In the modern economy, few things are more important to businesses and organizations than “big data, ” the massive collection of user data, behavior and metrics that companies use to make sense of the wants and needs of their customers. Data analytics is the process by which trained professionals read and analyze data, helping companies and organizations draw insight from the unfathomable amount of data humans produce daily. Data analytics has become increasingly common in other sectors, including the financial services industry, non-profits, sports and entertainment and government services. This has led to a significant spike in-demand for data analytics professionals.
Noble Desktop: Data Analytics Certificate
Key Information: This program is available in-person or in live online classrooms and can be completed in six weeks (full-time study) or 24 weeks (part-time study). Career development services include one-on-one mentorship sessions, industry-centered training, and free retakes within one year.
Students seeking a comprehensive data analytics education should consider enrolling in Noble Desktop’s Data Analytics Certificate program. This career-focused training program aims to provide students with the practical and technical skills they will need to find work as professional Data Analysts. Students will receive hands-on experience working with large datasets and will get foundational training working with programming languages such as Python and SQL, which are essential for advanced data analysis projects. Then, students will learn the practical art of data visualization to better communicate their findings to invested parties and stakeholders.
This course, open to complete novices, provides students with a complete data analytics education, starting with training in the use of Excel for building databases. Once students are comfortable building databases, they will learn how to use Python and SQL to organize, wrangle, and query their data, making it easier to work with and allowing them to start drawing inferences from it. Students will learn how to automate aspects of the data collection process and be introduced to machine learning concepts, so they can start building and training AI and neural networks that read and interpret data on their own. The course concludes with a training seminar in Tableau, one of the most commonly used data visualization tools available. Students will learn to create evocative and compelling charts and graphs that can easily communicate their findings to stakeholders and investors.
This program is available for students in-person at Noble Desktop’s Manhattan campus or in a live online classroom. Regardless, students will still enjoy live instruction from Noble’s expert data analytics instructors, who can guide students through their difficulties and provide them with feedback on their work. As a professional development program, this course aims to prepare students for entry into the job market once they graduate, meaning all the lessons that students learn will be modeled on real-world projects. In addition to the practical training, Noble offers students career development services, including one-on-one career mentorship and portfolio-building workshops to help them prepare job materials. Students looking for more training will be able to retake the course, for free, within one year, giving them even more time to get hands-on experience working with big data.
Noble Desktop: FinTech Bootcamp
Key Information: This professional development program is available in-person or in live online classrooms and runs for four weeks for full-time students and four months for part-time students. Students will have the opportunity to work one-on-one with career professionals, and they can retake the course within one year.
Students seeking a more targeted, practical data analytics education may want to consider a course like Noble Desktop’s FinTech Bootcamp. This program introduces students to financial data analytics and the most common practices used by Investment Analysts and Financial Analysts to understand markets and make sound long-term decisions. Smart financial strategists are taking advantage of the tools offered by big data collection and analysis technology. Anyone hoping to find work on Wall Street will want to learn how to use these tools. In Noble Desktop’s comprehensive, career-focused certificate program, students will learn how to utilize these new technologies and how to find work in the field of professional financial analysis.
The program introduces students to the Python programming language and its functions in data science. Students will learn how to program and query databases and how to automate data collection, which is vital given the huge amount of data that markets produce on any given day. Then, students will learn how Python can create evocative data visualizations that let professionals communicate with clients and investors, a vital skill for anyone looking to handle other peoples’ money. The course also introduces machine learning algorithms, giving students an understanding of this new technology and a practical lesson in how it is utilized in the financial sector. All of the lessons in this course are tailored to the present reality of the financial services industry, so students will learn the practical application of their skills in a career-focused learning environment.
This course is offered in part-time or full-time sessions, and students can either enroll in-person at Noble’s Manhattan campus or online in private digital classrooms. No matter what modality you pursue, you’ll receive live instruction from Noble’s data analytics experts, and you can turn to them for feedback and assistance even online. As a career-focused program, all of the lessons aim to prepare students for real-world financial situations, and the course comes with career-development services, including one-on-one career mentoring sessions. In addition, students can retake the course within one year’s time, giving them even more opportunities to learn FinTech skills from Noble’s expert instructors.
