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.
More and more decisions are made based on data, but that data is simply a collection of meaningless numbers until it is analyzed. Data analytics is the practice of analyzing raw, unprocessed data to extract relevant information, trends, and insights. This process includes collecting data, organizing it, and storing it, then performing statistical analysis on the data.
Data analytics is the basis for much of the problem-solving, business processing, decision-making, and predictions that can inform what a company’s next steps should be. This process relies on disciplines like mathematics, statistics, and computer programming.
Big data is not a new concept. Before the 1950s, companies and organizations manually examined numbers on a spreadsheet to identify trends and key insights. As computers became available, those calculations could be made much more quickly, and the field of data analytics evolved, gaining speed and efficiency as hardware and software improved. The faster an organization could extract and use information from data, the more of an edge they would have over competitors. Today, Data Analysts use a variety of techniques and methods to collect and analyze data depending on the goal of analysis and the industry in which the insights will be applied.
Data Analysts can work in a wide variety of environments including finance, business, retail, medicine, education, or for a government entity. Any industry that collects data to make predictions, solve problems, and plan for the future needs Data Analysts.
If you plan to change to a career as a Data Analyst, signing up for a class or a certification course will give you the skills to get a job. Here are some of the skills you will learn in a data analytics class.
How data is stored and organized affects how it can be accessed and used. A class will cover some version of SQL, a relational database management system used to organize large datasets.
Another skill covered in a data analytics course is data mining, which involves uncovering relationships and patterns in datasets. Data mining relies on statistics, AI, and machine learning. Some common data mining tools include Oracle, KNIME, and Rapid Miner.
Data analytics is based in large part on statistics and mathematics. R is a popular computer coding language for statistical analysis, as is MATLAB. Data Analysts also use Excel spreadsheets to keep track of results.
Data analytics can be powerful but only if people can understand the results. Data visualization takes the data and creates charts, tables, and graphs to tell the story of the data and help an audience see the trends and patterns it presents. Tableau and Microsoft Power BI are important data visualization tools.
Business analytics is a specialization of data analytics focusing on methods used in gathering business intelligence. In addition to visualization tools, Business Intelligence Analysts use tools like Python and Jupyter Notebook for documenting and sharing outcomes.
Learning tech skills tends to be challenging and requires time and commitment. Working with big data is easier if you have a background in statistics, mathematics, or coding. If you don't have a technical background, it is a good idea to take some of those courses before learning data analytics. Students often feel overwhelmed when trying to learn data analytics, and this is where signing up for a class can make the process easier.
One of the most challenging parts of learning data analytics is identifying whether or not the data is useful. Learning to clean data properly is an important skill for producing quality data analysis.
Data analytics is not a single skill but rather a process that requires knowledge of several related fields such as statistics, data visualization, computer programming, and spreadsheets. Most people can learn the core concepts of data analytics in about three months. However, this depends on various factors, like your background in math and statistics, the method of learning you select, and your experience working with data. Acquiring more advanced data analytics skills can take much longer than three months. Some estimate it can take between three and four years to achieve a mastery of data analytics.
When you decide to take a data analytics class, you will need to choose between in-person and online classes. Most people are more familiar with in-person instruction with an instructor in a classroom and students at desks around the room. You can ask questions, get help, and talk to other students. In-person classes run according to a set schedule and you have to commute to the class location.
The other option is to sign up for an online class. Live online classes run at the same time as an in-person class. There is a live remote instructor in a classroom with some students, while others attend over a video conferencing platform like Zoom. You can interact with the instructor and other students to ask questions, get help, or network together. You can attend class from anywhere with a stable internet connection, like your home, office, or favorite quiet cafe.
Data analytics is a multidisciplinary field and it would be very difficult to learn it completely on your own. However, there are many introductory seminars and tutorials on YouTube to get you started. Sessions like Noble Desktop's Intro to SQL, Intro to Python Fundamentals, and Exchanging Excel for Python can help you decide if data analytics is for you.
Once you have started learning data analytics, there are other skills you can learn to support your goal. Data Analysts working with big data need to understand relational databases, and SQL is a good tool to know. Data visualizations made using programs like Tableau and Microsoft Power BI help you explain trends and patterns in the data to colleagues and clients. Learning how to write machine learning algorithms is also useful for working with large datasets.
It is difficult to find an industry that doesn't use data analytics these days, but there are some industries that hire more Data Analysts than others. These include finance, retail, healthcare, manufacturing, and government.
The banking and finance industry was one of the first to recognize the value of data for doing business. Some Miami financial companies include Securitize, Citadel Securities, Greenbox Capital, Nymbus, and Crypto.com.
