Gain practical experience with Excel, SQL, and Tableau while building a strong foundation in data analytics.
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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.
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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.
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Data analytics is all about making sense of complex datasets that may otherwise look jumbled and have zero connection. The process involves turning raw numbers and information into something useful that helps you make better decisions, resulting in better outcomes. By finding hidden patterns, trends, and insights, you can figure out why sales have dropped, find ways to increase consumer engagement, or predict future trends for the company. Basically, data analytics helps you help the company through data-driven decision-making.
The history of data analytics can technically be traced back as early as the Stone Age where basic forms of data collection and analysis were used such as tally marks to track items. In the late 19th century, the automobile emerged and consequently, data analytics became necessary for tasks such as tracking assembly line speed times. Fast forward nearly a century, with the invention of tools like the computer, relational databases, and SQL, which revolutionized the way data was maintained, collected, and managed. Today, data analytics is often automated and performed in nearly every industry for businesses to see continued growth and relevance in the competitive market.
Data analytics training is useful for many reasons; if anything, for the sheer number of industries in which data analysis professionals can find work. Your data analysis skills will be useful for everything from helping companies track consumer behavior and streamline inventory strategies to analyzing patient data to improve treatment methods. You could also use your skills to help simplify complex financial data or improve public services. With so many different paths to take, you will never feel out of options.
You can also complete numerous projects as a data analysis professional, regardless of the industry. One day, you may be tasked with segmenting consumers based on their behaviors such as which groups purchase which products the most. The next day, you may be tasked with A/B testing, which involves running different experiments to see which consumers react more positively. Overall, whether you forecast upcoming sales for the quarter or use data to predict maintenance needs for software or machinery, each day brings a new project, which keeps the job dynamic.
Even if you learn data analytics for a future career, there are many ways to use your skills in your everyday life as well. For instance, you can use your data analysis skills to manage your budget and keep track of your spending habits. By doing this, you can see where you can pull back and figure out ways to save more money each month. Similarly, you could track your fitness progress, particularly if you wear a Smart Watch. All in all, data analytics is an incredibly valuable skill that pays off in more ways than one.
Data analytics courses, bootcamps, and certificate programs cover different topics based on their level and focus. Some teach only the basics, like data cleansing and preprocessing. Others focus on specific tools, like Microsoft Excel, whereas others will cover data visualization on a broader spectrum. More advanced courses may dive deeper into machine learning concepts as well. Each class varies, but you’ll gain a solid understanding of these topics in a variety of data analytics courses.
One of the most essential steps in data analysis is the cleansing and preprocessing stage. Here, you fix any issues such as duplicates or missing information. This makes your data ready for the actual analysis stage since it’ll be organized, free of errors, and therefore will come out far more accurate. Skipping this step will skew the entire data analysis process, so it’s easy to see why data analytics classes of all levels will cover this step.
To work with data efficiently, you will have to learn programming languages. The most common for data analysis include Python, R, and SQL. They are all used for somewhat different purposes, but all play a major role in the data analysis process. For instance, Python has libraries such as Pandas and NumPy that enable easy data manipulation whereas R can work best for statistical analysis. Mastering these languages is essential so you will practice using these in a data analytics course.
Excel is one of the most widely used tools in data analytics, which is no surprise. It’s an industry-standard tool in many fields due to its simplicity and ease of use. There are powerful tools such as PivotTables and formulas that make data analysis and visualization less stressful and time-consuming. Additionally, it’s best for analyzing basic datasets, creating reports, and organizing data. Even if you use more advanced tools, it’s an essential skill to have.
Once you’ve analyzed your data, you’ll have to figure out the best way to present it, particularly to someone with little experience with data analysis. Tableau, Power BI, and Excel are among some of the most useful data visualization tools. These allow you to create graphs, charts, tables, and dashboards that reveal trends and patterns in the raw data. Good visualizations make all the difference when discussing your findings with colleagues, clients, and stakeholders, so this is an essential skill for any level of data analytics student.
Machine learning isn’t always necessary for Data Analysts but it may be worthwhile to learn basic machine learning skills such as supervised and unsupervised learning and how to build basic models. This can boost your analytical skills and help you predict trends even quicker. Aside from that, it can cause you to stand out among others when you apply for a new data analytics position, which is always beneficial.