Certified Analytics Professionals: CAP™ Certification
Key Information: This professional certification exam is a 100 one hundred question multiple choice exam covering all the major practical elements of business data analytics. Students who pass the exam will be certified for three years, and CAP offers several options for certification-holders to remain current on their credentials.
Students looking for a professional certification option may want to consider the Certified Analytics Professional (CAP) certification, an industry-recognized third-party certification exam that gauges a student’s understanding of essential data collection and analysis techniques and practices. The course covers practical job analysis training, focusing on seven subfields: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. The exam tests students on all major aspects of professional data and business analytics, making this an ideal exam for students looking to demonstrate the breadth of their data analytics skills. CAP also offers an associate-level examination for students with fewer hands-on experience in data analytics and business intelligence.
Each exam comprises 100 multiple-choice questions, and students will have two opportunities to achieve a passing score (about 70%) within one year. CAP offers free study materials and sample exams for students who sign up for the exam. They also offer paid individual or group training sessions for students looking for more intensive study sessions. These certifications last for three years, and CAP offers a Professional Development Unit program to help certified experts stay current on their credentials without needing to retake the exam every few years.
Data Science Council of America: Associate Big Data Analyst Certification Exam
Key Information: This certification exam is intended for entry-level data analytics professionals with a bachelor’s in computer science or equivalent professional training. The exam has 100 multiple-choice questions and covers all significant components of professional data analytics. Certifications last for three years.
The Data Science Council of America is an industry-recognized certification exam provider emphasizing practical, professional data science and analytics skills. Their Associate Big Data Analysts Certification is an ideal fit for students with some practical experience or formal training looking to become certified as professional Data Analysts. The exam covers the foundations of data science and the mathematical principles behind the field, including statistical analysis, linear algebra and calculus. Then, students will be tested on the practical applications of these skills, including questions on working with data, programming with Python and R, and visualizing data with Tableau. Finally, students will answer questions about the business and professional applications of big data and the use of machine learning in data projects.
The exam lasts 100 minutes and is available completely online. Students who register to take the exam will receive two DSCA handbooks of study materials, and they will have six months to prepare for their test. The study materials are comprehensive and self-paced, giving test-takers ample opportunity to prepare for the exam. DSC recommends that students aiming to pass the Associate Big Data Analyst exam have either a bachelor’s degree in computer science or an equivalent level of professional development training. The certification lasts for three years, and the DSCA offers several options for recertification, including several that bypass the need to retake the exam.
Google Career Certificates: Google Data Analytics Professional Certificate
Key Information: Google offers an online, asynchronous certificate program for students looking to learn data analytics. This approximately two-hundred-hour course is self-paced, and students are expected to complete the program in about six months (of part-time study). Graduating students will have access to the Coursera platform’s career support services.
Offered through the Coursera online learning platform, Google offers a Data Analytics Professional Certificate training program for students looking to learn data analytics at their own pace. This asynchronous training program teaches students data analytics tools and practices, including lessons in R and SQL, spreadsheet management and data visualization. The course aims to teach students practical data analysis skills that they can use in a wide variety of professional contexts, and the Google certificate will help students achieve their career goals. The course is delivered asynchronously, but students will still receive hands-on, project-driven instruction that provides the training they need to apply their skills to real-world data projects and analytics scenarios.
The course offers on-demand material and is broken up into eight significant sections, including a final capstone project that students can use to demonstrate their practical skills to prospective employers. The course includes about 190 hours of content students can move through at their own pace. Google estimates that most students spend about ten hours a week on coursework and complete the program in about six months. The course is designed with beginners in mind, and students won’t need significant training to enroll (though basic computer skills are necessary). After completing the course, students can access Coursera’s career resources, including interview prep services and resume writing support.
General Assembly: Data Analytics Immersive
Key Information: This 12-month data analytics training program is a full-time course offered in-person and online. Students enrolled in the program will receive access to career mentoring services, including one-on-one coaching and General Assembly’s expansive hiring network.
