Explore data analytics through Excel, SQL, and Tableau programs. You’ll learn to identify trends and translate data into clear visual stories.
Master the industry-standard tools and programming languages used by Data Analysts, including Excel, SQL, and Tableau, in this comprehensive classroom training program. Gain hands-on experience working on real-world projects and learn to organize, analyze, summarize, and visualize data to present actionable insights.
Improve your data analysis skills with our Excel for Data Analytics class. Learn essential functions, formulas, and advanced techniques like Pivot Tables and VLOOKUP. Gain hands-on experience and optimize your workflow for efficient data analysis.
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.
Gain practical SQL skills in this hands-on certification program, where you’ll learn to write queries, manage data, and analyze results using Microsoft SQL Server.
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 to clean, organize, and reshape data quickly with Power Query, a powerful tool built into Excel and Power BI. This hands-on course will teach you how to streamline your data preparation process for analysis and reporting.
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 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.
Gain practical skills in analyzing datasets, building predictive models, and creating AI-powered applications using Python and industry-leading tools.
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.
Prepare for the Microsoft Excel exam and become an Excel expert with our certification program. Learn formulas, functions, Pivot Tables, charts, and more through group classes, private training, and an exam with a free retake.
Data analytics refers to the science of analyzing and interpreting datasets to provide insights that can affect business decisions. Though often conflated with data science, the role of a Data Analyst differs significantly from that of a Data Scientist in significant ways. Data Scientists typically extract and prepare data, whereas analysis requires a data professional to provide conclusions.
Analytics professionals hold a variety of disparate titles, including:
However, Data Analyst job postings often include additional information in the title, like:
Finally, varying data analytics roles specify a level in a job listing such as:
When searching for Data Analyst roles, be prepared to sort through numerous listings. These may not include the word data in the title, though the job description typically references multiple data-centered skills and tools. Read on to learn more about this fascinating field.
The applications of data analytics training depend on a user’s skills, knowledge, career goals, and other factors. Some students learn data analytics for business or finance roles, while others pursue careers in data science. To launch a career as a Data Analyst or Data Scientist, you must learn computer programming languages like Python or R, platforms like Apache Spark, and tools like Tableau or Power BI. Consider the following tasks you can perform using data analytics:
The data analytics field is so broad that multiple factors affect what you will learn in a course. For example, a data analytics novice might take a short introduction to principles and skills. However, another might enroll in an immersive bootcamp or certificate program. The length and cost of the course, whether it is available full-time, part-time, or both, and the student's goals are all factors. Many data analytics classes cover Python, Structured Query Language (SQL), and Tableau. Check out how these tools can apply to data analytics:
While you might enter training with Excel experience, you’ll need to learn how it applies to data analytics. Long an industry-standard for data management and visualization, many companies still use it for their analysis. You might move on to newer tools like Tableau or Power BI, but Excel is an excellent place to start, and it is a primary subject in many data analytics courses.
The utilitarian Python programming language is essential to Data Analysts, Data Scientists, Machine Learning Engineers, and many other data professionals. Most data analytics courses cover beginner-level, intermediate, or advanced Python for data science, automation, machine learning, or all three. Top Python libraries for data analytics include BeautifulSoup, Matplotlib, NumPy, and Pandas, to name a few.
Many different types of tech pros use Structured Query Language (SQL) to store, query, and process information in relational databases. SQL is a staple in a data science and analytics class, whether it features SQL Server, MySQL, PostgreSQL, or another option. Data pros who use SQL the most include:
Visualization is another essential skill for Data Analysts. Many learn platforms beyond Excel. The top business intelligence tools for data visualization include Microsoft Power BI and Tableau, and most data analytics courses include training in one or the other. You can read online articles comparing and contrasting the two, but chances are that your first data analytics job will require at least one of them.
Although most people new to data analysis have some math skills from their schooling, only some have a deep background in probability and statistics. This aspect of mathematics is essential to data analysis. However, it might not feature in a data analytics class. Statistics help Data Analysts and other data pros comprehend complex datasets, and students with a statistics background may have an advantage when training.
As in other aspects of data analytics, the difficulty of learning depends on multiple factors. For example, students who attend workshops on Python programming, SQL, or even Microsoft Excel often come to data analytics training with relevant skills. Additionally, the data analytics field itself is complex and multifaceted. Becoming familiar with a skill is not the same as being an expert, and data analytics training typically covers multiple skills and tools. Anyone planning to be a Data Analyst, Business Analyst, or Financial Analyst should consider enrolling in a bootcamp or certificate program that features analytics or includes it within a broader data science curriculum.
Most data analytics students report that the most challenging aspect of learning is integrating many disparate tools and skills. Python or R, MySQL or SQL Server, and Power BI or Tableau can all fit comfortably within a data analytics curriculum. On the other hand, some learners find the challenge of integration an acceptable one, struggling only with one skill or platform. Because immersive bootcamps typically build training modules on previous lessons, this strategic approach can make learning data analytics seamless.
