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Masters in Data Analytics Online
Introduction
Masters in Data Analytics Online
Best Programs
Masters in Data Analytics Online
Affordable Programs
Masters in Data Analytics Online
Program Details
Masters in Data Analytics Online
Difference between Data Analytics, Data Science and Business Analytics
Masters in Data Analytics Online
1 Year Programs
How To Pay
How to Pay?
Masters in Data Analytics Online
FAQ
Masters in Data Analytics Online
Careers & Salaries
license
Licensing
Masters in Data Analytics Online
Additional Resources

Masters in Data Analytics Online

Masters in Data Analytics Online

In the times that we live in, our world is interweaved between the internet and the amount of data that we access, and the footprint of data that we leave. When we talk about data, the first thing that comes to mind is the internet. But there is data that is not related to the internet also. Information like our demographics, habits, preferences, likes and dislikes, etc. And when we add digital footprints to this equation, the size of data becomes huge. So, if the data is mined and analyzed well, it can give us a ton of information. This information is used by organizations, governments, agencies like air traffic control, marketing companies, for-profit and non-profit organizations for various purposes. And that is where data analysis comes in. Masters of Data Analytics Online programs involve learning about data collection, data mining, analysis, and various techniques used to mine the data and provide intelligence.

Featured Online Programs

Best Masters in Data Analytics Online Programs

Data Analytics Best Seal

A few of the biggest dilemmas while deciding to do a master’s in dataanalytics are which program to pursue is what are the best data analytics programs. And then, there are other considerations such as cost, placements, starting salary, employment rates, acceptance rates, etc. We at OMC went through all these matrices and created a list of the best online master’s in data analytics programs. See the data analytics masters rankings below:

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College Name & AddressTuitionGraduation Rate
#1
Georgia Institute of Technology
225 North Ave, Atlanta, Georgia 30332
$14,06490%
#2
Villanova University
800 Lancaster Avenue, Villanova, Pennsylvania 19085
$20,61990%
#3
University of Wisconsin Madison
500 Lincoln Dr, Madison, Wisconsin 53706
$10,72888%
#4
Worcester Polytechnic Institute
100 Institute Road, Worcester, Massachusetts 01609
$28,98089%
#5
Texas A&M University
JKW Administration Building, Suite 200, College Station, Texas 77843
$6,77582%
#6
Saint Louis University
One North Grand Blvd, Saint Louis, Missouri 63103
$21,42079%
#7
American University
4400 Massachusetts Ave NW, Washington, District of Columbia 20016
$34,53379%
#8
Colorado State University, Global Campus
585 Salida Way, Aurora, Colorado 80011
$9,000N/A
#9
Brandeis University
415 South St, Waltham, Massachusetts 02454
$51,94087%
#10
Boston University
One Silber Way, Boston, Massachusetts 02215
$56,85488%
#11
University of Missouri
105 Jesse Hall, Columbia, Missouri 65211
$9,47871%
#12
George Mason University
4400 University Dr, Fairfax, Virginia 22030
$12,59471%
#13
Oregon State University
1500 SW Jefferson Avenue, Corvallis, Oregon 97331
$13,25767%
#14
New Jersey Institute of Technology
University Heights, Newark, New Jersey 07102
$20,62467%
#15
University of North Texas
1501 W.Chestnut Ave., Denton, Texas 76203
$6,35056%
#16
Southern New Hampshire University
2500 North River Road, Manchester, New Hampshire 03106
$18,81044%
#17
Harrisburg University
326 Market Street, Harrisburg, Pennsylvania 17101
$7,20031%
#18
Western Governors University
4001 South 700 East Suite 700, Salt Lake City, Utah 84107
$7,50021%
#19
University of Maryland Global Campus
3501 University Blvd East, Adelphi, Maryland 20783
$8,64015%

Source Integrated Post Secondary Education Data System & University Data
*Tuition rates are for in-state and per year. Program specific rates may apply.
**NA – data not available