Retail companies collect data to create a positive customer experience and healthy profit margins. Some retail companies found in Miami are Brilliant Earth, Chewy, Gopuff, AIR Communities, SellerX, and Intradeco Apparel.
The healthcare industry relies on data for recordkeeping, research, and revenue projections. Some healthcare companies based in Miami include CVS Health, Kaiser Permanente, DaVita, UnitedHealth Group, Labcorp, and HCA Healthcare.
Manufacturing companies generate a large amount of complex data surrounding raw materials, production, and distribution. Some of the top manufacturing companies in Miami are Ideal Unlimited, Sunco Plastics, Dynasty Apparel Corp., The Notch Project, and ARTCIFY.
People with analytics skills can choose between many different career paths. The U.S. Bureau of Labor Statistics lists data analytics jobs as the fastest growing professions over the next ten years at more than 35%. Some data analytics jobs with salaries are listed below.
Data Analysts collect, prepare, analyze, and interpret data for firms in several industries. The median yearly salary for a Data Analyst in the U.S. is around $76,000 and $74,000 in Miami.
Financial and Business Analysts work with banks, insurance companies, and investment firms and use data to help businesses plan for the future. Business Analysts earn about $84,000 a year in the U.S. and $75,000 in Miami.
Data Engineers create the infrastructure for data and format data into a useful system which Data Scientists use to analyze large amounts of data. Data Engineers can specialize in pipelines, databases or platforms, warehouses or infrastructure, or be generalists. Data Engineers in the U.S. earn around $125,000 a year and $130,000 in Miami.
A Database Administrator uses software to store and organize data and make sure the data is available only to authorized users. Some Database Administrators specialize in Systems or Applications while others work on all aspects of database administration. Database Administrators make about $80,000 annually in the U.S. and in Miami.
You have many choices for a data analytics course in Miami. Choose an introductory short course, a multi-day bootcamp, or a certificate course.
General Assembly offers a ||CPN398|| in-person. The course covers using industry-standard tools like SQL, Excel, Tableau, Power BI, and Python for data-driven decision making. Data Analytics Bootcamp is designed for individuals interested in learning the best practice of working with data and understanding the data analytics roadmap. Students will learn how data can help inform decision making, understand the data analytics workflow, and gain exposure to some of the most common tools used for data analysis.
Noble Desktop's ||CPN395|| is a live online course covering the skills you need, like data analytics fundamentals, data visualization, cleaning and manipulating data, and working with relational databases. One-on-one mentoring is included.
NYIM Training has a Data Analytics Technologies Bootcamp for participants who want to learn the key skills needed to succeed, including Excel, SQL, and Tableau. The program is open to beginners and has flexible scheduling options. Tuition includes hands-on training, a free retake, and training manuals for each course.
Data Analytics Technologies Bootcamp from NYC Career Centers is a course for students with little to no background in data analytics who want to learn how to use Microsoft Excel, SQL, and Tableau to summarize, display, and discover key insights hidden in datasets.
University of Miami Boot Camps provides a comprehensive foundation in Data Analytics Boot Camp. Students will learn statistics, Python, Tableau, SQL, and HTML and CSS. The course assignments help students put together a portfolio for job searches.
New Horizons offers several in-person classes on database management. SQL Querying Fundamentals Parts 1 and 2 take students from executing a simple query, performing a conditional search, working with functions, and organizing data. Students will also learn how to retrieve data from many different sources and export the results in a text or XML file. Part two covers advanced querying with subqueries and manipulating table data and table structure. The course also covers working with views, indexing data, and managing transactions.
Data Analysts study past data to gain insights that help inform future business decisions. In contrast, Data Scientists go deeper and use mathematics and statistics to build predictive models and algorithms. In Noble Desktop's ||CPN411||, you will learn a variety of critical skills to become a Data Scientist. You will learn Python coding, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.
If you are a business owner looking to retrain or upskill your employees in data analytics, Noble Desktop can meet your corporate training needs. You can schedule classes at your offices in a conference room with a live or remote instructor for the classes of your choice. Noble's catalog includes introductory and bootcamp courses in data analytics techniques, Excel, Python, SQL, and machine learning. Noble can also design courses to meet your company's specific needs.
Noble offers group class vouchers at a bulk discount. Employees can schedule individual classes according to their own schedules. Instructors are experienced industry professionals and attendees receive handouts, exam guides, and access to training videos to help them reinforce new skills. Find out how you can help your staff build their skills at corporate@nobledesktop.com.