Study data analytics using Excel, SQL, and Tableau. You’ll transform data into actionable insights through real-world business applications.
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 all about taking raw data that is seemingly meaningless and turning it into useful interpretations that can help improve customer relations, increase sales, and enhance business operations. It involves identifying trends and patterns to make better decisions. For example, you might analyze customer behavior to see why sales dropped. It could also be used to share more insights with the marketing team to determine how social media interactions could be improved. Ultimately, data analysis leads to better outcomes for businesses and is therefore one of the most useful behind-the-scenes aspects of a company.
Today, data analytics is often associated with databases, programming languages, and computers, but in truth, data analysis has a strong, lengthy history. It can technically be traced back to as early as the Stone Age, where simple forms of data collection such as notches on bone or drawings on the wall were performed to keep track of items. In the late 1800s, factories began keeping track of assembly line processes for efficiency. Although data analytics is incredibly necessary today, as well as highly automated, it can be used in virtually every industry for companies both big and small.
Data analytics training offers job opportunities in spaces you wouldn’t even believe—from healthcare and education to finance and even government. There’s no shortage of data analysis jobs since virtually any business or money-making entity relies on large amounts of data to understand the next step, optimize their operations, or market to consumers. With these skills, you can thrive virtually anywhere you desire, which is why so many opt for a data analysis education.
That being said, it’s no surprise that you’ll have the chance to complete numerous projects. Every day is different as a Data Analyst—some days, you’ll analyze recent financial data to provide the company with ways to budget more effectively in the next quarter. On other days, you will work on improving marketing techniques for the social media management team. The variety of work keeps things fresh and exciting.
Even if you don’t want to work as a professional Data Analyst, you could use these skills in your everyday life. For example, your analysis skills can help you track your finances more effectively. This means you’ll save money, learn where you need to cut back, and figure out the best way to approach each month. You could also put your skills to use in your latest fitness journey. This is especially true if you wear a Smartwatch that keeps track of your health metrics. You could collect, compare, and gain insights from your exercise routine and figure out how to improve your overall health. Data analysis is a great way to benefit your professional and personal life, so training is incredibly worthwhile.
Each data analytics class differs based on the subject matter or the level of depth. For instance, some will focus solely on the basics such as data cleansing and preprocessing as well as the relevant programming languages. Others will focus on data visualization tools, whereas some will dive deeper into how to use Microsoft Excel. Furthermore, some more challenging courses will discuss machine learning concepts. This all depends on the specific course, but you could expect any number of these subjects in a beginner, intermediate, or advanced-level course as well as a bootcamp or certificate course.
Data cleansing and preprocessing are essential steps in the data analysis process and will certainly be discussed at any level of a data analytics course. Think of this stage as similar to cleaning up a cluttered space—it involves removing duplicates, fixing errors, filling in missing spaces, and making sure everything is organized. This step is important because raw data can be messy and unorganized in addition to being inconsistent. If you skip this step, your data could end up inaccurate and therefore worthless.
The most commonly used programming languages for data analysis include Python, SQL, and R, so these will likely be discussed at length. They allow you to handle, analyze, and visualize large datasets with ease. Programming languages allow you to automate tasks and use their associated libraries and tools. For example, Python’s libraries, Pandas and NumPy, allow users to manipulate data with ease. R is most useful for statistical analysis. In essence, if you want to learn data analysis, programming languages are a nonnegotiable skill.
There are dozens of data analytics tools but one that reigns supreme is Excel. It’s a staple for data analysis because it’s simple and is great for smaller tasks. The tool has numerous functions like formulas, Pivot Tables, and charts so you can easily organize, find, and analyze data. Whether you’re working directly with data, generating reports, or running through basic statistics, Excel is versatile and necessary to master.
The best way to share your insights is through data visualization, so many data analytics courses will cover this topic. Tools like Tableau and Power BI are great for data visualization (in addition to Excel) and help you make it easier to spot trends, communicate your findings, and explain what’s going on to people who may not have the same data skills as you such as stakeholders or marketing teams. This makes it easier for everyone to get on the same page and act quickly to understand how business operations can improve.
While not every Data Analyst will need to study machine learning, some advanced courses may cover it to an extent. Understanding the basics can help you stand out among other analysis experts. Machine learning can provide algorithms that make it easier to identify patterns within larger datasets. At a minimum, it may be useful to learn supervised and unsupervised learning as well as how to train a model. With this, you can take your analytics skills to the next level and predict future trends quickly.
