Develop your data analytics abilities using Excel, SQL, and Tableau to turn raw information into actionable, well-structured conclusions.
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 identify 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 equivalent to 250,000 films, and the large datasets used in data analytics measure anywhere from hundreds to thousands of petabytes. (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 across 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 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. 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.
The good news is that, no matter which option you choose, you can obtain a quality education with a top-notch curriculum and expert instructors.
Technically, it is possible to learn data analytics for free online. YouTube videos, blogs, and free short workshops can all be a great way to learn the basics without purchasing any educational content. (Don’t forget to watch the most recent uploads so you’re learning the latest trends and techniques.)
But, for the more advanced skills, an in-depth training course is going to be your best bet. These courses have a curriculum developed and taught by experts with the chance to receive feedback or troubleshoot any issues with your instructor or a support team. Formal training can also provide the structure and accountability that some students need to stay focused, creating an environment where you’re more likely to succeed. So, if you’re looking to master more than just the basics, a formal workshop or class is a better choice than free online resources.
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.
Portland is known for its incredible mountain views, lush landscapes, and quirky culture, so it should come as no surprise that the city has several emerging and thriving industries. The top ones are outlined below, each of which could have opportunities for experts in data analytics. Keep reading to learn more.
Bioscience is one of these sectors, with big hitters like Genentech, Thermo Fisher Scientific, Micro Systems Engineering Acumed, and Absci calling the region home. (Oregon and Washington combined raised a record $324 million across 37 deals in 2021.) Specialized university labs in the region include Oregon Health & Science University’s (OHSU) National Primate Research Center, UO’s Genomics & Cell Characterization Core Facility, OHSU’s biolibrary of tissues and blood, and OHSU’s Massively Parallel Sequencing Shared Resource. Access to hands-on education facilities like these boosts the number of STEM occupations, which made up 27% of the region’s jobs in 2022.
The city’s climate tech industry is also booming, thanks to Portland’s passion for the outdoors. Employing over 14,400 across 843 enterprises, Portland has led the nation in climate tech for decades. In fact, six related companies raised nearly $550 million in 2021, proving the industry's lasting presence in the region. Local organizations like CleanTech Alliance, Cascadia CleanTech Accelerator, and VirtueLab offer funding, mentorship, connections, and entrepreneurial support to local climate tech companies.
Centered around innovation, creativity, and inclusion, design and media generate $4.2 billion in economic output each year. Employing 33,000 professionals, this sector’s workforce is 48 percent larger than the U.S. average. World-class engineering, advertising, architecture, and production brands call Portland home, solidifying the city as a hotbed for creative endeavors.
Greater Portland is the epicenter for apparel & outdoor gear companies for both the U.S. and the world. Industry leaders, including Nike, Columbia Sportswear and Sorel, have chosen to headquarter in Portland for the rich ecosystem of creative minds and innovative outerwear companies. The incredible access to outdoor activities doesn’t hurt, either. Additionally, the University of Oregon created the first master’s degree in Sports Product Management, a pioneering program that underscores the region's commitment to excellence and innovation in this field, helping to supply the industry with fresh, new talent.
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 Portland, you can make $101,000 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 and 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 $125,000 as a Database Developer, Administrator, or Architect in Portland.
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 $66,000 to $102,000 per year in Portland, so you can expect salaries around that range.
Are you a marketing or digital media wiz? You could become a Marketing Analyst and spend your time researching and optimizing campaigns and they 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 $93,000 per year as a Marketing Analyst in Portland.
General Assembly’s bootcamp offers hands-on experience using industry-standard tools such as SQL, Excel, Tableau, Power BI, and Python. Learn how to solve problems like an analyst and effectively communicate your findings. Gain the skills needed to make ethical, data-driven decisions and become proficient in tools highly sought after by employers in the data analytics field. This course is offered in-person at select locations in Orlando, or live online for more flexibility.
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. They offer 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.