How do Beginners Learn Data Analytics?

Learning data analytics is an exciting and challenging process for most learners, one that requires mastery of several related skills and tools. Once you’ve decided to embark on this learning journey, you may wonder how to get started. Before you can begin your studies, you’ll need to have the software and programming languages available that you’ll use. Next, you will select a beginner-friendly method of learning, whether it’s through free online content, self-paced materials, live courses, or some combination. Once you gain an understanding of the basics and have a solid foundation in data analytics in place, you can progress into more challenging skills.

Getting Started with Data Analytics

Before you get started studying data analytics, you may wonder what you’ll need to streamline your studies. Since data analytics is a broad field comprising a range of tools, applications, and software, you’ll likely need to have several installed or available before you can put them to use. The following sections will briefly examine some of the software and computer languages you might want to have installed or ready to use before embarking on data analytics training.

Excel 

Microsoft Excel is the industry-standard spreadsheet application and is used by approximately 750 million people around the world. This tool is widely used by data professionals in a range of careers, such as financial analytics, business analytics, and business analytics. Excel for use on computers can only be downloaded as part of the Office 365 suite of applications (which includes Word and PowerPoint). To purchase an individual or family Office 365 plan, you must have a Microsoft account. Personal plans are approximately $70 per year or can be purchased on a monthly basis for $7. Those interested in using this spreadsheet tool on their Android or iPhone can download Excel for free as a standalone app. 

Tableau

Another common data analytics tool that’s used for data visualization purposes is Tableau. This popular analytics platform is a go-to for data professionals who want to transform their data insights into engaging, interactive dashboards or visualizations. Tableau is often used alongside other business intelligence tools to find data solutions for organizational decision-makers. It provides a way to clearly express data findings that depict patterns, trends, or outliers and share them with relevant internal or external stakeholders, some of whom may not have technical expertise. Several Tableau products and licenses are available, each of which has its own unique price point:

• Tableau Creator includes Tableau Desktop, Tableau Prep Builder, Tableau Pulse, and a Tableau Cloud Creator license. This tool costs $75/user/month or $900/year.

• Tableau Explorer provides users with access to Tableau Pulse and one Tableau Cloud Explorer license. It costs $42/month or $504/annually for a license. 

• Tableau Viewer offers access to Tableau Pulse and one Viewer license for Tableau Cloud. It is offered for $15/month or $180/year.

• Tableau Public is a free option for those interested in creating and publicly sharing their data visualizations with hundreds of thousands of others online.

Tableau also offers a free trial of Tableau Desktop, which may be a great starting place if you are new to working with this software and don’t want to invest hundreds of dollars into a subscription. All Tableau products can be purchased directly from Tableau. 

Python & SQL

If you’re interested in learning data analytics, chances are you will need to have knowledge of one or more programming languages. The two most widely used languages for data professionals are Python and SQL. Python has many applications for data analytics. This object-oriented programming language is helpful for developing software and websites, in addition to automating tasks and analyzing and visualizing data. This language is especially helpful for automating tasks that must be executed repeatedly. Python has several powerful libraries that are applicable to those working with data science or analytics. These free libraries, such as NumPy and Pandas, are considered to be some of the most robust available for coding. This language can be downloaded free of charge for Windows or Macs and is available directly from Python.

SQL, or structured query language, is another staple coding language for Data Analysts. Using SQL for data analysis helps with tasks like retrieving data from databases, updating or deleting database records, creating new tables or databases, establishing permissions, and performing queries against a database. There are many benefits to working with SQL. It helps data professionals directly access huge amounts of data where it’s stored so it doesn’t have to be copied into other apps. It’s also a powerful tool for creating data warehouses because of its interactivity, accessibility, and straightforward organization. SQL Server can be downloaded directly from Windows for no cost.

Basic Understanding of Databases/Relational Databases

If you’re new to working with data, you may wish to become familiar with databases before you embark on a formal course of study. Databases are large collections of millions or even trillions of pieces of related information. A database makes it possible for users to quickly and easily sort through huge data stores. Most organizations rely on operational and production systems connected to databases that are constantly fed with streams of transactional data originating from sources like customer activity on web pages, digital footprints, and enterprise resource planning platforms. Relational databases are a type of database that organizes data into tables that can then be linked based on common data. Information contained in data points inside a relational database is organized based on defined relationships, which leads to easy access to this information. Every row in a relational database contains information pertaining to related objects. It has a key, which is a unique identifier, and every column is made up of attributes of the data. The records designate a value for each feature so that the relationship between data points is simple to pinpoint. By using just one query, relational databases allow users to retrieve a new table from data in one or multiple tables. This provides organizations with a more holistic understanding of the relationships present among all data, which can help with the decision-making process.

