Your Guide to Online Data Analytics Bootcamps in 2020

In today’s tech-driven society, data touches almost every aspect of our lives.

The field of data analytics combines information technology and business management to help companies manage data, gain business insights from it, and develop opportunities for expansion. 

Read on to learn more about job market predictions and skill requirements, as well as our top picks for the best online bootcamps and how to choose one that best fits your needs. 

What Are Online Data Analytics Bootcamps?

Data analytics bootcamps offer short, knowledge-intensive programs to teach students professional skills. The curriculum, layout and duration of each bootcamp will vary based on the course in which you are enrolled. Some bootcamps may focus on the basics of working with big data, while others dive deep into specific subjects—such as visualization and statistics. You should attend an online bootcamp that aligns with your interests and career goals.

Data Analytics vs. Data Science Bootcamps

While many people use the two terms interchangeably, data analytics and data science have unique qualities, with the main difference being their scope. Bootcamps focused on these two disciplines have substantially different subject matter. 

Data Analytics Bootcamps

Data analytics focuses on processing and implementing statistical analysis with ongoing sets of data. Bootcamps in this area study the creation of methods to capture, manipulate and sort data to uncover insights for problems. They also establish ways to present this data to businesses. Above all, data analytics is based on generating results that can lead to immediate solutions.

Data Science Bootcamps

Data science is a cross-cutting field focused on digging up insights from big sets of raw data. Bootcamps on data science and workers in the field often focus on finding answers to the things that may not be known already, compared to analytics, which is seeking specific insights. Data science experts use a number of techniques to get these answers, from incorporating computer science and predictive analytics to machine learning. A data scientist’s primary objective is to ask questions and identify potential avenues for additional research. There is less concern for specific resolutions and more on finding the right questions to ask. 

Popular Data Analytics Tools

The online software used at a data analytics bootcamp often varies from what is taught at a coding program. Here are some of the most popular tools used in the profession, along with their purpose.

• R (programming language) is the most common analytics tool used in the industry. It is open-source software that provides statistics and data modeling. It can be applied to examine data and create software or other applications that can carry out statistical analysis. R also supports computer platforms like MacOS, Windows and viz -UNIX. 
• Microsoft Excel is another universal program used by many industries. It enables a user to quickly summarize data by creating pivot tables from a range of rows and columns. Before learning about advanced analytics software, it’s recommended that one master the ins and outs of Excel to develop a broader understanding of data analytics. 
• SAS (statistical analytics software) is a tool made for statistics, business intelligence (BI) and data management. It helps organizations in all focus areas make better business decisions. Users can access it through GUI (graphical user interface) and the SAS programming language, which allows one to retrieve, report and analyze big data. 
• SQL is an acronym for Structured Query Language. It was designed to store, manipulate and collect data that is kept in a relational database. Industries rely on SQL to pull out data for data analytics and reporting. 
• Tableau is a cloud-based data visualization tool used in the business intelligence field. It simplifies raw data into easy-to-use charts, dashboards and worksheets. These formats can be shared with anyone, allowing it to run seamlessly across all systems. 
• Apache Spark is a unified data processing system made for big data operations. In addition to the Spark core processing engine, there are libraries for SQL, machine learning, graph computation and other applications that can be used collectively. App developers and data analysts include Spark in their programs to query, analyze and transform data at the scope.

What Skills Will You Learn?

The specific skills you will learn at a data science bootcamp vary widely based on the structure of the bootcamp, goals and instructors or hosting institution. Many bootcamps will work on how to use some of the tools listed above, as well as other manipulation tactics for data. Some common skills in courses include:

• Python Fundamentals offers a basic introduction to essential programming concepts and the Python programming language. Python is a general-purpose coding language that’s used for web development and other types of programming software, such as mobile apps. Many online bootcamps will teach you how to use loops, lists and dictionaries, strings and conditionals. 
• SQL Queries allow data analysts to create tables and select data in various ways. You can learn how to communicate with relational databases through SQL and make queries that interact with multiple tables.
• Anaconda is a Python and R distribution that makes it simple to install a number of libraries. Upon the completion of a data analytics course, you’ ll be able to understand best practices for machine learning, package management, visualization and statistical modeling.
• Jupyter Notebooks is an open-source web tool that allows you to build and share documents that contain live code, visualizations, equations and narrative text. This will help you write lines of code and run them one at a time, making it easier to perform data analysis. 
• Numerical Models are used in predictive analytics to forecast model deals in a mathematical form, estimating numeric value for new data through insights from previous data analysis. There are several numerical analytics classes that will teach you everything from machine arithmetics to data simulation. 
• Tableau gives you the chance to explore, experiment with, fix, prepare and present data in an instant. Having experience with Tableau sets you on a path to learning technical skills needed in today’s job market. 
• Data visualization uses computer technology to make images, charts or animations that deliver clear and concise information. As businesses become increasingly data-driven, learning this skill will be essential to many roles in this field. An online class will provide you the opportunity to practice and engage with data visualization tools like Tableau and Microsoft Power BI.

Each bootcamp is unique. When evaluating what course you want to take, consider the curriculum and compare it to your current skill set. 

How To Choose The Best Online Data Analytics Bootcamps

Trying to find an online bootcamp that fits your needs can be overwhelming. Although there is no perfect formula for choosing the right program, you can take a few steps to make things easier.

Step 1: Rank and Identify Your Priorities

By outlining your priorities and evaluating each program, you can figure out which one works for you. Take some time to weigh the pros and cons of all your ranked choices. It’s important to carefully consider your needs and goals when thinking about where you’ll spend the next few weeks or more. 

Step 2: Develop a Shortlist of Your Top Choices

Creating a robust shortlist is a key step to narrowing your options. Compare class sizes, program highlights, costs and selectivity.

Step 3: Investigate Career Outcomes 

One reason to attend an online bootcamp is to set yourself up for a job. Students should check to see if mentorships, interview coaching, and resume workshops are offered outside the classroom to ensure the bootcamp provides the help you need.