General Assembly offers a Data Analytics Immersive program for students interested in attending a comprehensive certificate-granting data analytics training program. This career-focused, practical data analytics training program aims to teach students the real-world data analysis skills they will need to find work in an industry defined by big data collection and analysis. Students will receive an education that blends practical training in skills like Python and Tableau with grounded lessons in the ethics and best practices of data collection and analysis. Students will receive live instruction in both in-person and online classrooms, giving them additional training flexibility. The course is designed with “true beginners” in mind, so you won’t need any data science experience to succeed.
The course runs full-time classes every day for twelve weeks, and in-person and remote instruction options are available. This is a career-focused training program, so all of the lessons are designed with practical work scenarios in mind, and students will receive lessons that are transferable to a diverse range of different professional fields. Students enrolled in this program will receive access to career development support services, including one-on-one career mentorship and access to networking and job search opportunities through General Assembly’s hiring network. Financing options are available, and General Assembly regularly holds information sessions for students looking to learn more about the program.
ECornell: Data Analytics
Key Information: Offered by Cornell University, this part-time, fully-online data analytics certificate program provides students with practical career training in data management and analysis skills. The course meets for approximately 3-5 hours per week and lasts nine weeks.
Cornell University offers an expansive online continuing education program, including a robust Data Analytics Certificate program. This course provides students with practical training in data visualization techniques, predictive analytics tools, and theories. In addition, the course emphasizes teaching students the critical thinking skills required to approach data analytics problems and how to apply their data analytics skills in their professional lives. Lessons will mirror real-world data scenarios and look at a business-oriented approach to understanding and utilizing data. In addition to learning business analytics, students will learn how to use applications such as Tableau to create graphs and charts that communicate their data findings to non-specialist audiences.
This course is a part-time, fully online training program offered by the Cornell computer science and business faculty. The program is offered over nine weeks, and students can expect to spend around three to five hours per week working on material outside of the classroom space. This makes the course a good way for students with business schedules to receive live online instruction from a reputable training provider. Students will receive a certificate of completion from Cornell University, and the course will count as 45 hours of professional development training for certification purposes and 26 hours of training for PMI recertification purposes.
Microsoft: Microsoft Power BI Data Analyst Associate
Key Information: Microsoft offers specialized data analytics certifications to students proficient in using their Power BI data analysis platform. These exams last 100 minutes and test students’ general data analytics knowledge and their skill with Power BI tools. Certifications last one year, but Microsoft offers a range of options for recertification without needing to pay to retake an exam.
Another path to certification is to become certified in using specific data analytics platforms and services through certification exams like Microsoft’s Power BI Data Analyst Associate program. This exam covers a wide range of data analytics skills, including testing students’ ability to prepare, model, and visualize data and maintain their databases and assets. All of these skills are tested using the Microsoft Power BI platform to gauge whether a test-taker is prepared to utilize its functionalities in a professional environment. Candidates will also be tested on their understanding of data security practices and data-sensitivity concerns. This certification exam will demonstrate a candidate’s understanding of broad data analytics practices and the practical use of Power BI to facilitate those practices.
This exam lasts one hundred minutes, and questions are divided to cover all the important aspects of Power BI and data analytics. Students enrolled in this exam can take it online and can use their own access to the Power BI platform to complete practical skills questions. The exam costs $165, and passing grades average around 70%. Students who sign-up for an exam will receive free study materials and sample exams, and live instruction is available for an additional fee. This certification expires after one year, but Microsoft offers free recertification services that students can use to demonstrate their continued Power BI proficiency without needing to pay to take another exam.
CareerFoundry: Data Analytics Program
Key Information: This fully online, asynchronous data analytics certificate program takes full-time students approximately four months to complete and part-time students approximately eight months. Students can access one-on-one career mentoring services, and CareerFoundry offers a job placement guarantee.
CareerFoundry offers a fully online, asynchronous Data Analytics Program for students looking to become certified in data management skills. The course begins with lessons in the history and basic practices of data analytics, including lessons in using Excel, wrangling and cleaning data and using visualization tools to make your data tell a story. Then, students will move onto immersive data analytics achievement tracks that will have them working on practical projects that they can add to their own professional portfolios. These include exercises in managing and analyzing data, using SQL to create searchable databases, concerns surrounding ethical data management and data visualization exercises. By the end of the program, students will have built a collection of projects that they can show prospective employers to demonstrate their proficiency in data analytics.
