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Why You Should Consider a Career in Data Analytics

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Alert: approaching maximum storage capacity. 

The world’s data use increases each year, with a forecast of 147. zettabytes created, consumed, and stored in 2024 – which is enough storage for 55 billion 4K movies.

This is a good thing – right? More data means more innovation, which means more advancements for society. 

Not necessarily. 

Think of data the same way you think about a library. There are so many books in one place (which is awesome) but it’s only useful if you know: 

  • How to find the information you need.
  • And how to apply it. 

Businesses have more data than ever before – about their company, their customers, and the world – but no one to tell them what it means. 

That’s where data analysts come in. 

WHAT DO DATA ANALYSTS DO? 

When there’s a problem, data analysts help solve it. 

The first step to addressing business challenges is gathering information (data) and finding answers and insights to guide companies towards better decisions. That’s the role of the data analyst. 

For example, a company may want to know which segment of customers is driving the most revenue from a marketing campaign. 

The data analyst will gather all the data related to the campaign. This may mean exploring customer demographics, marketing acquisition sources, behavioural data, and purchase data. 

They’ll look for notable statistical findings. They’ll form these into insights and create written and/or visual reports to help stakeholders learn and apply the findings to their future campaigns. 

As a distinction from data scientists, data analysts typically work with structured data from a single source and provide historical analysis as opposed to predictive modelling.

WHY SHOULD YOU CONSIDER A DATA ANALYTICS CAREER? 

The most obvious reasons to work in the field of data analytics include these top three reasons: 

  1. You’re dealing with data, numbers, and statistics, but you still get to creatively work to solve problems. 
  2. You’re paid well for this skill.
  3. Data keeps growing and so will the need for data analysts. 

But there are other benefits that may not be quite so apparent: 

  • Most employers are interested in talent with skills. There is not a big focus on degrees and further education. 
  • Many data analyst jobs are remote. No more commuting!
  • The technical skills you learn are easily transferable to other jobs like coding, data science, and more. 

5 TOP JOB TITLES FOR DATA ANALYSTS

What kind of jobs can you get as a data analyst? There are varying specialities and job titles in the field of data analytics. Here are some job titles you may see in this family of jobs:

DATA ANALYST

Related job titles: Junior Data Analyst, Entry-Level Data Analyst, Associate Data Analyst

You can find a data analyst at nearly every company in the world, in every industry imaginable. The average data analyst needs to know some basic programming languages like Python and SQL, and they should be comfortable running statistical analyses and visualising data. 

OPERATIONS ANALYST 

Related job title: Operations Research Analyst 

An operations analyst focuses on the inner workings of a business, helping it run more efficiently. They typically work for larger companies or they work at consulting firms employed by bigger businesses.

MARKETING ANALYST 

Related job title: Market Research Analyst 

One of the biggest parts of any company’s budget is the money they spend on marketing efforts. A marketing analyst looks at market, campaign, and demographic data to ensure companies are executing marketing efforts in the most cost-effective and impactful way possible.

BUSINESS INTELLIGENCE ANALYST 

You’ll spend your days as a BI analyst looking for patterns in your company’s data. You’ll have to make sure you’re good at communicating and that you enjoy visualising data and modelling future scenarios. 

Is a business analyst the same as a data analyst? While the skill sets are similar, there are some differences. Here’s our take on business analyst vs. data analyst. 

LOGISTICS ANALYST

Logistics analysts look at every stage of a production process and product lifecycle. They may analyse supply chain flows and find areas of improvement to increase efficiency and profit for a company. 

DATA ANALYST CAREER OUTLOOK 

Companies, including retailers, investment banks, big tech, and professional services (including accounting and insurance), are all ramping up their data analytics workforce. Other industries hiring for data analysts include logistics, healthcare, government, and sports. 

ARE DATA ANALYST JOBS IN DEMAND? 

The Singapore Economic Development Board (EDB) stated that the data science industry in Singapore contributes an estimated $730 million (USD) to the economy annually. Operations research analysts and market research analysts are also high-growth job categories. 