Most Affordable Masters in Philosophy Online Programs

Data Analytics Affordable Seal

The cost of education is such that it is the primary measure for anyone considering an online masters in data science. And to the latest Salliemae study, the average family spent about $ 30,000 on education for the year 2019-20. This is up from $26,266 from a year ago. That is a 15 percent jump in a year. Students that want to pursue a master’s in data analytics online also identify affordability as a key factor in choosing a university. We have researched dozens of programs and created a list of the most affordable data analytics masters:

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College Name & AddressTuitionGraduation Rate
#1
Dakota State University
820 N Washington Ave, Madison, South Dakota 57042
$5,93943%
#2
University of North Texas
1501 W.Chestnut Ave., Denton, Texas 76203
$6,35056%
#3
Emporia State University
1 Kellogg Circle, Emporia, Kansas 66801
$6,54750%
#4
Texas A&M University
JKW Administration Building, Suite 200, College Station, Texas 77843
$6,77582%
#5
University of Oklahoma
660 Parrington Oval, Norman, Oklahoma 73019
$6,94370%
#6
Harrisburg University
326 Market Street, Harrisburg, Pennsylvania 17101
$7,20031%
#7
Western Governors University
4001 South 700 East Suite 700, Salt Lake City, Utah 84107
$7,50021%
#8
University of Illinois Springfield
One University Plaza, Springfield, Illinois 62703
$8,24754%
#9
University of Maryland Global Campus
3501 University Blvd East, Adelphi, Maryland 20783
$8,64015%
#10
Colorado State University, Global Campus
585 Salida Way, Aurora, Colorado 80011
$9,000N/A
#11
University of Missouri
105 Jesse Hall, Columbia, Missouri 65211
$9,47871%
#12
West Virginia University
PO Box 6201, Morgantown, West Virginia 26506
$10,13461%
#13
University of Wisconsin Madison
500 Lincoln Dr, Madison, Wisconsin 53706
$10,72888%
#14
University of California, Los Angeles
405 Hilgard Ave, Los Angeles, California 90095
$11,44292%
#15
George Mason University
4400 University Dr, Fairfax, Virginia 22030
$12,59471%
#16
Oregon State University
1500 SW Jefferson Avenue, Corvallis, Oregon 97331
$13,25767%
#17
Saint Joseph’s University
5600 City Avenue, Philadelphia, Pennsylvania 19131
$17,80281%
#18
Southern New Hampshire University
2500 North River Road, Manchester, New Hampshire 03106
$18,81044%
#19
Villanova University
800 Lancaster Avenue, Villanova, Pennsylvania 19085
$20,61990%
#20
Saint Louis University
One North Grand Blvd, Saint Louis, Missouri 63103
$21,42079%

Source Integrated Post Secondary Education Data System & University Data
*Tuition rates are for in-state and per year. Program specific rates may apply.
**NA – data not available

Understanding Masters in Data Analytics Programs

The first thing to understand when discussing a master’s in data analytics is the difference between analysis and analytics concerning data. An analysis is the study of historical data to understand the trends and the patterns. In other words, analysis helps answer the ‘HOWS’ and the “WHYS’ from a historical point of view. On the other hand, analytics tries to implement data applications’ considering the intelligence gained from analyzing the data. Though the program is called a master’s in data analytics, students learn data analysis and data analytics in this stream.

Analytics applies to two areas, Qualitative Analyticsand Quantitative Analytics. Mainly in qualitative analytics, one uses intuition and experience with the combination of the analysis results for a good decision, on the other hand, in “quantitative analytics”, one uses formulas and algorithms to apply on the numbers that one already gathered from the previous step, analysis, to predict and prepare for the future.

Typically, the data analytics practice encompasses many separate processes, which can comprise a data pipeline as listed below:

Tools for Data Analytics

Analytics software is a tool that helps humans and machines perform the analysis that allows us to make mission-critical business decisions.

Common tools for performing data analysis and overall analytics include:

  1. Microsoft Excel
  2. Microsoft Power BI
  3. Tableau
  4. R analytics
  5. Python
  6. Google Analytics

Masters in Data Analytics Degree Types

There would typically be a few variants of a master’s in data analytics, with a few subjects changing concerning the specialization being pursued. Master’s in Data Analytics programs mainly come in three degree formats – MS in Data Analytics, MPS in Analytics, and MBA in Data Analytics. Below we would discuss the different types of master’s that can be pursued in data analytics.