Learning data analytics can be somewhat tricky, particularly if you are starting your educational journey from the beginning. However, what’s difficult for one person may be relatively easy for another. If you’re new to the field and hoping to turn it into a career, some concepts may feel overwhelming, but they are not impossible to learn. With the right approach, you can learn the basics or the more advanced concepts. Having a background in a related skill such as mathematics or information technology may make the learning process easier too. Plus, if you’ve already learned how to use certain tools such as Excel, you’re already one step ahead.
Data analytics has some hurdles to overcome. The hardest parts can vary, but most agree that data cleansing and preparation, especially for large datasets, is particularly challenging. This is because it requires a lot of time and effort. Another challenge involves the mathematics and programming side of things such as while creating predictive models and machine learning models. This presents a relatively hefty learning curve if you're not already experienced. It also matters whether you’re naturally inclined to technology and analytical thinking, but despite all this, you can overcome these challenges while learning data analytics.
The time it takes to learn data analytics typically depends on a few key factors: your previous or relevant experience and the level of expertise you want to obtain. If you have some prior knowledge in adjacent skills, it may not take as long to learn data analytics. On the other hand, if you have little to no experience, it’s going to take additional time. Similarly, if you want to gain a basic understanding of data analytics skills, you can perhaps spend a few weeks to a few months perfecting tools like Excel, SQL, or Tableau. If you want to become a professional Data Analyst, you can expect to spend a few months to a year or more studying and mastering all the different tools, techniques, and terms associated with data analytics.
When deciding between in-person and online courses, you’ll have to consider things like your schedule, preferences, learning needs, and end goals. In-person learning offers a more traditional classroom experience, which can be great if you prefer direct interaction with the material, your classmates, and the instructor. In-person training provides hands-on practice and interaction, but the main thing to consider is your schedule. If you don’t have the time (or transportation) to make the commute, this may be less than ideal.
However, there’s an alternative to in-person training if you still want a structured, interactive learning experience without the commute. Live online classes allow you to attend classes from anywhere as long as you have a stable internet connection to avoid potential technical issues that could derail your learning experience. Even though it may feel a little less personal due to the virtual setting, you still gain ample feedback and assistance from the instructor.
If you need even more flexibility in your learning journey, you could consider asynchronous training. These are self-paced courses that allow you to learn whenever it suits your schedule. There’s no instructor, so you won’t have anyone to provide assistance or feedback, which is why it isn’t exactly a good option for students with little experience or those who want to work their way up to become Data Analyst professionals. Still, asynchronous classes can foster strong self-discipline and time management skills and may be good for current data analytics professionals who want to sharpen their skills or refresh their memories.
You can explore free online resources before enrolling in a data analytics course as a way to familiarize yourself with relevant terms, concepts, and tools. There are tons of resources out there, like tutorials on YouTube—such as Noble Desktop’s extensive group of playlists on Excel, Python, SQL, and general data science information. Moreover, it would be useful to explore training center websites for blogs and pre-recorded lectures such as those offered on Noble Desktop’s Free Seminar page. Otherwise, there are countless social media accounts that offer more insight into the data analytics field, and you can find other online groups such as discussion boards, chatrooms, and forums. Still, consider your end goal. If you want to become a professional, a free resource is only step one. You will need a more comprehensive way of learning that fosters professional development.
Exploring data analytics is just one useful skill among many others. For instance, you may want to learn more about artificial intelligence (AI) and machine learning. These skills supplement your data analytics training and make it easier to automate tasks and make data-driven decisions. Ultimately, with the combination of these skills, you can handle more complex datasets.
Moreover, you may want to learn business intelligence (BI) tools like Power BI. This is especially true if you’re leaning more toward business analytics. Power BI lets you create clear, visually attractive data visualizations that convey complex information with simplicity. Plus, since Power BI comes from Microsoft, it can integrate seamlessly with Excel, a commonly used data analytics tool.
Data analytics is used in virtually every industry and at any company where data is essential for success and development. It helps companies make better decisions and optimize operations, whether it’s healthcare and technology or education and finance. In this section, you can learn more about the most successful Baltimore industries and decide which one may be right for you based on your interests, preferences, and training.