WHAT’S THE AVERAGE SALARY WORKING IN DATA ANALYTICS? 

In Singapore, the median salary for a data analyst is SGD $99,000, with the middle 50% earning between SGD $75,000 and $137,000. Of course, how much you can earn as a data analyst depends on several factors including education, experience, industry, and geography. For example, the median data analyst salary in the United States is $113,250, with the middle 50% earning between $93,000 and $134,000. In Australia, the typical data analyst salary is in the range of AUD $114,500 and $143,500

Experience and industry can also have an impact on your expected salary. An entry-level data analyst in Singapore’s financial services industry, for example, earns a median salary of SGD $60,000, while a senioranalyst in the same industry earns SGD $74,000 and a director in analytics earns SGD $132,000. 

HOW TO BECOME A DATA ANALYST

Most data analytics jobs require a bachelor’s degree. Degree programs in mathematics, statistics, business, or economics are ideal, but college grads can re-skill for data analytics with any major. 

There have never been more options for individuals to skill up for a career switch, and some employers will even pay for it because of fast-changing business needs. Here are twoways to gain the data analytics skills you need to fast-track a new career in this field:

#1: PART-TIME DATA ANALYTICS COURSE

If you have a full-time job or other responsibilities, a part-time course can be a good option and offers accountability for a set curriculum and timeline. However, the part-time model takes longer to finish and longer to reach the job market than a full-time option. 

#2: FULL-TIME DATA ANALYTICS BOOTCAMP

What is a data analytics bootcamp? Bootcamps provide immersive, intensive training for entry-level professionals in a field. Bootcamps can be in-person or online and are instructor-led, often with multiple speakers and mentors for a course and a cohort. 

So, which option is the best for you? It really depends on your background and learning style.  

If you have transferable skills and experience, you may only need to brush up on a programming language like Python to make the leap. If you’re coming from an unrelated field or from a career break, a more immersive, structured program like a bootcamp may be your best bet to get job-ready. 

GO FROM BEGINNER TO DATA ANALYST IN 12 WEEKS

General Assembly’s Data Analytics Bootcamp is designed for complete beginners. Get hands-on training from actual data analysts working in the field, and graduate in just 12 weeks ready for your first data analyst job. It’s the most direct route to your new data analyst career.

Data And AI: Best Friends Or Foes Of The Future?

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Estimated reading time: 5 minutes

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If you work in data, chances are you’re hearing a lot of buzz about AI and how it’s going to automate everything. While the headlines spell doom and gloom for knowledge worker roles like yours, the reality isn’t quite so dark. In fact, there won’t be any future of AI without people like you, who have the skills required to prepare and use data. 

Right now, AI adoption is in a strange phase. The media is telling you that you could be replaced by it, but your day-to-day probably hasn’t changed all that much. You might be thinking that this all seems like a bunch of hype… and you wouldn’t be wrong. That’s because most companies’ use of AI is still in its infancy. 

While 94% of companies say they are using AI today, most aren’t using it to its full potential. They’re struggling with data quality and infrastructure issues that make layering on AI nearly impossible. In the same study, almost three quarters of execs said that data issues would be the most likely reason they fail to achieve their AI goals. As it turns out, even a robot can’t make lemonade out of bad data. 

This is where you, and your skills, step in to save the day. And you’re in higher demand than ever before. There’s been a 2,000% surge in roles requiring AI skills, such as data science and data analytics. 

Before you breathe a sigh of relief, it’s important to recognize that your skills will need to evolve for an AI-led future. Let’s dig into exactly how. 

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Teching Care of The Planet: How Tech Skills Can Promote a Greener Earth

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Technology plays a crucial role in cultivating a greener earth by enabling the development of innovative solutions for environmental challenges. Some of these technological advancements include renewable energy sources, energy-efficient devices, green transportation, and sustainable agriculture practices. 

Over the last few years, we’ve seen how the demand for green or sustainable tech jobs has increased. According to a report by LinkedIn, there has been a 191% increase in the number of sustainability jobs posted on the platform since 2016. Additionally, the report found that sustainability jobs are not limited to specific industries and are found across a range of sectors, including technology, finance, and energy.