Master’s of Science in Data Analytics programs prepare students to step into specialist roles in analytics, business intelligence, and even data science. Typically, these students have strong STEM backgrounds and pursue this science degree to get into the Data Analytics field and/or want to increase their career prospects by becoming a Master of Data Analytics.

This program is designed for students looking to hone their analytical skills to provide data-driven business recommendations. MBA in Data Analytics programs focus on the business side of Data Analytics and not necessarily on the technical side of this field.


Specializations in Masters in Data Analytics Programs

The subjects and courseware of a different master’s in data analytics are interleaved. But this field also provides several concentrations and specializations. Below we discuss a few masters in data analytics courses with specialization and careers path post-graduation.

Area of FocusDescriptionCareers This Concentration prepares for
Master’s in Predictive Analytics – Specialization in Data Mining and Statistical AnalysisIn this specialized role, students learn about discovering and identifying meaningful structures from data and mapping them all together to produce meaningful information. It allows us to provide exploratory data analysis with predictive models for extracting patterns and trends in data. The professional will then look into the business issues and will interpret them into a data question.
  • Statisticians
  • Data Analysts
  • Business Analysts
Master’s in Data Analytics and Policy –Business Intelligence & Strategy-MakingBusiness Intelligence is a domain where the analyst has to transform data into insights that can help propel a business with maximum potential. This specialized domain allows cultivating back-end data sources with high accuracy and simplicity.
  • BI Engineers
  • Data Strategists
  • BI Analysts
  • BI Developers
MS in Data Analytics and Engineering –Data Engineering and Data WarehousingData engineering is converting data into a meaningful format so professionals can use those data for intense analysis. This data science specialization involves managing the source, arrangement, tone, storing, and retrieving the data for other data analysts and data science professionals.
  • Data Analysts
  • Database Professionals
  • Data Engineers
Master of Professional Studies in Data Analytics and Visualization — Data visualizationThe culture of human civilization is mostly visual, which includes everything from art and advertising to entertainment and learning. Data visualization is the data science specialization domain responsible for representing data and information into a graphical representation. It uses visualization tools like graphs, tables, charts, plots, infographics, and maps. In data visualization, professionals can easily tweak the data to modify the visuals, making data visualization an essential field of data analysis.
  • Data Visualization Engineers
  • Software Developers
  • Data Scientists
Master’s in Data Analytics and Engineering–Database Management and Business Intelligence ConcentrationIn this era of data science and big data – enterprises and organizations need to have centralized data architecture aligned with industry standards. After successfully cleaning or scrubbing, the data is deployed and maintained in databases for complex data transactions supporting applications, services, or groups of services.
  • Database professionals
  • Database Administrators
  • Data Specialists
MBA in Data Analytics –Operations-Related Data AnalyticsOperational-related data analytics directly uses tools and data provided by the other employees and members of the organization. The tools fed with data find possibilities of improvement within the various operations (like logistics, technology, human resources, financials).
  • Planning Analysts
  • Decisions Analysts
Master’s in Applied Data Analytics –Machine Learning and Cognitive SpecialistMachine learning and cognitive algorithm development are some of the top-rated specializations of data science. Through this, aspirants and professionals can develop algorithms and Artificial Intelligence (AI) based solutions. Companies hire ML professionals to build the actual algorithms and models and use industry-standard tools and statistical techniques. A machine learning algorithm can multiply the turnover by smartly reducing the repetitive tasks done earlier by tedious human labor.
  • ML Engineers
  • Data Scientists
  • Researchers
  • AI Specialists
Master’s in Data Analytics –Market ResearchThe marketing data analysts are responsible for measuring, analyzing, and managing marketing performance for effectiveness and optimize return on investment. Marketing data analytics uses tools and techniques like paid search marketing, marketing software products, search engine optimization, etc., and uses those data to leverage the analysis.
  • Product Analysts
  • Market Analysts
  • Web Analysts
Master’s in Data Analytics Cybersecurity and Data AnalysisCompanies hire cybersecurity data analysts to design and implement algorithms using large datasets to detect bugs and vulnerabilities, predict future attacks and threats, and produce useful intelligence for improving the security and privacy of data within that organization. These analyses are responsible for protecting the organization’s resources and plans from external and internal threats and crimes.
  • Cybersecurity Analysts
  • Data Scientists
  • Data Analysts