The First Steps When Learning Data Analytics

While all learning approaches are different, most introductory-level data analytics programs begin by providing participants with instruction on basic data-related concepts and skills they’ll need as a learning foundation for future studies. Coursework often commences with a brief overview of the data analytics process and the steps in it. This involves exploring concepts like data distributions, descriptive statistics, and inferential statistics. Students also learn about how data is gathered, why it’s collected, and what importance it has for the organization. Most beginner-level programs also teach techniques like predictive and prescriptive analytics and the role they play in aiding an organization’s decision-making. 

For learners who don’t come from a math-heavy background, reviewing basic statistical concepts early on may be useful as well. Similarly, learners who don’t have prior computer programming experience may find it useful to study basic coding concepts, such as what object-oriented programming languages are or the basic syntax used in Python and SQL.

Free Data Analytics Tools for Beginners

In addition to studying basic data analytics concepts and theories, those new to data analytics will also want to become familiar with the tools and software they’ll use to analyze data. A free trial of programs like Microsoft Excel or Tableau can be a great choice for those looking to explore these programs’ basic interface and learn how to work with core features or perform common tasks in each. Aspiring data professionals may also wish to download Python, which is free to use since this coding language will likely be a part of their data analytics toolkit as they progress with their studies.

Live Data Analytics Training for Beginners

There are many training formats available for learning data analytics. While each has its own unique advantages, most students will agree that the most effective way to learn this skill set is through live data analytics classes. These interactive courses are available in most major cities throughout the US and are also offered in the online training format using a teleconferencing platform like Zoom. They’re offered to learners at all levels, including those who are new to data analytics and need to understand the basics. Students benefit from learning from an instructor with real-world data analytics training. Participants also have the support of other learners in their cohort, which can provide an additional level of support and community. Live courses are taught in real-time, which means those who have questions can ask them as necessary and receive immediate clarification.

Because so many skills and tools are required to be a successful Data Analyst, most providers offer short skills classes in specific applications like Excel, Tableau, or Power BI, as well as programming languages. Aspiring data professionals can get started learning to work with spreadsheets in Noble Desktop’s Excel Level 1 or acquire introductory-level training in data visualization by enrolling in Tableau Level 1. Students can opt to enroll in one or more skills classes as needed. These live classes provide all the perks of live training in a fast-paced, straightforward educational environment.

The Next Step

Once you learn the basics of how to analyze and visualize data, many learners will want to take their skills even further. Aspiring data professionals or those interested in using their training toward a new career in data analytics will likely need to be familiar with various tools, skills, programming languages, and applications. This may require further training beyond a skills class. 

If you’re interested in studying one or more analytics skills during the same course, enrolling in a data analytics bootcamp is a great option. These programs provide hands-on training for learners at all levels who want to learn how to work with big data. Participants learn from an expert instructor with real-world data analytics expertise and experience. Depending on the type of bootcamp you select, you may focus entirely on one data analytics tool, such as in Noble Desktop’s SQL Bootcamp. These types of programs often combine beginner, intermediate, and advanced-level short skills classes and help learners progress from basic data knowledge into more complex concepts over several days or weeks of training. Sometimes, these bootcamps are available for a discount for those who commit to all three levels of coursework rather than opting for just one skills course.

Those looking to study the field of data analytics in its entirety may opt for a certificate program in data analytics that teaches a range of in-demand skills and tools, all as part of the same comprehensive program. Courses like Noble Desktop’s Data Analytics Certificate are available live online and in-person in New York City and provide participants with a way to take a deep dive into the skills they’ll need to succeed as a Data Analyst. Most certificate programs provide learners with more than in-depth classroom study; they also offer a range of professional development services intended to help graduates secure a job with their skills. Some certificates provide 1-on-1 mentoring, access to networking events, resume critiques, LinkedIn profile guidance, or professional portfolio feedback.