The time it takes to get comfortable experimenting with data analytics will differ from how long it will take to learn this field for a career. If someone decides to know SQL to handle large datasets, they can learn fundamentals in a few days or hours. However, training to be a Data Analyst can take months or even years. Consider enrolling in an immersive bootcamp or certificate program to qualify for an entry-level data analytics role.
While not entirely controversial, not all experts agree about whether in-person data analytics is essential. Many bootcamps and certificate programs are available live online, and some participants prefer the convenience of a virtual training program.
Before choosing data analytics training, consider the three most popular types of courses: in-person, live online, or asynchronous (on-demand).
Self-taught Data Analysts are increasingly rare in the modern age.
Although many course providers host free webinars and blog posts with information about data analytics, they hardly substitute for professional training and skill development. If you are new to data analytics, check out the Noble Desktop YouTube channel and Learning Resources page. You can find solid introductory information, including video seminars about SQL and data science.
When you are ready to learn more, a bootcamp or data-centered certificate program will prepare you for a successful career.
What you learn alongside data analytics depends on two main factors: your current knowledge and skill set and how you plan to use your data analytics skills.
Several additional platforms and programs may be essential for data analytics in a general business setting. However, a financial role for data analytics can require multiple other tools. Consider the following:
Data analytics skills are essential to nearly every industry, from governmental agencies to multinational corporations. In the DC area, several top industries require data analytics professionals with diverse knowledge and skill sets. Consider the following sectors if you plan to launch a new data-centered career:
While it dipped during the COVID pandemic, the hospitality and tourism industry in the Washington-Arlington-Alexandria metropolitan statistical area (MSA) is nearly back to pre-pandemic levels. Data analytics is essential to tourism, especially in an area like the nation's capital, which hosts over 25 million visitors annually.
Media and communications is another sector driving growth and innovation in the DC metro area. This sector accounts for around $10 billion in wages and salaries, a substantial figure. Media and communications firms rely on data analytics to provide actionable insights in a concise timeframe. While media organizations in DC include the Washington Post, NPR, and National Geographic, the federal government also supports multiple international media outlets.
The professional services sector includes numerous companies and positions, including advertising, engineering, law, private medical practices, and BFSI (banking, financial services, and insurance. The role of data analytics in these organizations varies from risk management to marketing to predictive analytics. The Washington-Arlington-Alexandria MSA boasts a growing professional services sector, representing around half a million employees.
Topping most lists for DC industries, the government adds the most value to DC's gross domestic product (GDP). Around one-fourth of area residents are federal government employees. Data analytics in government ranges from analyzing government contract spending patterns to obtaining data for strategic planning.
Besides the obvious choice of Data Analyst, a tech pro in DC with data analytics training can work in multiple roles in nearly every industry. Consider the following top options:
Many Data Scientists begin their careers as Data Analysts. Among the most respected data science professionals, Data Scientists command impressive salaries. In Washington, DC, the estimated total pay for a Data Scientist is around $122,000 annually.
Business Intelligence Analysts work with multiple tech tools, from SQL to Tableau or Power BI. DC-area BI Analysts can anticipate earning an average annual salary of around $108,000, not including bonuses or other compensation.
Financial Analysts in Washington, DC, work in numerous industries, from the public sector to private aerospace and defense companies. Their average base salary here is about 90,000 annually, comparable to national averages.
Noble Desktop offers multiple data analytics bootcamps and certificate programs appropriate for Data Analysts, Financial Analysts, or Business Analysts. Check out the ||CPN395||, Data Science & AI Certificate, Business Analyst Certificate, or ||CPN509|| to learn more.
General Assembly offers Washington, DC residents a 24-week Data Analytics Boot Camp. Topics include Tableau, SQL, and Python, to name a few. The course is also available live online.
Ledet Training provides data analytics training, including their five-day ||CPN848||. This course combines beginner and intermediate-level training for an intensive, high-level program.
New Horizons offers multiple data analytics courses. Their beginner-level SQL program is called SQL Querying Fundamentals – Part 1. The one-day workshop covers queries, searches, functions, and other essential foundational subjects.
Flatiron School provides data analytics training, including a three-month Data Science Bootcamp. Attendees learn Python, Tableau, and Jupyter Notebook in this portfolio-based immersive.
Students new to data analytics can learn SQL from Softek Services, Inc. Their Introduction to SQL Querying covers query fundamentals in a one-day workshop. Softek offers live in-person or live online training.
Would your team benefit from data analytics training? Noble Desktop offers corporate and onsite training you can take at your location or live online from anywhere. Topics include Excel, Python, Tableau, SQL, and Power BI, to name a few.
If you want more flexibility in scheduling, Noble Desktop can provide vouchers for bulk purchases of open-enrollment courses. Employers get discounts when purchasing in bulk. Contact Noble Desktop for more information and a free consultation.