Entering the data analytics field offers secure job opportunities and above-average salaries, with professionals often earning six figures. In addition to entry-level positions, many companies hire senior professionals with management and leadership skills to help lead data and information technology teams.

Let’s dive into the lucrative career of Data Analytics.

What is Data Analytics?

Data analytics combines mathematics and computer science, creating many opportunities for professionals to enter this field.

What courses do you need to take if you want to pursue a career in Data Analytics?

  • Intro to Data Analytics: In this Excel, SQL, Power BI, and Python course, you’ll learn the necessary skills to become a junior data analyst, a job slated to grow 25% between 2019-2029 (BLS).

Data is considered the new gold and the basis of sound business decisions in every industry.

This course teaches you how to use data to make informed decisions. You’ll use industry-standard tools such as Excel and PowerBI to analyze real-world data sets to create dashboards and visualizations to present your findings. The course will also cover:

  • How to acquire data from multiple sources
  • Data visualization
  • An understanding of data and its quality
  • Using Excel, PowerBI, and SQL to collect, sort, and analyze large data sets
  • How to present data-driven insights with dashboards and graphs
  • Professional development

  • Advance Data Analytics – In this Data Analytics, Python, Machine Learning, Predictive Analytics, Prescriptive Analytics course, you will dive deeply into how to use data to drive robust and informed decisions. Data is considered new gold, and data scientists are the new gold miners. You will learn how to acquire data from various sources, visualize data in a meaningful way, and optimize decisions making tell an impactful story.

This course will deeply explore using data to drive effective, informed decisions. You will learn how to:

  • Acquire data from various sources
  • Visualize data in a meaningful way
  • Machine Learning
  • Do exploratory analysis to understand data and its quality
  • Perform classification of data
  • Regression and Statistics
  • Python for Data Analytics
  • Predict/forecast what might happen in the future
  • Optimize decision making
  • Tell an impactful story

Data Analytics Career Paths and their Salaries

Data Analyst – $70,060 /year – Data analysts build systems to collect large amounts of data. They then clean and organize the raw data according to the necessary data points and interpret them to derive relevant conclusions.

Data Scientist – $119,563 /year – The roles of a data scientist are similar to those of a data analyst in that they use their understanding of data analysis, statistics, and programming to process big data and turn it into actionable insights. Unlike data analysts, these professionals go the extra mile to develop solutions to business challenges. In addition, they create new questions for data analysts to find answers to.

Machine Learning Engineer – $142,988 /year – Machine learning engineers have advanced knowledge of artificial intelligence. They develop independent software to help automate predictive models based on significant data results.

Data Architect – $136,106 /year – Data Architect collects and maintains industry data, creating secure databases based on client needs and coding requirements. After designing the initial database, data engineers manage, organize, and draw conclusions from their findings.

Business Intelligence Analyst – $86,220 /year – Also known as business intelligence managers, these professionals oversee data collection and analysis activities for the companies that hire them. In addition to identifying key data points, they also establish communications between the IT staff they oversee and senior management to ensure needs are understood and met.

Why Pursue a Career in Data Analytics?

For people who enjoy working in mathematics, computer science, artificial intelligence, and database management, a career in data analytics makes sense. These jobs also attract people who want to earn above-average salaries and choose between different industries and clients.

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