Curriculum and Skills Gained in Masters in Data Analytics Online Programs

A master’s in data analytics would have common courseware for most of the credits. But some concentrations would vary per the specialization of the course. Below we would discuss a few subjects learned in a master’s in data analytics online program and attained skills.

CurriculumSkills Gained
Data Analytics Fundamentals
  • Applied Business Analytics and Decisions
  • Advanced Big Data Analytics
  • Big Data Management: Tools and Techniques
  • Marketing Research Design and Analysis
  • Managerial Data Analytics
Statistics
  • Managerial Data Analytics
Big Data
  • Business Applications of Database Management Systems
  • Business Intelligence Applications and Tools
  • Big Data Analytics for Business
  • Advanced Predictive Data Analytics for Business
  • Business Applications of Text Mining
Introduction to Probability and Statistics
  • This course aims to provide students with the mathematical fundamentals required for successful quantitative analysis of problems.
Data Analysis and Visualization with R
  • Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis. These topics are explored using the statistical package R, focusing on understanding how to use and interpret output from this software and visualize results. The methodology, including underlying assumptions and the mechanics of how it all works, along with an appropriate interpretation of the results, are discussed in each topic area.
Data Mining
  • Here topics include data preparation, classification, performance evaluation, association rule mining, and clustering. Also, basic data mining algorithms and data mining techniques are thought of using data mining software.


Accreditation for Masters in Data Analytics Online Programs

Accreditation means that an institution has been evaluated by an independent accrediting body and found to meet the high standards of a rigorous education. Thus, accreditation is enforcement of quality. Read more about Accreditation.It is of utmost importance that a student’s degree is recognized by academicians and the industry universally as a certain academic and professional standard. Hence, one must ensure that the institution they are enrolling in has their master’s in data analytics online programs accredited. Also, a college or university must be accredited by one of the federally recognized accreditors for students to be eligible forUS federal student aid.

AACSB Accredited International (AACSB), is one such organization. It is a global non-profit association that connects educators, students, and businesses to achieve a common goal: creating the next generation of great leaders. AACSB typically accredits Data Analytics Programs. Students should check for accreditation by AACSB for their Data Analytics programs.


Timeline for graduation from Masters in Data Analytics Online Programs

Most master’s in data analytics online typically takes anywhere between 16-24 months, while many accelerated master’s programs require just one year of study after students have completed their bachelor’s. In doing an accelerated program, students can save money on tuition. One can refer to such a course here. Typically, for a master’s in data analytics, students need to take 30 – 36 hours of credits.


Masters in Data Analytics Online Programs Admission Requirements

Even though every master’s in data analytics online will have a specific requirement, but generally speaking, a master’s in data analytics online would require a bachelor’s degree majoring in a STEM discipline, GPA of more than 3, and some universities would require qualifying GRE and GMAT scores as well. Some universities might even require experience and employer reference. These are the typical masters in data analytics prerequisites. And for students preparing, OMC has dedicated resources for GRE and GMAT.

Difference between Data Analytics, Data Science and Business Analytics Programs

When some are trying to start a career in a data-related field, students are often confused about the difference between data analytics and data science. Despite the two being interconnected, they provide different results and pursue different approaches. Here we will discuss the differences between them and look at what each delivers. Furthermore, we will also discuss the difference between data analytics and business analytics.

Data analysis involves answering questions generated for better business decision-making. It uses existing information to uncover actionable data. Data analytics focuses on specific areas with specific goals. On the other hand, data science focuses on discovering new questions that you might not have realized needed answering to drive innovation. Unlike data analytics which involves checking a hypothesis, data science tries to build connections, and it shapes the questions to answer them for the future. If we used the analogy of a house, it would be safe to say that, If data science is a home for all the methods and tools, data analytics is a small room in that house. Reflecting on the fact that data analytics is more specific and could be said to be a special and concentrated field of data science.

