How to Get into Analytics

Analytics has shifted from a “nice-to-have” function to a core driver of decision-making in almost every industry.

From marketing and healthcare to sports, finance, and tech, organizations are racing to hire people who can turn data into clear, actionable insight.

U.S. Bureau of Labor Statistics projects employment of analysts (a closely related role) to grow much faster than average through 2034, driven by rising data volumes and expanded use of data-driven decision-making.

Like any career that is newly trending and innovative, there are multiple pathways from which to choose.  Let’s weigh each option so that you may decide which best aligns with your career aspirations.

We will take a close look at the following:

• Degree Programs
• Bootcamps
• Certificates
• Work Experiences
• Internships
• Scholarships

It’s key to read onward as the science of analytics has changed drastically even over this recent past decade.

What Does “Analytics” Really Mean?

At its core, analytics is about using data to answer questions and guide decisions. The specifics depend on the role and industry, but most analytics work sits in one of these buckets:

• Descriptive analytics – “What happened?” (reports, dashboards, KPIs)
• Diagnostic analytics – “Why did it happen?” (segmentation, correlation, cohorts)
• Predictive analytics – “What is likely to happen next?” (forecasting, basic ML)
• Prescriptive analytics – “What should we do?” (experiments, optimization, scenario modeling)

In practice, many entry-level jobs blend parts of all four. Someone in a junior analyst role might clean data, build dashboards, answer ad-hoc questions for stakeholders, and eventually help design experiments or basic predictive models.

A Career in Data Analytics or Data Science

Due to the digital transformation, the call for knowledge in data analytics and data science has grown. Gartner Research’s Senior Vice-President Peter Sondergaard points out, “Information is the oil of the 21st century, and analytics is the combustion engine.”

The beliefs of Sondergaard are shared by leaders throughout corporations. Prowess in analytics is a valued skill set. The need is great for every business spanning industries and across the globe.

There stands tremendous opportunity in these fields, and related ones, with job growth very high, at 20 percent. According to the Bureau of Labor Statistics, the average annual wage is $140,910. The stats indicate its value in organizations around the world.

Career seekers with an interest in data science and/or analytics are taking a good look at how to best head off their journey. There are many ways to get started or expand your core competencies. 

Popular entry-level analytics roles

• Data Analyst – Cleans, joins, and explores data; builds dashboards and recurring reports; answers business questions with SQL, spreadsheets, and BI tools.
• Business / BI Analyst – Connects business questions to data; builds reporting layers for leaders; focuses heavily on KPIs, dashboards, and storytelling.
• Marketing / Product Analyst – Specializes in product usage, growth, or campaign performance, often using digital analytics tools plus SQL/BI.
• Operations / Supply Chain Analyst – Optimizes processes, capacity, and logistics using data from ERP, CRM, or ops systems.
• Junior Data Scientist / Analytics Engineer (for some) – Early-career roles that blend analytics with light ML or data engineering under guidance.

Most of these roles share a similar core toolkit: SQL + spreadsheets + a BI platform and solid communication skills.

Degree Programs in Analytics

When referring to “degree programs,” we are looking at that takes place at an accredited institution. In this modern age, there has never been more flexibility in terms of schedules. Not only are there in-class and online programs, but also the choice of synchronous and asynchronous classes. 

Colleges and universities are catering to the needs of their students at a level like never before. There is a mass effort to accommodate a generation of students that are balancing work and/or family while at the same time attending school.

As a result, students may select a full- or a part-time program. The offering of multiple learning modes aims to meet the varying needs of its student body.

Whether you seek an associate’s degree, bachelor’s, master’s, or PhD, there are an array of tracks that are specific to the study of analytics and/or data science. Listed are course names and titles of study that just twenty or so years ago were non-existent:

• Data Analytics
• Data Science
• Business Analytics
• Business Intelligence (BI)

In determining if the traditional route in education is the right one to take, the question posed is whether it’s worth it. Studies show a clear linkage between a degree and earnings potential. The higher the degree the better the compensation.  

Bootcamps in Analytics

Bootcamps were born a little over ten years ago. These have grown by leaps and bounds with the evolution of technology. 

Bootcamps are intensive and accelerated. These training programs are marketed to be both rigorous and fast-paced. They offer students the opportunity to add new skills to their portfolios.

It is this interactive approach that drives its students to work hard. Upon completion, they can tout new skills that offer a competitive edge.

Bootcamps are also highly specialized and short in length of time. There are a large number of technical training programs offered. Some are specific to the fields of data science and analytics and are of a technical nature. They include the following:

• Data Science Bootcamps
• Coding Bootcamps
• Data Analytics Bootcamps

The above represents only a sprinkling of what is currently offered in the training space. These programs take place at schools as well as centers for tech ed. Like the degree programs, boot camps are presented online and offline. 

There are an abundance of bootcamps, especially in the realm of analytics, that it may be difficult to pinpoint which one is ideal for you. It’s imperative to shop around. Some boot camps offer perks like job placement services.

Apparently, 74 percent to 90 percent of graduates of boot camps land a job within six months of completion, according to FlatIron school blog.

Work Experiences

Whether you have worked in a professional or low-level job setting, you have likely been involved in analytics to some degree. You don’t have to hold the title of Data Analyst or Data Scientist to have acquired these skills on the job. It’s important to pinpoint what you have accomplished and claim them as such. 

Have you ever input customer data? Looked for info about an account on the computer? Tracked the whereabouts of an order? Pulled a report on daily sales? Delivered tallies to your boss about why people didn’t make a purchase? Scanned items in a store? Used software to record outcomes?

