Turn complex data into stories through hands-on lessons in Excel, SQL, and Tableau data analytics.
Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to clean and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.
Learn to extract information from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You'll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL.
Become proficient in Microsoft Excel and go from beginner to pro with our hands-on Excel Bootcamp. Learn functions, formulas, Pivot Tables, macros, and time-saving techniques to conquer all the key skills needed to excel in Excel.
Learn how to use Tableau, a powerful data visualization tool, to create interactive and aesthetically pleasing charts, graphs, and maps. This course will teach you how to connect to datasets, analyze and structure data, customize visualizations, and publish your work.
Learn how to use Power BI, a powerful data visualization tool, to create interactive and aesthetically pleasing charts, graphs, and maps. Learn how to connect to datasets, analyze and structure data, customize visualizations, and publish reports.
Learn the fundamentals of data analytics, including descriptive and inferential statistics, and how different industries and organizations use data for forecasting and decision-making. Explore statistical analysis and modeling, including statistical algorithms, theorems, and models.
Learn the fundamentals of machine learning, including regression analysis and classification algorithms, in this practical, hands-on course. Gain the skills needed to solve real-world problems using machine learning, with a focus on Python programming and data science libraries.
Automate and enhance the data analysis process with artificial intelligence (AI). In this course, you'll learn how to utilize AI tools to collect, preprocess, analyze, visualize, and interpret data without the need for extensive coding knowledge.
Learn to gather, manipulate, and analyze real-life data in this course, where you'll gain hands-on experience with Python's NumPy and Pandas libraries. Develop your data visualization skills using Matplotlib, Seaborn, Plotly, and Dash Enterprise, and complete real-life projects that can be deployed online.
Learn the essential skills needed to become a Data Analyst or Business Analyst, including data analysis, data visualization, and statistical analysis. Gain practical experience through real-world projects and prepare for a successful career in the field of data analytics.
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
Learn Tableau for data visualization and become a certified Tableau Desktop Specialist in this hands-on certification course.
Learn to extract information from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You'll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL.
Learn Power BI for data analysis & visualization and become a certified Power BI Data Analyst Associate in this hands-on certification course.
Boost your resume with a Microsoft Excel Certification. Our program offers three courses, private training, the Specialist Exam fee with free retake, lifetime access to Excel video courses, and free exam proctoring.
Data analytics is the process of analyzing raw data to find trends and answer questions. Applicable in any industry, this process includes extensive sets of diverse data—structured, unstructured, and semi-structured—that are continuously generated at high speed and in high volumes.
Big data is typically measured in terabytes or petabytes, with one petabyte equal to 1,000,000 gigabytes. One petabyte is the equivalent of 250,000 films, and the large datasets used in data analytics measure anywhere from hundreds of petabytes to millions. (That’s a lot of data!)
A successful data analytics professional can help answer business questions related to historical trends, future predictions, and decision-making. Machine learning tools, massive datasets, and more affordable computing power have made these techniques applicable in many industries, helping businesses draw meaningful conclusions from complex and varied data sources.
If you speak with a Data Scientist or analyst, they’ll tell you that it’s more than just a potential profession. Data analytics is a hobby, a passion, one that can be applied in all areas of life. Noticing issues in your neighborhood? You could use urban data flows to predict and prevent infrastructural issues like potholes through a complex analysis of factors like traffic volume, pavement age, weather, and traffic accidents. Whether you’re on your local HOA board or presenting to your city council, your insights can help better your community.
Or, you could use predictive analysis to gather information on various sports-related topics, allowing you to make strategic choices in your fantasy leagues based on current team and player strengths and weaknesses.
Data analytics is, at its base, the combination of noticing patterns and a healthy amount of math and statistics. These things exist in everything around you, so data analytics can apply to almost anything you can think of.
Data analytics courses can teach you about the data analytics process (including collecting, wrangling, mining, and visualizing data), different data roles, and data structures. Basic math will be covered as well, and, for technical skills, you can expect to study programming languages like Python, database tools like Excel, and data visualization tools like Tableau. By the end of a data analytics course, you should be competent and confident enough to begin or expand a career in data science and analytics.
Typically, the data analytics process is divided into six sequential parts:
A data type is the most basic and the most common classification of data, one where information is transmitted between the programmer and the compiler. The programmer informs the compiler about what type of data is to be stored and also tells it how much space it requires in the memory. A few basic examples are int and string, essentially any variable used in the code.
In contrast, a data structure is a collection of different forms and different types of data that has a set of specific operations that can be performed. A collection of data types, data structures are a way of organizing the items in terms of memory, and also a way to access each item through some defined logic. Examples of data structures are stacks, queues, linked lists, and binary trees.
The math requirements for a Data Analyst vary, but they typically include probability and statistics, calculus, and linear algebra. The foundation for optimization algorithms and deep learning techniques, calculus helps Data Scientists solve optimization problems, like finding the minimum or maximum of a function. Probability is critical for hypothesis testing and distributions like the Gaussian distribution, while statistical methods are used to analyze large datasets and interpret the results. Finally, linear algebra helps Data Scientists understand algorithms. While you don’t need to have complete mastery of each of these, it is helpful to have some knowledge of these specific math skills to succeed at data analytics.