Data analytics focuses more on viewing the historical data in context, while data science focuses more on machine learning and predictive modeling. Data science is a multi-disciplinary blend that involves algorithm development, data inference, and predictive modeling to solve analytically complex business problems. On the other hand, data analytics involves a few different branches of broader statistics and analysis. If you would feel the need to learn more about data science, you can do it here.

Data Analytics vs. Business Analytics: Understanding the difference

Data analytics involves analyzing datasets to uncover trends and insights used to make informed organizational decisions. Business analytics focuses on analyzing various types of information to make practical, data-driven business decisions and implement changes based on those decisions. Business analytics often uses insights drawn from data analysis to identify problems and find solutions.

While data analysts and business analysts both work with data, the main difference lies in what they do with it. Business analysts use data to help organizations make more effective business decisions. In contrast, data analysts are more interested in gathering and analyzing data to evaluate and make decisions independently.

1-Year Masters in Data Analytics Online Programs

Some experienced hands in the data analytics domain would benefit from a fast-track masters in data analytics online program. But these programs are very rigorous and fast-paced and hence not for someone not well versed with the discipline. These accelerated programs are similar to the 1-year MBA degrees. Here are a few universities that offer 1-year Masters in Data Analytics Online programs:

How to Pay for Masters in Data Analytics Online Programs

According to the latest figures of the Federal Reserve, the average college debt among student loan borrowers is around $32,731, wherein most borrowers have debt between $25,000 and $50,000 outstanding loans. Looking at the data from 2015-16, that is an increase of about 20 percentage points. Keeping in mind the cost of education these days and the amount of debt each student carries, it is important to think about funding masters in data analytics online programs. The smartest way to fund education is a scholarship.

It might happen that someone does not qualify for a scholarship, for such candidates, if they are working professionals, they can check with their employers to reimburse the tuition fee. The other way of funding your master’s in data science is to apply for a student loan. Students can also check if they are eligible for federal student aid. Find out more about FAFSA.


Scholarships for Masters in Data Analytics Online Students

There are many scholarships available in the sphere of a master’s in data analytics online program. A few of them are listed below:

Scholarship

ACM SIGHPC/Intel Computational & Data Science FellowshipThe Association for Computing Machinery’s (ACM) Special Interest Group on High-Performance Computing (SIGHPC) partners with Intel to provide the Computational & Data Science Fellowship worth $15,000 annually to masters or doctoral students researching with big data. Eligible nominees will be females or members of racial minority groups who have completed less than half of their computing degrees at accredited US colleges.

scholarship

Acxiom Corporation Diversity ScholarshipAs a publicly traded marketing analytics firm founded in 1969, Acxiom Corporation proudly began the Diversity Scholarship Initiative to award $5,000 yearly to nine full-time college students majoring in computer science, information systems, data science, statistics, math, information quality, and related fields. Eligibility criteria require attaining at least junior status, belonging to a historically underrepresented group, achieving a minimum 3.0 GPA, and agreeing to internships at Acxiom offices.

scholarship

Bill Caspare Memorial Diversity ScholarshipValued at $10,000, the Bill Caspare Memorial Diversity Scholarship was initiated by The Collective, LLC, in 2015 to nudge undergrads and post-grads into careers for new media, digital advertising, or data science. It’s reserved for diverse applicants who are Black, Asian, Hispanic, Native American, multiracial, or LGBTQ. Students must also be US citizens or green card holders, study full-time, finish 60+ college credits, uphold a minimum 3.25 GPA, and submit three references.

scholarship

CA Technologies Fellowship for WomenAt the University of Vermont, the CA Technologies Fellowship for Women is one of the most lucrative big data scholarships covering full tuition up to $14,670 per semester for outstanding bachelor’s females pursuing the MS in Complex Systems and Data Science. Engagement in CA’s Tech Girls Rock Initiative and the Anita Borg Institute for Women is included. Qualified fellows will be creative thinkers, great communicators, and high achievers with a minimum 3.0 GPA.