Learning data analytics can be a little challenging but it mainly depends on your background and goals. If you are a beginner with hopes of making data analytics into a career, certain concepts can be relatively difficult. However, if you have relevant experience, this may not be the case. Likewise, if you just need a few basic skills, you will likely have an easier time picking up the basics, like learning Excel and SQL. For professional-level skills, you’ll have to explore more complex topics like machine learning or advanced data visualization. While it’s not incredibly difficult to start learning, the further you go in your studies, the more challenging it may get.
There are some challenging parts of learning data analytics, although difficulty is considered subjective. Some may find handling large datasets relatively tricky as cleaning and preparing data for analysis can be time-consuming and require a high level of attention to detail. Furthermore, statistical methods can be especially difficult if your mathematics and programming skills are highly developed. Additionally, some may find sharing their insights the most challenging part since it requires clear data visualizations and strong communication abilities. In other words, this combination of technical skills and creative storytelling can be relatively challenging.
If you plan to make data analytics into a career, you can expect to spend several months to a year, or even more, becoming familiar with data analytics on a more professional level. Learning complex topics such as building machine learning models and handling advanced analytics requires time and effort, so this also depends on how much time you’re able to dedicate every week and if you have any relevant skills. However, if you just want to get comfortable with data analytics concepts such as analyzing simple datasets, or using tools such as SQL, Excel, or Tableau, you could spend anywhere from a few weeks to a few months learning.
If you’re deciding between in-person or online courses, consider your needs, preferences, and goals. For instance, in-person learning is great for hands-on instruction and immersion. It offers direct interaction so you can ask for assistance, get questions answered, receive feedback, and collaborate with classmates. However, this method can be less flexible for those who have busy schedules, particularly if the commute takes longer than expected. However, those with ample time and who live near a training center may find this the most effective learning option.
On the other hand, live online training is also an effective way to learn data analytics, particularly if you have a busy schedule or live further from a training center. You’ll still have the benefits of learning from an expert instructor and can collaborate with peers via the video conferencing platform, which can be done from any location. It’s flexible and effective, but time zone differences could cause issues as well as potential technical difficulties. Still, if you are unable to make it to an in-person class, this is a great way to learn data analytics.
Asynchronous learning, on the other hand, is a self-paced, self-taught training method that will not benefit everyone equally. While it’s incredibly flexible and allows you to learn when and how you want, it lacks interaction that would make learning the material stick. In addition, you’ll need a high level of self-discipline and motivation to ensure you complete the material, which may be hard if you get discouraged. Plus, you’ll need to answer your own questions since there’s no instructor to assist with this. However, if you are a current professional or someone who just wants to learn for personal reasons, an asynchronous class may be a good option.
Through exploring free resources online, you can gain a solid understanding of what data analytics is and learn some key terms and the purpose of certain tools. This is a great place to start since there are countless resources online. You can explore social media accounts from professional Data Analysts to learn more about the career path or enter chatrooms where people of all levels of expertise share insights and feedback. However, starting with a training center’s resources is one of the best options. For example, you can check out Noble Desktop’s Free Seminar page for pre-recorded lectures or the YouTube channel for playlists on SQL, Python, Excel, and data science. However, this is just a starting point. You will need to search for a thorough, hands-on training method if you want to become a professional.
When learning data analytics, it may be a great idea to explore different topics that are complementary to the field. For instance, artificial intelligence (AI) and machine learning are useful. These fields build on your data analytics skills, helping you develop predictive models and automate tasks to make smarter decisions based on data insights. AI and machine learning are becoming increasingly prevalent in many facets of life and are proving more and more essential for analyzing complex datasets and uncovering patterns that traditional analysis can’t.
You may want to get familiar with business intelligence (BI) tools like Power BI as well. This is useful for those who work in business analytics especially since it’s designed to help you visualize data, create interactive dashboards, and make your findings far more simplistic for those working in other departments as well as the layman or stakeholders. Power BI in particular integrates well with other Microsoft products such as Excel, which is widely used in data analytics for reporting and visualization.
