Over half the world’s population is online, and we’re generating more data than ever. As businesses get their hands on our increasing amounts of customer information, new techniques and tools are being developed to make sense of it all. Talented data analysts are powering marketing campaigns, improving internal processes and, ultimately, boosting revenues. So it’s no wonder that this career is in hot demand.
To help you understand the learning pathways into data analytics, this article sheds light on the field, how it differs from data science, and the best ways to upskill in the core knowledge areas. We’ll also discuss the range of onboarding and support you can expect as you embark on your learning journey.
Data Analytics Vs Data Science
Data analytics focuses on practical insights that can be gleaned by detecting patterns and making predictions. It’s best suited to situations where there are focused questions to be answered. Many organizations use data analytics to make informed choices.
Data scientists often utilise data analytics to test out their theories and hypotheses. Depending on the application, the data used can be either new information or historical records from varied sources. While it’s sometimes confused with data science, data analytics is a markedly different field.
In comparison to data analytics, data science is broader in its scope. In fact, it’s probably safe to say that data analytics is a subset of data science. Data science is about making estimations by working with algorithms and building statistical models. Instead of answering a specific question, as in the case of data analytics, it instead involves analyzing massive data sets (structured or unstructured) to unearth insights. Hopefully that clears things up, but you can also read more about the key differences.
A Career in Data Analytics
There’s no question that data analytics roles pay well. The average data analyst in the US takes home $76,000 a year. And if we’re talking about a senior data analyst role in a major city, that figure could be anywhere up to around $210,00 per year. It’s also a very versatile field, so you can be sure that you’ll never get bored.
It’s true that some companies have begun working on automating data analytics, but this can only be applied to around 20% of the work. The vast majority of data analytics requires skilled professionals at the helm. So jobs in data analytics aren’t going away any time soon.
Data Analytics Schools
There are a growing number of schools providing full-time, part-time and self-paced data analytics courses. You can choose to pursue these online, on campus, or in a blended model. Once you start browsing for a course to pursue, you’ll find you’re spoilt for choice. But some of these courses are quite expensive and call for a major commitment of time. So, it’s important to make sure you understand current industry requirements, as well as your own learning expectations.
There are also a number of data analytics certifications you can earn. Most of the certifications are industry-based, so you’ll need to have decided which area of data analysis you prefer. That’s why it’s preferable to complete a data analytics course before you enrol in certifications.
We offer data analytics courses in two formats: full-time or part-time. This gives you the option of choosing the pace that suits your schedule and commitments. Below is a guide to what you can expect from our data analytics course.
This is an immersive full-time program designed to get you a job as a data analyst. The curriculum is divided into six sections:
This module covers one of the most fundamental tool required in data analysis – Microsoft Excel. You’ll learn how to use Excel and answer business-related questions by building data models. You’ll also learn about spreadsheets and their importance in business.
Storytelling with Data
This is the section where you ‘ll learn how to communicate your findings to relevant stakeholders. The most common tool used for presenting your findings as a data analyst is Microsoft Powerpoint, and you will learn how to use it for creating visually stimulating business presentations.
As the name suggests, this section will teach you the basics of SQL and relational databases. SQL (Structure Query Language) is a programming language used to communicate with data stored in a relational database management system.
In this section, you will learn to use Tableau for building dashboards for data visualization and answering business-related questions.
Business research is a crucial part of the data analytics profession. Through this course module, you’ll get acquainted with various business scenarios, questions, and approaches. You’ll also be introduced to statistical analysis.
Python has become a very popular programming language for data analytics. Python allows you to work quickly and integrate systems effectively. In this section of the course, you’ll learn how to use Python for accessing and analyzing datasets from different sources.
This is the final stage of the course where you’ll build a capstone project. Your capstone project will be a multifaceted assignment that will allow you to apply the skills and knowledge you’ve picked up throughout the course. You’ll also enhance your employability and job seeking skills by take part in two mock interviews.
How We Support Our Students
At Thinkful, we make sure our courses are in line with your expectations. That’s why we’re one of the fastest growing online bootcamps. Just because you’re learning online doesn’t mean you sacrifice support and personalized guidance. Our admissions process and ongoing support includes:
Application and Fit Interview
Looking for courses online can be overwhelming. If you’re not up on the technical terms, it can be hard to understand what each curriculum is offering. Once you complete the application form for Thinkful, one of our admissions reps will get in touch with you to explain the program structure, modules, assignments, and career path offered by the program. You can ensure you have all the relevant information about the course before you commit.
Our thoughtfully curated curriculum is highly regarded by tech industry recruiters. Most of our students get a job within 180 days of graduation. Our alumni work in big tech companies like Google, Amazon and IBM. Having former students like this in your network could help you land a position in your dream company. Come with an open mind, learn and get hired.
Learn from Experts
Data analytics as a field is vulnerable to sudden changes. So, it’s essential to ensure you’re learning the most up-to-the-minute industry practices. Our talent pool of passionate, energetic, and brilliant mentors have an average of 10 years’ teaching experience. Learn from them and be ready to enter the world’s next workforce.
Acing a job interview takes a lot of practice. Keeping calm is the secret to performing well. But this doesn’t come naturally and requires regular practice. To help you achieve this, we conduct five trial interviews throughout the course. The panel will include hiring managers from corporates to gauge your skills and problem-solving abilities. After the interview, feedback will be given to help you improve.
There are a lot of nuances to understand before applying for a tech role. To help you with this process, we assign a job coach to all students. After graduating, a personal coach will guide you in applying for top companies. They’ll stick with you for six months, after which you can waive the cost of tuition if you haven’t landed a great job.
Start Your Career in Data Analytics
If you’re serious about a career in data analytics, you’ll need up-to-the-minute expertise that’s ready to adapt to changes in technology. It’s a broad field, and the industry is prone to rapid change—so learning different tools and mastering them is vital. Read more about data analytics for beginners before you take the plunge, or for further inspiration, check out our article about five insanely cool companies that use data analytics.