Programming is essential for Data Analysts to manipulate, clean, and analyze data efficiently. Through programming languages like Python or R, Analysts can clean and preprocess data, handle missing values, and format it for analysis. Proficiency in these languages can be highly beneficial in performing advanced analysis and building custom data models.
Data visualization is a key part of data analytics and business intelligence that uses visual elements to represent data more effectively. It translates complex, high-volume, or numerical data into a visual representation that is easier to process. Data visualization tools improve and automate the visual communication process for accuracy and detail. You’ll use tools like Tableau to create engaging and effective data visualizations that help communicate your findings to various stakeholders.
Given the field’s complexity and the diverse skill set required to excel, data analytics is considered somewhat challenging to learn, blending elements of statistics, mathematics, computer science, and specific industry knowledge. In data analytics, both the initial learning curve and the requirement for continuous learning are substantial, largely because of the breadth of the field and the continual advancement of technology. While data analytics comes with its challenges, it is ultimately a field that anyone can master. With the right amount of passion, dedication, and time, anyone can become an expert in data analytics.
The answer to this question may vary, depending on your current skill set. If you don’t have previous experience with programming or a background in mathematics, you may find mastery of these two subjects particularly challenging. Additionally, understanding the data often requires documenting data assets by keeping track of information such as every definition of columns in a data warehouse’s tables. Some parts of data analytics, like understanding data, may seem repetitive or time-consuming, but usually, there are tools to help streamline these processes.
Data analytics is a broad field; the time it takes to learn depends on several factors. You can master the basics of data analytics in less than a year, but your level of expertise will include various skills and practice in a particular role. You shouldn’t expect to become an advanced data pro in a matter of months.
The time required also depends on your existing knowledge and how much time you can dedicate each week. With full-time dedication (30-40 hours per week), you can become proficient in around three months, while part-time learners (15-20 hours per week) might take six months or more.
One factor to consider is the type of training you choose. Self-guided data analytics education can take much longer than a targeted bootcamp or certificate, so choosing the right course that fits your schedule is paramount to your success and efficiency.
There are several factors to consider when answering this question. First, you’ll want to consider what learning environment is best suited for you. Do you thrive in a collaborative environment where you can interact with your peers and receive in-the-moment feedback from your instructor? Or, do you prefer a more solitary learning environment, perhaps one where you can learn at your own speed?
You’ll also want to consider how much time you can dedicate to your education and what level of flexibility your schedule requires. Are you looking to immerse yourself in an intensive program? Do you work full-time and need your classes to be scheduled for evening and weekend hours?
In-person courses offer face-to-face interaction with both your fellow students and your expert instructor. This collaborative environment is available for both full-time and part-time classes and provides structure and accountability, two things that can help you succeed. Online classes may lack this in-person interaction, but they make up for it with increased flexibility. Live online classes still offer instant feedback from your instructor and interactions with other students, while on-demand virtual courses allow for the most flexibility since you can decide where and when you learn.
There are several other skills that you can start working on while studying data analytics. While you’ll most likely have the experience needed in mathematics and statistics, it can’t hurt to brush up on those two subjects. Additionally, programming languages like Python, R, Java, C, or Perl will be very useful.
Hadoop is the most popular Big Data framework. Most professional arenas will expect (or hope) that you have experience in Hadoop, so it can’t hurt to tackle it alongside data analytics. Likewise, SQL is the most common way of getting information from a database and updating it, so if you can master SQL as well, you’ll be a step ahead of your career competition.
Orlando’s various thriving industries and ever-growing economy make it the perfect place to study and work in data analytics. Below are some of the top industries in the region, each of which will utilize data analytics experts in a variety of ways. Check out these industry options to get one step closer to your dream career.
Centrally located in Florida, Orlando is one of the world’s few quinti-modal transportation centers, making transportation easily accessible by land, air, sea, rail, and even space, making it an ideal location for the advanced manufacturing industry. Over 2,400 advanced manufacturing companies, 115,000 manufacturing employees, and 6,000 annual graduates in related programs are all proof of the thriving manufacturing sector in the city.
Seven of the largest industry aerospace and defense firms on the Fortune 500 list all have operations in or near Orlando, including some of Florida’s biggest aerospace manufacturing operations. Over 76,000 tech workers call the city home, as does the nation’s top aerospace and defense workforce supplier, the University of Central Florida. So it comes as no surprise that there are more than $6 billion worth of annual simulation-related contracts in the region.
Orlando is also a creative hub with a combination of industry and education contributing to the tech economy that supports not only the region’s massive theme park and attractions industry, but the expanding footprints of many other major corporations, including Lockheed Martin, Darden Restaurants, Siemens, and more. The city even has a 68-acre creative village that supports a high-tech cluster in downtown Orlando. Digital media co-exists with almost every other major industry in the region, employing countless Photoshop professionals to help them communicate their brand identity and engage with customers through the medium of image.