Data analytics has become deeply ingrained in nearly every industry and business as it is the perfect way to make more informed decisions, improve efficiency, and stay competitive. You can work in technology, finance, or healthcare, or even explore the world of film and media. In these next sections, you can read about different industries in New Jersey that contribute heavily to the economy and figure out which seems most aligned with your goals and preferences.
The technology industry covers everything from software development and communications to cybersecurity and AI. This industry is growing steadily across the state of New Jersey, especially in places like Newark and Princeton where there are numerous tech companies, startups, and research institutions. For instance, MongoDB, LanceSoft Inc., and Nielsen are all located in Princeton. The state is also popular for data centers and cybersecurity firms so there are many job opportunities in the state.
Data analytics is also a huge part of the tech industry. It’s key for improving products, learning more about consumer needs, and optimizing workplace operations. Tech companies will use data analytics to improve their software as well or predict trends in sales, which can in turn enable them to prepare for an uptick or a downturn. Overall, data analytics helps companies stay ahead of the game and maintain a competitive edge.
The film and media industries in New Jersey are incredibly strong, particularly with New York City being in such close proximity. Film studios, production companies, acting schools, and traditional media studios such as television and radio, are prominent all across the state. In addition, there are streaming service companies in the region as well. Regardless of how you want to work in the film and media industries, New Jersey provides numerous opportunities.
Data analysis is incredibly necessary for film and media, although it may not be one of the most commonly considered roles within this industry. For instance, data analytics can help improve marketing techniques for new projects or enable streaming platforms like Netflix to provide personalized recommendations to consumers. In addition, Data Analysts can determine gaps in the market and suggest new audiences to engage with when a new film or television show comes out. News stations can also gain insight into which viewers are most likely to tune in every night and therefore curate more personalized stories.
New Jersey has numerous financial institutions that employ a large number of residents, including everything from big-name companies like Prudential Financial, Goldman Sachs, JP Morgan, and Lakeland Bank as well as smaller, more local institutions. The state also has close ties to New York City’s Wall Street, which makes it an even stronger financial hub including everything from investment firms and banks to FinTech startups and insurance companies.
In finance, data is used to avoid risks, detect fraud, and help companies make better investment decisions for clients. In addition, banks often analyze data that predicts market trends and enables them to offer their customers insights into the market and, ultimately, better services. It’s also useful for personalizing services, improving lending processes, and helping employees with day-to-day workplace operations.
The healthcare industry is strong in New Jersey thanks to the large, diverse population. Many well-known medical institutions are located in New Jersey such as Hackensack University Medical Center and Morristown Medical Center. The state is home to some incredible medical schools and biotech firms as well, which support the healthcare industry even further. This industry is essential to the New Jersey economy and has opportunities beyond just medical care such as administrative roles and behind-the-scenes work.
For example, data analytics plays a crucial role in the healthcare industry. It enables healthcare providers to offer more efficiently run ICUs with better, streamlined medical services. In addition, insurance companies can manage their costs by analyzing trends and tracking outcomes. Biotech and pharmaceutical companies use data analytics to optimize drug development or improve clinical trials.
You can pursue numerous jobs related to data analysis with the right training. Whether you want to focus on business practices or general data analytics, as well as databases or machine learning, New Jersey residents have many options. Here are just a few job titles and their expected salaries across the state.
A Data Analyst gathers, cleans, and analyzes data to uncover trends and insights. This helps businesses make smarter decisions when deciding the next course of action. Data Analysts in New Jersey earn a yearly average salary of $85,000 according to data collected on Indeed. However, it all depends on your location. For instance, analysts in Summit can earn closer to $126,000 whereas those in Newark can take home $97,000. Those residing in Princeton align more with the state average as well as those in Trenton.
Machine Learning Engineers build algorithms that can learn from data and make clearer predictions and decisions without explicit programming. They often apply techniques like supervised or unsupervised learning to large datasets, which is an extension of data analytics into predictive modeling. Indeed provides more insight into salary expectations for this role. A Machine Learning Engineer in the state of New Jersey earns an average base salary close to $154,000. Those in Jersey City surpass most others based on reported salaries from that area, landing at $215,000. In Princeton, the average is slightly less, landing at $140,000.