In this blog, we will look at how technology is leading innovation for a better and greener environment, identify some of the most popular tech jobs in sustainability, and what digital skills you need to acquire to combat environmental challenges in your career. 

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Top 5 Industries Hiring Data Analysts and Data Scientists

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Without data, humans make decisions based on intuition. However, we don’t make very good decisions with our gut. That’s because as humans we have our emotions, unconscious biases, and gaps in information to contend with. 

Everyone makes better decisions with data. For a business, poor leadership decisions can be incredibly costly. But companies don’t just need to collect data—they need professionals who can analyze and interpret it. That’s where data analysts and data scientists come in. 

Glassdoor and U.S. News & World Report have both named data scientist among their best jobs based on salary, job satisfaction, and career opportunities. Data analysts earn a median base salary of $66,370 in the U.S., while data scientists earn $103,525 on average. If you’re ready to jump into your first data analyst entry-level job, read on for how to break in and the top industries hiring data analysts and data scientists. 

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What Jobs Can You Get After a Data Analytics Bootcamp?

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Article reviewed by: Megna Murali

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In 2022, the estimated data generated equaled 97 zettabytes (that’s nearly 100 billion terabytes). As companies generate more data, they need data analysts to interpret it. With an acute skills shortage, entry-level data analyst jobs are a great place to start or restart a career.

According to research from the World Economic Forum, data analysts and scientists are the most in-demand job worldwide. Data analysts help companies solve business problems by collecting, cleaning, and interpreting data with statistical methods and analysis software.

Since the field is evolving and growing so fast, four-year degree programs can’t produce graduates fast enough or keep up with the changing skills needed for the workplace. One option to bypass the four-year degree or switch careers into data analytics is to complete a data analytics bootcamp.  

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How to Become a Data Analyst in 4 Steps (No Degree Required)

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Making a career change can be scary, especially if self-doubt of “I’m not good enough” starts creeping in. However, there is no point in staying in a job or career that no longer brings you joy or fulfills you professionally. 

If you’re reconsidering your career, you’re not alone — over the last two years, over 50% of employed Americans have considered a total career revamp. Chances are, you know a relative or friend who is going through a similar career dilemma right now.

If you’re considering making a bold move to data analytics, we’ve got you covered. Understand if a career in Data Analytics is right for you in four easy steps.

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5 Key Excel Skills You Can Learn in Minutes

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Since it was created in 1985, Excel has practically become synonymous with data itself, and still is many years later. Spend a few minutes with our expert instructor in the videos below to learn the kinds of Excel tools that can help you be your own analyst—and make smarter decisions with data. 

How to Create an Excel Bar Chart

Bar charts are an important visual tool that can help express your data over time and tell a story in a visually appealing and digestible way. Learn more in our 2-minute lesson below:

How To Create an Excel Pivot Table

Pivot tables allow you to effectively summarize and highlight the importance of your data sets. They are an important presentation tool and can help you simplify your data. Learn more in our 3-minute lesson below:

How To Create a Histogram in Excel

Histograms provide a visual representation of variations within your data and can help display degrees of difference in an impactful way. Learn more in our 2.5-minute lesson below:

How To Create a Pie Chart in Excel

Pie charts can express percentages of a whole and represents a set period of time and can be helpful to show differences among a handful of categories. Unlike bar charts, it does not express changes over time. Learn more in our 2.5-minute lesson below:

How To Create a VLookup in Excel

A VLookup (vertical lookup) can help you lookup data that is organized vertically. It is useful in helping you spot trends and find important pieces of data that can be difficult to locate in large data sets. Learn more in our 2.5-minute lesson below:

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A Beginner’s Guide To Tableau

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Estimated reading time: 3 minutes

Featuring Insights From Iun Chen & Vish Srivastava

What is Tableau

Tableau is a powerful data analysis and data visualization tool that anyone can use. It can be used by beginners to create simple charts and by advanced practitioners to solve complex business problems. It is user-friendly, easy to learn quickly, and includes a portfolio of business intelligence tools with the potential to give a wide range of roles the advantage of professionally analyzing data.

