathons], students gain hands-on experience and an understanding of the true power of analytics.”

An advanced degree provides aspiring analysts with the tools they need to be successful in this evolving field. From practical skills such as programming and statistics to professional or soft skills like communication and presentation abilities, graduates leave with the tools and experiences they need to not only fill one of the many open roles in this industry, but to also thrive in it.

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”“Why did you pursue a master’s in analytics? When I embarked on my degree, I already had 10+ years experience in the IT field where I was doing data analysis. However, I needed a career advancement [strategy] to get up to date with Big Data technologies and programming languages that are now widely used in the industry such as Python, R, and visualization for data analytics.

Additionally, because Northeastern offers this degree as a STEM program, I was able to utilize the OPT [extension program that allows international students in STEM programs to stay in the U.S. for an additional 24 months to receive practical training related to their program of study].

An Insider's Perspective

Is earning an advanced degree in analytics the right move for you? Smita Gupta, 2019 graduate and current human resources IT data analyst at Northeastern University, shares how earning an MPS in analytics helped advance her career.

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““What would you say is the value of an advanced degree in the analytics field? This degree has certainly added a valuable layer in my professional career. My perspective when analyzing requirements has changed—in a good way. The specialized knowledge that I have gained with this program, such as exploratory data analysis, prediction modeling, visualization with different types of data sets, and the assignments that were provided by lecturers helped me to be more confident and improve my analytical, writing, and research skills.

Has your MPS in Analytics helped you in your career? Yes. My career opportunities have increased, since everybody [in the industry] now talks about data and analytics, and these skill sets are in high demand. I have recently joined the Northeastern staff as a data analyst, where I am able to utilize my previous skills and improved analytical skills that are needed to perform my job efficiently.

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Analytics at Northeastern: Fast Facts

Master of Professional Studies in AnalyticsCampus Locations

→ Boston→ Charlotte → Seattle→ Silicon Valley→ Toronto→ Portland→ Online

Available Concentrations:> Statistical Modeling

> Evidence-Based Management

> Applied Machine Intelligence

LEARN MORE →

Commitment> Full Time

> Part Time

Duration> 2-3 Years

Boston | Burlington, MA | Charlotte, NC | London | Nahant, MA | Portland, ME | San Francisco | Seattle | Silicon Valley | Toronto | Vancouver | Online

Are you ready to take the next step in your analytics career?

Northeastern can help you get ahead.Visit northeastern.edu/graduate to learn how.