A Database Administrator organizes and manages the data within different systems to ensure it is safe and secure but also easily accessible. They also optimize queries and keep up with data integrity, which is essential for accurate data analysis. According to Glassdoor, a Database Administrator in New Jersey can expect to earn between $88,000 and $122,000 with a yearly average of $104,000. Still, this all depends on location as well as other factors like level of experience.
Business Analysts derive insights from data to address a company’s needs. They identify trends in data to share what can be improved within business operations, from finances and social media to assembly lines and supply chain management. All in all, they use data analysis to solve business-specific problems. Glassdoor shares that a Business Analyst in New Jersey earns an average of $94,000 per year, but the range is realistically anywhere between $75,000 and $118,000.
For a thorough and in-depth look at data analytics tools, concepts, and practices, check out the ||CPN395|| from Noble Desktop. This course spans 156 total hours, covers the most essential tools such as Excel, Tableau, SQL, and Python, and offers a free Python for AI course. You’ll learn how to use Python for automation and machine learning practices and master Tableau to create clear, impactful data visualizations such as charts, dashboards, graphs, and tables. The instructor will guide you through complex datasets and assist with extracting data using SQL. You’ll also gain practice presenting your findings, develop a professional portfolio, and earn a certificate of completion to show for all your hard work.
On the other hand, the Data Science and AI Certificate from Noble Desktop offers hands-on learning and an overview of data science concepts, including analytics. In this program, you’ll work with Python and SQL to automate processes, create visualizations, and apply machine learning methods. Moreover, you’ll dive into analyzing tabular data with NumPy and clean datasets with Pandas. As part of the course, you’ll also practice developing data visualizations using Matplotlib. Projects include anything from double line graphs and heat maps to 3D models and animated bar chart races. Much like the ||CPN395||, you’ll have free enrollment in the Python for AI course to further develop your AI skills. By the end, you’ll have a comprehensive understanding of the subject matter, a portfolio, and a certificate of completion.
If you need a shorter introduction than a certificate course could offer, consider Noble Desktop’s 12-hour Data Analytics Foundations course. This course provides students with the fundamentals of data analytics and shows them how to use different methods for analysis such as descriptive and inferential statistics. You will learn to use data for forecasting and decision-making and explore data visualization projects like charts, histograms, sparklines, and Pivot Tables.
From Rutgers Bootcamps comes a Data Science Bootcamp located in Somerset. Throughout 24 weeks, you will prepare for a career in database administration, data science, or data engineering. You’ll specifically learn how to use programming languages such as Python, JavaScript, and SQL as well as tools like Excel and Tableau. Students will leave the bootcamp with a portfolio that can take them into the job search.
NextGen Bootcamp provides a Python Data Science and Machine Learning Summer Program for high school and college students who want to take their skills to the next level. In Hackensack, this 45 total hour course includes lessons in Matplotlib, Pandas, and scikit-learn which enables students to learn how to input, visualize, and analyze data. This course is also essential for anyone hoping to master Python fundamentals.
In Bridgewater Township, you can enroll in the Tableau Desktop: Business Intelligence course from Certstaffix Training. This is a two-day course that teaches students how to use Tableau for data visualizations. You’ll cover topics ranging from analytics and data preparation to story points and data organization. This is ideal for business professionals who require strategic, data-driven decision-making skills.
Corporate training is one of the most effective ways to help your team upskill, enhance collaboration, and improve workplace outcomes. By bringing employees together for training, everyone learns at the same pace, which helps foster a cohesive environment but also a shared understanding of data-driven decision-making. This means your team will leave with the skills and tools necessary to work more efficiently as a collective rather than as separate parts. Noble Desktop offers customized corporate training that can be tailored to your group’s specific needs, with both in-person and live online options available. No matter the size of the company, corporate training can truly make a big difference.
Additionally, Noble Desktop offers organizations a discounted rate for bulk vouchers of regularly attended classes. This means your team can learn beyond their corporate training and continue to sharpen their skills, explore new concepts, and stay updated with industry trends. If you are ready to upskill, contact Noble Desktop at corporate@nobledesktop.com to ask about pricing, scheduling, and training options.