Whether your job experiences have been customer-facing or behind-the-scenes, it is likely that you have been exposed to data in some way, shape, or form. Take note of these experiences and use them to position yourself for a more advanced one in the realm of analytics. You know more than you think you do.

Reflect upon the words of inventor Benjamin Franklin. He makes the case for the value of on-the-job training. Franklin stated, “Tell me and I forget, teach me and I may remember, involve me, and I learn.”

Certifications in Analytics

Getting certified is another way to delve more deeply into a data tool. With this, you can quickly acquire new skills in a specialized area. There are certificate programs designed for each and every knowledge level, i.e., from the newbies to the experts. These will help make you more attractive in your current job, gig, or marketable for new opportunities.

Choose from getting certified in Data Analytics and Data Science. Dig deeper into the subject matter of an Analytics Professional, Data Platform Generalist, and/or Business Analyst. Every field of analysis is open for study. 

Speaking in general terms, certificates are offered for an array of vocations. They are also focused on a single skill. For this reason, programs are often short-term and continue for the duration of a year or less. Certificates are awarded to those who have mastered a special area of study.

The track for certification is unique. The focus is on practical training rather than a framework that is centered on academics.

Similar to boot camps, certificates may or may not take place in a higher-ed setting that is linked to a college or university. And like most learning pathways, these are to be made accessible with just a click of a button.

Internships in Analytics

Internships have always been a great way for people new in a field to gain relevant know-how. Many students and trainees will opt to work in an organization, sometimes without pay, just to get their foot in the door. It’s the chance to acquire hands-on experience. Some may be leveraged to satisfy a requirement in a program.

The job duties of an intern may vary and will often include tasks in clerical and administration. The scheduling of appointments, sorting of files, and data entry are all good ways to get to know a new area in the business sector. 

These job-training programs will vary. Some can be completed in 10 to 12 weeks or for a semester, while others may last for an entire year. It’s pertinent to note that such experiences are the surefire way to get insight into what it is like to work in the data space.

At the same time, your peers will be taking note of your ability to navigate your role as an intern. It is a win-win in determining if this would be a good long-term company and career fit. 

The linkage between internships and hiring is positive. According to recent stats, 70 percent of interns are hired at the company in where they had previously interned. This makes the case for assuming an internship even if the position is not well paid or results in a weekly or monthly stipend. 

Scholarships in Analytics

Education in STEM has been a focal point in the United States for the past twenty years. In 2017, the Administration prioritized science and technology training with a $200+ million annual budget for school grants. 

Technology training remains front and center. The Science and Technology Council has doubled its size in just the past few years. Government leaders in the U.S. recognize the importance of technical expertise at the national and global levels.

It is for this reason that scholarships and grants for the learning of analytics are so widespread. Businesses and nonprofits are on the same page in their mission to offer incentives for the purpose of STEM.

Analytics is a skill that is coveted. Some companies will offer tuition reimbursement as part of their benefits package. If you are currently employed, check in with your HR department. Educational perks are trending in businesses all over the country.

How AI is changing analytics careers

By 2026, being proficient in analytics will have become a basic skill for professionals across industries.

However, true expertise will be marked by AI fluency—analysts who can effectively leverage large language models to automate tasks and gain deeper insights will stand out as leaders in their fields.

Key AI skills to master

Skill	Description	Why It Matters in 2026
Prompt Engineering	The ability to write precise, detailed natural language commands to get the best output from AI tools (e.g., generating SQL, cleaning Python scripts, summarizing findings).	It accelerates the creation of boilerplate code, queries, and initial insights.
Output Validation	Critically checking the code, models, and conclusions generated by AI for logic, accuracy, and bias.	AI is a powerful assistant, not a replacement. The analyst is still accountable for data integrity.
Synthetic Data Generation	Using GenAI to create realistic, artificial datasets for training models or ensuring data privacy when real data is sensitive or scarce.	Allows for robust testing and development in environments where real-world data is restricted.

Emerging Career Paths

Let’s look ahead to the inventions in analytics and data science that are currently trending in both the US and abroad. For college graduates or individuals preparing for their futures, it is important to know where you can put your new skills to good use. 

When it comes to industries, the options are endless. Are you drawn to finance or healthcare? Perhaps you find social justice most appealing. It is simply a matter of what motivates and interests you on a personal level. Consider these as well:

• Digital Marketing
• Automotive
• Healthcare
• Telecom
• Retail
• Agriculture
• Banking
• Government/Public Sector
• Mining, Oil & Gas
• Cybersecurity

You need not look very far to find businesses that are hiring. Companies are in sync with the outlook of thought leaders like Tim Berners-Lee, inventor of the World Wide Web. He proclaimed, “Data is a precious thing and will last longer than the systems themselves.” 

If you wish to venture towards what promises to be the most cutting-edge in tech, explore the fields of Artificial Intelligence (AI) and Machine Learning (ML).

Key Takeaways for Getting into Analytics

By 2026, building a successful analytics career will increasingly rely on AI augmentation, transforming the traditional skill set. Instead of focusing solely on manual coding, professionals will need to develop fluency in AI tools and techniques.

Mastering prompt engineering and validation will be essential for effectively leveraging AI models, while foundational skills like SQL and Python remain important for data management and analysis.

However, the most valuable abilities will be domain expertise, storytelling, and critical thinking—areas where AI cannot replicate human insight. These skills enable analysts to interpret data meaningfully, communicate findings compellingly, and make strategic decisions.

As the landscape evolves, a blend of technical proficiency and soft skills will be key to standing out and delivering impactful insights in an increasingly AI-driven world.

Frequently Asked Questions