Simply put, if you can present data in a clear, compelling format, you gain a competitive advantage in today’s data-driven marketplace.

“Tableau enables you to quickly connect disparate data sources and utilize a drag-and-drop interface to analyze data and create dashboards,” says Vish Srivastava, who leads our Data Visualization & Intro to Tableau workshop. As a product leader at Evidation Health, he relies on Tableau to turn around fast data analysis. “For example, product teams use it to analyze user growth and analytics, BizOps teams use it to analyze operational data, and sales teams use it to analyze customer and revenue data.”

Businesses survive and thrive on data. The amount of data available to businesses today is impressive. To keep organizations on a successful path, analysts need to provide the key insights needed to make important decisions.

Here’s where Tableau comes in.

Tableau takes business intelligence to the next level, making it fast and efficient to analyze large amounts of data and create beautiful, presentation-ready visualizations that generate insights.

Data is the lifeblood of modern teams. Being able to quickly answer ad hoc questions and integrate data analysis into your day-to-day decision-making will make you an MVP. Though not all data analysts use Tableau, they do need some way to quickly create data visualizations.

Tableau is the data viz tool of choice.

Tableau is so popular in part because it is easy and fast to learn. In Iun Chen’s Intro to Data Analytics course, students learn the life-changing basics of Tableau in an afternoon. Aspiring analysts come to understand the power of data and the impact their numbers can have. As more data becomes available, there are more opportunities for data to be misused, a risk that every data scientist soon realizes. To quote the Nobel laureate and economist Ronald Coase, “If you torture the data long enough, it will confess.”

The ethics of data form the foundation of Chen’s syllabus so pitfalls are avoided from the start. “Overanalyzing and manipulating data too deeply can always give you the information you want,” says Chen. “Unfortunately, this is all too common in professional settings, though it’s usually unintentional.”

What features does Tableau offer?

  • Tableau Accelerators
  • Data Stories
  • Predictive Modeling and more

Tableau is a powerful tool.

Business insights are only as good as the data behind them, and the best data analysts understand that the human choices they make matter.

“Data is the perfect example of garbage in, garbage out,” says Srivastava, who defines good data as data that is ethically collected, complete, objective, and thoroughly analyzed. ”The double-edged sword of using powerful data analysis and visualization tools is that beautiful charts can create a false precision and obfuscate data integrity issues.”

To delve deeper into this topic, Chen recommends How Charts Lie, by Alberto Cairo, an exploration of how data can be altered:

“This book details how the use of data and data visualizations in journalism can be distorted and misleading, without the audience even realizing it, due to the urgency to present findings in a timely manner to the public.”

Want to learn more about Iun?
https://www.linkedin.com/in/iunchen 

Want to learn more about Vish? https://www.linkedin.com/in/vishrutps

7 Tips to Learn Tableau Fast

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Featuring Insights From Iun Chen & Vish Srivastava

Read: 2 Minutes

Let’s get it straight: How difficult is it to learn Tableau for a complete beginner? Are there shortcuts to learning Tableau? Any tips, tricks, or time-saving work-arounds? Thankfully, the answer is yes. Try these top tips, approved by our expert instructors, and start data viz now.

“It’s a little overwhelming at first but as soon as you understand the basics, like what are dimensions and measures, everything falls into place pretty quickly,” says Vish Srivastava, product leader at Evidation Health and GA instructor.

“In essence, you need to understand two things: The basics on how data works — for example, what are common formats of data and what is a primary key? And a basic understanding of data visualization in a business setting. Can you answer the question: When is a time series vs. a pie chart valuable for decision making?”

But can you really learn the basics of Tableau in an afternoon?

“The best way to learn is to download a sample dataset and dive right in and start creating data visualizations. To keep going from there, check out various portfolios online to get inspiration, and try to build those.”

According to Iun Chen, who conducts internal Tableau training at LinkedIn, Tableau is easy to learn, but hard to master.