One of the most successful industries in the country, let alone Baltimore, is healthcare. Baltimore has some of the nation’s best medical institutions such as Johns Hopkins University, where there are numerous career opportunities for medical professionals as well as those who work behind the scenes. The city is a hub for healthcare innovation, research, and services, with both private and public health organizations developing and using cutting-edge technologies to improve patient care and operational efficiency.
In healthcare, data analytics is used to improve patient outcomes and streamline workplace operations. This could mean tracking patient data and predicting their needs from the results. It could also consist of optimizing hospital workflows, allowing healthcare providers to move seamlessly from patient to patient, case to case. Furthermore, it assists with identifying trends in community health data so diseases and illnesses can be prevented. It’s used in preventative care, reducing remission rates, and reducing healthcare costs.
With an emerging tech space, Baltimore has major companies, small businesses, and startups that make up a good portion of the local economy. Its proximity to Washington, D.C., as well as the National Security Agency in Fort G. Meade, Maryland, also makes it a center for technological innovation, particularly for cybersecurity and software development. The city itself sees steady growth, and the tech industry shows no signs of slowing—making this a worthwhile city for aspiring tech professionals.
In the tech industry, data analytics is king. It’s used to improve everything from products and consumer experience to algorithms and workplace operations. For example, companies in Baltimore may use analytics to enhance their application’s performance. They may develop machine learning models that predict trends through automation. It’s also essential for cybersecurity such as detecting fraudulent activity and preventing security breaches. All in all, analytics helps tech companies stay afloat in a competitive market.
As home to Johns Hopkins University, one of the most well-known in the country, Baltimore has a thriving education industry rife with opportunity. The city also has public and charter schools that exceed expectations and frequently adopt new technology to improve educational outcomes for students and faculty alike. As education evolves and becomes more intertwined with tech, data has become a central force in supporting the education industry, which in turn helps support Baltimore’s local economy.
Because data analytics is increasingly necessary for educational institutions, Data Analysts can find work in universities, community colleges, public schools, and training centers. In Baltimore schools, for example, data can help administrators monitor and understand test scores so curricula can be updated in the following year. Moreover, analytics can be applied to optimize resource allocation and improve faculty efficiency. This enables educators to make better decisions that can directly impact student outcomes and success.
Baltimore’s finance industry is supported by several top-name banks, insurance companies, and financial services firms. The city has a strong FinTech presence as well since there’s a strong connection with the technology sector, so local startups emerge yearly. This industry depends heavily on data to help make informed decisions and keep the ball rolling with innovations, as well as maintain users’ sensitive financial information.
As a result, data analytics is virtually indispensable for financial companies. It’s useful for things like risk management, or otherwise determining which investments will have unfulfilling payoffs. In addition, many financial Data Analysts are tasked with detecting fraud and helping figure out how to prevent it. Data Analysts may collaborate with cybersecurity teams to prevent any data breaches and financial losses. By monitoring transactions for fraudulent activity, the financial institution can remain trustworthy in the consumer’s eyes.
If you’re in the Baltimore area and interested in taking your data analytics training into the professional world, you can work in numerous positions. Whether you want to become an analyst, engineer, or administrator, you can find lucrative and worthwhile careers across all kinds of industries. Read below to learn more about the different jobs a data analytics education can provide.
Data Analysts are tasked with sorting through data, cleansing and preprocessing it for clarity, and identifying patterns. These patterns provide insights that allow businesses, teams, or clients to make smarter decisions going forward with their projects or endeavors. According to Indeed, a Data Analyst in the Baltimore region earns an average of $79,000 each year, but this range can vary substantially. In fact, just 23 minutes outside of Baltimore in Owings Mills, the average is closer to $98,000 according to the reported salaries in that area.
A Machine Learning Engineer is someone who teaches computers to learn from data and make predictions on their own. They do this by building algorithms and models that make it easy to spot trends and make decisions. They combine the world of AI with data analytics and speed up the process. With appropriate training, a data analytics student can become a Machine Learning Engineer. In Baltimore, a Machine Learning Engineer earns between $94,000 and $144,000 each year, with an average of $117,000 per data compiled from Glassdoor. However, salary expectations vary based on whether you’re an entry-level or lead engineer.