Orlando’s life sciences industry is home to groundbreaking medical advances, thanks in part to large health systems like AdventHealth and Orlando Health. More than 195,000 professionals are employed in the life sciences and healthcare sector, and major players like CVS and Walgreens call the region home.
There are several exciting career options available for both those who are just getting started in the field of data analytics and those looking for advancement. Each position will have a unique specialty or focus, so you’ll want to have a clear understanding of how you’d like to apply your data skills professionally.
Financial Analysts guide individual stakeholders, businesses, and companies on how best to invest money and resources to gain the maximum profit. They will analyze multiple factors like business environments, market trends, financial status of companies, expected outcomes of operations, and past financial data to make the most informed and calculated decision. In Orlando, you can make $70,000 as a Financial Analyst, with the potential to earn much more as you gain experience.
Database Developers study database processes with the goal of updating them, improving their efficiency, and getting rid of inefficient coding. They keep track of how existing databases are performing, use code and web architecture to create data systems, analyze and maintain existing databases, and implement new user features. You can expect to make around $95,000 as a Database Developer, Administrator, or Architect in Orlando.
Do you also have an interest in weather systems? Weather Analysts study atmospheric occurrences and analyze data pertaining to meteorological events to provide forecasts and reports. It’s important they have a sound understanding of math and statistics, and are also familiar with meteorology. Meteorologists and Atmospheric Scientists make $81,268 to $130,605 per year in Orlando.
Are you a marketing or digital media wiz? You could become a Marketing Analyst and spend your time researching and optimizing campaigns. Marketing Analysts may be required to use tools like Moz or Ahrefs, depending on their employer. A Marketing Analyst must also have a basic understanding of data analysis and using Google Analytics. You can earn $60,000-$82,000 per year as a Marketing Analyst in Orlando.
Offered by Noble Desktop, this in-depth course can take anywhere from four to 20 weeks to complete. You’ll learn all the skills needed to become a professional Data Scientist, like how to manipulate databases and perform data analysis, master the fundamentals of Python programming, and use its main data science libraries to analyze data. You’ll also try your hand at creating machine learning models, making dashboards and visualizations, and deploying your projects online with GitHub.
Held live online, this course includes access to 1:1 mentoring, a free retake within one year, and a verified digital certificate upon completion. Small class sizes and live project-based training with industry experts help ensure you gain all the knowledge and experience needed to land your dream Data Scientist job.
This project-based course from Noble Desktop teaches you to gather, wrangle, analyze, and visualize data using various tools and technologies to help businesses in decision-making and strategy. You’ll work on multiple real-world projects to explore both predictive and prescriptive analytics and gain practical experience. Plus, you have access to 1:1 mentoring, a free retake, and setup assistance when you enroll in this course. Payment plans are available to make this certification more accessible.
If you’re looking to offer in-person or online training to your office or team, Noble Desktop can help. It offers a variety of corporate training programs, including in data analytics. You can order vouchers in bulk at a discount, choose which courses are available to employees, and even let your employees choose their own schedule. Plus, you can choose to have your training hosted at a location of your choosing, live online, or at Noble Desktop’s Manhattan office.
With a top-notch customizable curriculum and instructors who are experts in their industries, Noble Desktop’s corporate training is designed to cater to your business or organization’s needs. For more information or to schedule a free consultation, you can reach out to Noble Desktop at corporate@nobledesktop.com.
A city bursting with innovation and energy, Orlando is becoming one of Florida’s most exciting places to build a career. Long recognized for its world-class tourism and entertainment industries, the city is now gaining a lot of traction in fields related to tech, data, business, and design. Industries like tech, entertainment, healthcare, and aerospace reign supreme, which means there are ample job and professional development opportunities. Start-ups, research institutes, and global corporations alike call Orlando home, creating countless opportunities for professionals eager to expand their skills and make a real impact. Data analytics is one field that's really taking off, especially in Orlando with such a strong mix of tech, healthcare, and tourism companies. Knowing how to collection, organize, and analyze datasets to uncover patterns and make better decisions is an invaluable skill. Through Noble Desktop’s training from experienced instructors, you’ll be able to access the most updated industry-standard information that will help you get right to work in the field. This fast-growing region is worth exploring, and the new skills that you can learn in the region will help you get your foot in the door sooner and are beyond worthwhile.
Dr. Cheryl McCloud brings over 35 years of experience in global supply chain management, with expertise in transportation, inventory systems, trade compliance, and regulatory affairs. She’s earned a Bachelor’s in International Studies from Old Dominion University, along with an MBA in Project Management from DeVry University and a DBA in Global Supply Chain Management from Walden University. Throughout her career, Dr. McCloud has owned a global transportation business, served as a federal government contractor, and provided trade compliance oversight for various shippers. She currently teaches project management courses and, as a licensed U.S. Customs Broker, she also holds certifications in project management and federal maritime law.