Data Category Archives - General Assembly Blog

Celebrating the Rise of Mothers in Tech: Helping Moms Make Waves in Software Engineering, Data Analytics, Data Science, and UX Design

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Let’s face it — Mother’s Day should be every day. But officially, every second Sunday in May, we have the special day to honor and celebrate the incredible women who’ve shaped our lives and inspired us to reach for the stars. 

In the world of technology, there are countless moms not only balancing the demands of motherhood, but also making significant contributions to fields like software engineering, data analytics, data science, and user experience design. As we celebrate Mother’s Day this year, let’s shine a spotlight on some of the trailblazers helping moms make waves across tech disciplines.

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Celebrating AAPI Tech Trailblazers: Pioneers in Software Engineering, Data Analytics, Data Science, and UX Design

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At General Assembly, we know the power that comes with people being able to pursue a meaningful career they love. And we’re excited to be able to celebrate Asian American and Pacific Islander (AAPI) Heritage Month by highlighting AAPI tech trailblazers who’ve made their mark on our core bootcamp disciplines — software engineering, data analytics, data science, and user experience (UX) design. 

AAPI talent has long played a pivotal role in shaping the landscape of the tech industry. From software engineering to data analytics, data science, and user experience design, AAPI tech trailblazers have made significant contributions that have revolutionized how we interact with technology. Here are just some of the remarkable individuals who’ve blazed trails and left an indelible mark on the tech world.

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Introducing the Most Flexible Way to Break into a User Experience Design or Data Analytics Career: GA’s New Part-Time UX Design and Data Analytics Bootcamps

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We recently introduced our new part-time Software Engineering Bootcamp, giving learners the unique ability to hit start on a new coding career without pressing pause on their life. The response has been overwhelmingly positive, and we’re excited to announce two more new part-time bootcamps to our program mix — a part-time UX Design Bootcamp and a part-time Data Analytics Bootcamp.

All our part-time bootcamps are specially designed to fit learning into your life — understanding your schedule is already action-packed. Now you have the opportunity to learn at your own pace and dedicate time when it works for you. To learn without having to quit your job. With our new part-time bootcamps, in just 15 hours a week, you get the tech skills you need to jumpstart your new career. 

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Applied AI Engineering Workshop: The Latest Skills for Software Development and Data Science

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The groundwork has been laid for what many consider the dawn of the fourth industrial revolution, propelled by transformative artificial intelligence. GenAI, debuting in 2023, gains momentum in 2024, with a rapidly growing market valued at $22.12 billion, expected to achieve a 46% adoption rate by 2025.

In short? Now’s the time to bring your teams up to speed to stay ahead of the curve.

You don’t have to look far to see how AI is benefitting industry. AI algorithms are already enhancing security with city-wide drone detection, driving efficient recycling, revolutionizing accessibility, skyrocketing creativity, and addressing complex societal concerns.

Ethics, data visualization, and AI are all cornerstones of a data-driven culture. Companies who put data at the heart of their operation outperform competitors in revenues by 16%, operational efficiency by 23%, and customer retention by 32%.

Given the transformative potential, it’s no surprise 25% of global workers deem AI skills crucial. Yet, 66% of senior IT leaders say their employees need more AI skills to harness predictive analytics and machine learning.

There’s no time like the present. Let’s get started.

General Assembly’s Applied AI Engineering Workshop, designed for existing software engineers and data scientists, builds core AI competencies, empowering your team to become enablers of GenAI throughout your organization.

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Why You Should Consider a Career in Data Analytics

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Singapore learner on laptop

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 Skills: What Professional Service Consultants Need To Know

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As a strategic consultant, you know your clients are eager to talk data. From mining to analysis to modeling, they’re keen for you to extract meaningful insights and use them to shape forward-thinking strategies that address their most pressing challenges.

Maintaining leading-edge data skills is a top business imperative for all professional service firms — but how do you make sure you — and every new employee that joins your ranks — are sharpening data competencies to the highest standard? 

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Mastering Data Analyst Skills for Future Success

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data analyst smiling in front of whiteboard

In today’s interconnected world where information reigns supreme, strong data skills are a powerful lever for professional success, opening doors across diverse roles and industries. As 2024 gets underway, there’s never been a more opportune moment to embark on a new career path or elevate your current role. 

The question remains: which data skills do you need, and how can you acquire them quickly and effectively? 

Let’s take a closer look.

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5 Ways to Build a Data-Driven Culture

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Two men and a woman sit in a business lounge area having a discussion about making data-driven decisions.

Estimated reading time: 5 minutes

What do ship captains and business leaders have in common? 

They both need to navigate through stormy and calm seas, constantly charting course across uncertain and hostile waters. While captains often turn to their maps, radars, and compasses, business leaders need to turn to their data.

Data helps you nail down the strategic plan for achieving your business objectives. Data keeps you on course. And data enables you to change course when needed. 

But here’s the thing — your business is a large vessel with multiple departments (like a large luxury liner) that must succeed in their respective journeys. One misstep in one department could affect your overall company journey. 

All departments must know how to handle their chief navigation equipment — data.

When data-driven decision-making becomes a company-wide practice, it positions your business for sustainable success. Data-driven companies are 58% more likely to exceed their revenue goals. 

So, how do you cultivate a culture where every department leverages data to succeed in their roles? And have everyone collectively steering your organization towards its goals? Let’s find out.

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A Breakdown Of Data Science Vs. Computer Science: History, Applications, and Career Paths

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Article reviewed by: Shilpa Sindhe

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Estimated reading time: 9 minutes


Trying to wrap your head around the difference between data science and computer science? 

Many of the luxuries that we have today — a favorite streaming service that recommends new movies, the ability to unlock our phones with facial recognition technology, or virtual home assistants that let us play our favorite music just by speaking — are made possible by computer science and made better by data science.

Today, these two fields complement each other to further applications of artificial intelligence, machine learning, and business forecasting. Read on to learn a definition of each, their histories and applications, and career paths in computer science and data science. 

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

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Estimated reading time: 5 minutes


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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