“The basic concepts of charting and color theory are easy to pick up and can take just a few weeks. However, if you are looking to be a subject matter expert, this can take years to perfect,” she says. 

Chen preps students in her Intro to Data Analytics course to achieve close-to-mastery in these key areas.

  1. Can they quickly prep and analyze large volumes of data?
  2. Identify key information and determine the best visual method to present them?
  3. Take business questions and determine which visualizations to use?
  4. Translate raw datasets to storylines with a beginning, middle, and end? 
  5. Format charts, graphs, titles, text, and images for a polished deliverable? 
  6. Articulate best practices on design and visualization techniques?
  7. Provide feedback on ineffective visualizations and how to improve them?

    This checklist is the closest thing to a Tableau cheat sheet you’ll find. Prioritize these skills, and you’ll waste no time learning Tableau. Now that you know what you need to succeed, you can choose whether to take our Data Analytics course fast or slow. Learn Tableau — along with data analytics tools SQL and Excel — in a 1-week accelerated format, or over 10 weeks in the evening.

Chen sums it up perfectly: “As long as you are actively learning, applying your learnings, and ensuring innovation of your work, you will be a data visualization expert in no time.”

Want to learn more about Iun?
https://www.linkedin.com/in/iunchen 

Want to learn more about Vish? https://www.linkedin.com/in/vishrutps

Top 3 Reasons To Learn Tableau

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Featuring Insights From GA instructor Candace Pereira-Roberts

Read: 2 Minutes

Do you communicate data? Do you want to create more effective data visualizations? Tableau is the data analytics tool you’re looking for. Here are the top three reasons why you should learn how to use Tableau, the popular data viz software focused on business intelligence. Read on for the advantages of being a Tableau professional.

#1 Tableau Is Easy

Data can be complicated. Tableau makes it easy. Tableau is a data visualization tool that takes data and presents it in a user-friendly format of charts and graphs. And here’s the rub: There is no code writing required. You’ll easily master the end-to-end cycle of data analytics.


Need to showcase trends or surface findings? Tableau will make you an expert. Proficiency in business intelligence is a transferable skill that is quickly becoming the lifeblood of organizations. 

“I see students who are new to analytics learn Tableau desktop and be able to develop Tableau worksheets, interactive dashboards, and story points in a couple of weeks — essentially a complete data analysis project,” says Candace Pereira-Roberts, FinServ data engineer and one of our Data Analytics course instructors. She adds, “I like to share knowledge and watch people grow. I learn from my students as well.” 

 #2 Tableau Is Tremendously Useful

Would you rather tell visual stories with data? Or present the same old boring reports and tables? Is that even a question?

“Anyone who works in data should learn tools that help tell data stories with quality visual analytics.” Full stop.

The smart data analyst, data scientist, and data engineer were quick to adopt and use Tableau tool by tool, and it has given those roles a key competitive advantage in the recent data-related hiring frenzy. But their secret is out. And the advantages go beyond the usual tech roles. Having a working knowledge of data, and specifically knowing how to use Tableau, can help many more tech professionals become more attractive to recruiters and hiring managers.

Plus, it has a built-in career boost. Tableau’s visualizations are so elegant, you’ll be confident presenting the business intelligence and actionable insights to key stakeholders. Improving your presentation skills is par for the course.

#3 Tableau Data Analysts Are in Demand

As more and more businesses discover the value of data, the demand for analysts is growing. One advantage of Tableau is that it is so visually pleasing and easy for busy executives — and even the tech-averse — to use and understand. Tableau presents complicated and sophisticated data in a simple visualization format. In other words, CEOs love it.

Think of Tableau as your secret weapon. Once you learn it, you can easily surface critical information to stakeholders in a visually compelling format. That will make you a rockstar in any organization. 

“Tableau helps organizations leverage business intelligence to become more data-driven in their decision-making process.” Pereira-Roberts says. She recommends participating in Makeover Monday to take your skills to an even higher level. 

Take Our Free 2-Hour Data Visualization Class

Want to learn more about Candace? Check out her thoughts on how to become a business intelligence analyst, or connect with her on LinkedIn.