This is a completely asynchronous course, so students can learn at their own pace and complete the lessons as they see fit. Since this is a self-paced course, students will finish the program at different speeds, but CareerFoundry estimates that part-time students will complete the program in about eight months. Students will be paired with a program instructor who can keep them on track and provide them with one-on-one mentorship and assistance, and they will have access to CareerFoundry’s career coaching services. CareerFoundry offers a money-back guarantee that students who meet certain requirements will find a job in six months or have their tuition refunded.
Rice University: Data Analytics & Visualization Bootcamp
Key Information: Rice University offers this online, part-time data analytics bootcamp. Students will be expected to work approximately 30 hours per week over the twenty-four-week seminar. Enrolled students will have access to Rice University career services, including one-on-one mentorship and professional networking opportunities.
Rice University offers a dynamic, online Data Analytics & Visualization Bootcamp for students seeking professional training in practical data management skills. This program covers everything from basic programming training (including HTML and CSS, JavaScript, SQL and Python) to complex data analysis projects like machine learning algorithms and deep learning techniques. This course aims to give students the career skills they need to pursue a professional future in a data analytics-related career. Students will learn how to use common business intelligence applications, and the lessons all focus on the practical application of data analytics techniques. These skills are all highly transferable, so students will be able to follow their own passions and interests while making use of their data science training.
This program is fully online and offers flexible part-time scheduling options. The course lasts for twenty-four weeks, with an expected nine hours of live classroom sessions and about twenty hours of hands-on, self-paced projects and exercises. The program is taught by experienced data science professionals who can help guide students through the challenging concepts covered in the course. Students will also receive access to career development assistance services, including one-on-one career coaching sessions, industry speakers and a network of peers and tutors with whom students can collaborate. This course has no formal requirements, but students are encouraged to have some background knowledge of business management and statistics.
Frequently Asked Questions
What is the Difference Between a Certification and a Certificate?
Students looking at the options for becoming certified in data analytics may be surprised to discover that certificates and certifications are different. They are both methods of becoming certified, and they both demonstrate a student’s proficiency in practical and theoretical data analytics skills, but they demonstrate those skills differently. Certifications are awarded to students who pass exams offered by first-party application publishers or third-party vendors. These exams test students’ existing knowledge of data science principles and techniques, and many first-party exams focus on using specific data analytics applications. While exams do include study materials, they are intended to test the knowledge that students already have, so there is no formal training component to certifications. Most certifications expire after a fixed period of time, and many will require students to retake the most recent version of the exam to keep their certification up-to-date.
Certificates are more like diplomas since they are awarded to students who successfully complete industry-recognized training programs. Unlike certification exams, which test existing knowledge and experience, certificate programs are designed to train students in practical, hands-on data analytics skills. These programs are designed for students who have minimal data analytics experience and are looking to learn the skills they need to start a new career path. These programs tend to be more expensive and time-consuming than exams because they are training courses that aim to build students’ career potential rather than judge whether they already have experience and knowledge. Certificates granted by these programs do not tend to expire once a student has completed the course.
Should I Pursue a Certificate or a Certification?
Deciding whether to pursue a certificate or a certification will likely depend on how comfortable you are with your existing data analytics training. Students who have professional training, on-the-job experience or a college-level degree in a data-related field are likely to find it easier and more cost-effective to pass a certification exam since they have already spent the time and money to build their skills. These programs do often come with supplemental study materials that can help make the process of completing the exam significantly easier.
Students who don’t have a background in data analytics are likely to want to enroll in a certificate-granting program since the main appeal to these programs is the training you receive. Students who want to shift into a new career will benefit from this focused, professional training, and the certificate they receive from their training provider will signal to prospective employers that they have gotten the training they need to be ready to start working on data analytics projects immediately. These programs are also a good place for students with some data analytics training to hone their skills in preparation for a certification exam.
Do I Need to Be Certified to Find a Data Analytics Job?