Database Administrators keep databases organized and operating at maximum efficiency. They set up and maintain the data within a database, ensuring everything is where it is supposed to be. This makes the data analysis process much easier. Indeed shares that a Baltimore-based Database Administrator earns an average base salary of nearly $115,000. However, just outside of Baltimore, in Annapolis Junction, a Database Administrator can earn closer to $162,000, so there are likely varied salary expectations in this region for this role.
A Business Analyst helps make connections for non-data professionals. They help those who work solely on the business side of things figure out the meaning behind datasets and trends. In other words, they are problem-solvers for those who aren’t sure what to make of all the data they’ve collected. The expected pay range for a Business Analyst in Baltimore is roughly $70,000 to $112,000, according to Glassdoor. The average is closer to $89,000, but there are typically opportunities for additional pay and career development with time and experience.
If you want an in-depth look into data analytics, consider checking out Noble Desktop’s Data Analytics Certificate. This course gives you an in-depth look at Excel for data analytics, Tableau for data visualizations, and Python for data science, automation, machine learning, and data visualizations. Plus, you can take the Python for AI course at no additional cost with this certificate. You’ll get introductory topics such as how to interpret results from advanced data analysis techniques and practice extracting information with SQL from relational databases. Moreover, you’ll use Python and Tableau to visualize data so anyone can understand your findings. Beyond that, you’ll practice machine learning principles and develop a data analytics portfolio that shows potential employers all your skills. After 156 hours of total instruction, you’ll leave with a clear understanding of data analytics and earn a certificate of completion to serve as proof of your hard work.
Otherwise, you can explore the Data Science and AI Certificate. Over 114 hours of total instruction, you will practice using Python and SQL for automation, data visualization, and machine learning concepts. Specifically, you’ll analyze tabular data using NumPy and clean and balance data in Pandas. Moreover, you’ll practice data visualizations with Matplotlib. You’ll complete hands-on projects like animated bar chart races in Python or using user-defined functions in SQL to query databases. Plus, you can attend the Python for AI course for free once you enroll in this certificate program! All in all, this course gives you an all-encompassing look into the world of data analytics and leaves you with a developed portfolio, a certificate of completion, and a well-rounded data analytics education.
Noble Desktop also has a technology-specific course titled Data Analytics Technologies Bootcamp. This course lasts 51 hours and includes eight separate units that cover Excel, SQL, and Tableau. You’ll learn to use SQL to sort, filter, and summarize data and practice visualizing data in Excel with Pivot Tables, charts, and tables. Furthermore, you’ll learn how to manipulate, format, and understand data in Tableau. You’ll explore the most advanced database queries and procedures and feel comfortable presenting your visualizations to others by the end of the course.
In Laurel, Maryland, you can enroll in the SQL Querying: Basic course from Certstaffix Training. Here, you’ll spend two days learning basic SQL skills and exploring database concepts like grouping and summarizing data. Furthermore, you’ll learn how to join tables and clauses. You’ll also study writing simple queries and practice using built-in functions. The lab environment promotes hands-on learning and interaction with the material.
The American Management Association offers an Advanced Tools and Techniques for Data Analytics course in Baltimore that provides an interactive exploration into statistical and predictive analysis as well as data visualization tools. You’ll learn how to apply your skills to practical data analytics situations, making it ideal for those who want to turn their data analytics skills into a full-blown career.
At the Human Resources Institute in Oxon Hill, you can enroll in the Microsoft Excel: Level I course. This two-day exploration into foundational Excel techniques and tools will prepare you to partake in numerous data analytics situations. Specifically, you’ll practice data entry and calculation in addition to text functions, formatting, and charts. This program is intended for those who wish to become, or already are, federal employees.
Corporate training is becoming increasingly common among the most successful companies, both big and small. That’s because it’s an ideal way to upskill any team, including the data analytics team. It enables them to work more efficiently and effectively with data and also with one another. By investing in training, companies can ensure their teams are equipped with the skills and techniques necessary to improve their data-driven decisions, optimize workflows, and solve complex challenges. For comprehensive training, Noble Desktop offers customizable corporate training sessions, both in-person and live online, that meet the standards and needs of any organization, regardless of size or location.
In addition to Noble Desktop offering accessible and flexible training, they also give your organization the chance to purchase bulk vouchers for regular classes at a discounted rate, which provides a cost-effective way for team members to keep learning. If you are ready to elevate your team’s data analytics skills and improve overall workflow, consider reaching out to Noble Desktop at corporate@nobledesktop.com to discuss pricing, scheduling, and training options.