While it will vary from job to job, becoming certified isn’t always necessary for aspiring Data Analysts. Many jobs don’t require or offer certification as part of their on-the-job training. There are exceptions to this, particularly if you are applying for a job with sensitive data like banking information or social security numbers, but it won’t be a hard requirement. However, becoming certified will open the door to other job opportunities, and it will demonstrate to employers that you have the formal skills training required to start working immediately. It can also help set you apart from other applicants.
What Certificate Program is Right for Me?
Students who opt to enroll in a certificate program will have a lot of different options to choose from. Between professional training centers, universities and first-party publishers, there is no shortage of options for students looking to receive top-quality training in data analytics. When considering their options for further training, students must decide between in-person or online classes and live, self-paced or hybrid classes. All of these different modalities come with different advantages and disadvantages, so students should consider their long-term goals and learning styles when considering what course to enroll in.
Which is Better: In-Person or Online Instruction?
With recent developments in online learning, more and more training centers are offering their certificate-granting courses through online learning platforms. Online learning has greatly improved over the last few years, and nowadays, online training can be just as thorough, engaging and effective as in-person training. This means that students will need to seriously consider whether online or in-person learning is right for them, particularly if they are looking for a live training program to suit the needs of their schedule or career goals.
Many students still prefer in-person learning because the classroom space is very useful for keeping them engaged and directing their attention toward their instructor. In-person courses are also ideal for students to work directly with their instructors and receive hands-on assistance with difficult concepts like writing machine learning algorithms or creating automated databases. Students will also have the opportunity to work directly with classmates on collaborative projects, which can provide valuable experience and productive networking opportunities. The drawback to these classes is that students can only enroll in courses offered at locations they can physically attend, which can greatly restrict their options if they are not located near a major city. Students will also have less flexibility in their schedules since fewer training options are available.
Online learning allows students to practice their data analytics skills from anywhere. As long as students have an internet connection, they can enroll in classes offered nationwide. This will significantly expand students’ options for finding the training program that suits their needs. Students will still be able to find courses taught by expert instructors and, if they enroll in a live online class, will be able to receive feedback and assistance on their work. Students looking for greater flexibility in their schedule can enroll in a self-paced online class and engage with materials when they can. The drawback to these classes is that students will need to do more work to stay motivated and on top of their lessons, particularly if they are enrolled in a self-paced program. In addition, students may miss the social atmosphere and opportunities provided by working directly with classmates (though many online classes still include collaborative projects).
Which is Better: Live, Self-Paced or Hybrid Instruction?
Students who enroll in an online class will then need to decide whether they want to enroll in a live online class, a self-paced class, or a hybrid course. Live courses are similar to in-person classes, featuring a live instructor providing lessons over a digital telecommunication platform. These classes let students get real-time feedback and assistance from their instructors. Self-paced (or on-demand or asynchronous) courses give students all of the material they need upfront, usually in the form of recorded lectures and interactive modules and let the students learn at their own pace. Hybrid classes combine the two modalities, and while they vary from class to class, they tend to lean more heavily toward self-paced learning.
On-demand classes are best suited for students who need the added flexibility of being able to work for different amounts of time each week and can’t commit to a scheduled course. They are also suitable for students who want to learn a specific aspect of a tool or programming language and aren’t starting from scratch. The drawback to these classes is that without a live instructor to assist students, it can be difficult to keep up with the course materials, and students may find it hard to stay motivated, particularly if they run into problems early on in their training. Students also won’t have a means of receiving feedback on their work, making it hard to develop important data visualization and computer programming skills. Also, since many programs involved in data analytics are constantly being updated, it is possible that even a reputable training program will provide students with out-of-date information, which can further delay a student’s training.
Live online training provides students almost all of the advantages of in-person training without requiring a commute. Students will be able to ask questions and receive feedback in real-time, and get personalized support if they find that they are facing challenges. Students will also be able to meet their classmates and work alongside them on collaborative projects. Finally, students can be more comfortable knowing that their learning material is as up-to-date as possible. Live online classes have stricter scheduling requirements, though many programs offer part-time options for students with work or family obligations, and they tend to cost more (since they are more thorough and in-depth). As a general rule, unless you absolutely need the flexible scheduling offered by a self-paced course, the advantages offered by a live online model more than make up for the added cost.