Scholarship

Daniel Larose Scholarship for Data Mining ExcellenceNamed for the Department of Mathematical Sciences’ professor, the Daniel Larose Scholarship for Data Mining Excellence confers $4,000 annually, or $2,000 per semester, to post-grads at Central Connecticut State University. They excel in the MS in Data Mining program. Big data lovers must have finished 12+ master’s credits, been graded “B” or better for Stat 520-Stat 527, exhibited strong performance as graduate assistants, and reached a cumulative 3.5 GPA.

FAQs about DATA ANALYTICS Programs

Q: What Is Data Analytics?
A: Data Analytics is the process of cleaning, analyzing, interpreting, and visualizing data to discover valuable insights that drive smarter and more effective business decisions.
Q: What are the three types of data analytics?
A: Three key types of analytics businesses use are descriptive analytics, what has happened in a business; predictive analytics, what could happen; and prescriptive analytics, what should happen.
Q: Is Data Analytics a good career?
A: Skilled data analysts are some of the most sought-after professionals in the world. Because the demand is so strong, and the supply of people who can truly do this job well is so limited, data analysts command huge salaries and excellent perks, even at the entry level.
Q: How to Become a Data Analyst in 2021
A:
  1. Earn a bachelor’s degree in a field with an emphasis on statistical and analytical skills, such as math or computer science. Learn important data analytics skills.
  2. Consider certification.
  3. Get your first entry-level data analyst job.
  4. Earn a master’s degree in data analytics.
Q: Do Data Analyst code?
A: Some data analysts use code in their day-to-day duties, but it’s typically not required or requires only a basic understanding to help clean and normalize a company’s data.
Q: Who can become a data analyst?
A: Expect that you will require at least a bachelor’s degree to become a data analyst, preferably in Information Technology, Computer Science, Mathematics, or Statistics. However, some people become data analysts even with just strong foundational data analytics training.
Q: What is the career path for a data analyst?
A: The career path of a Data Analyst typically starts with an Analyst 1 position and then progresses to Analyst II, Senior Analyst, and then Data Scientist or even Chief Technology Officer.
Q: What does a Data Analyst do?
A: A Data Analyst uses data to help solve business problems, like how to optimize profits, minimize turnovers and streamline logistic processes. Data Analysts look at complex sets of information to reach conclusions, and they may also lead the process of collecting and reporting on new data.

Careers and Salary Outlook for Masters in Data Analytics Graduates

Post a master’s in data science online, one can delve into many roles in the data field. This could vary from a data analyst role at an entry-level to a chief information officer role at the top of the hierarchy. There would be other intermediatory roles in between. Below is a list of roles and salaries with their responsibilities highlighted. 

OccupationMedian Annual Salary (US $)Job Growth (2019-2029)Job Description
Information /Cyber Security Analyst$103,59031%The incumbent assists with setting up machine learning techniques for cybersecurity risk reporting and alerts and helps to alert the university of potential cyber threats.
Market Research/Research Data Analyst$65,81018%Research Data Analyst acquires skills and knowledge of professional concepts in research data analysis, focusing on machine and deep learning.
Product Analyst$111,7562%Product Analysts provide quantitative analysis, market expertise, and a strategic perspective to our partners throughout the organization.
Senior Manager, Data Analytics$116,46515%Data Analysts will work cross-functionally to help users better incorporate data into their daily decision-making. This often will include connecting to and across disparate data sources, building interactive & insightful reports, designing and helping select appropriate ways to capture data, and even helping business users understand best practices in creating KPIs.
Senior AI/Data Analyst$126,83015%
  • Perform analytics to support enterprise-wide research
  • Apply statistics and AI to meet business goals
  • Produce visualizations of data
  • Partner with data engineers to provide applications and advice for internal clients to better understand their data
  • Innovate novel analytics and tools to support research objectives
Equity Research Data Analyst$107,10112%Leads the planning and implementation of program evaluation and equity analysis projects, facilitating, identifying the scope, goals, and deliverables, and providing analysis and reports. Establish data collecting and management procedures that allow for formative and summative assessment of Division of Student Affairs and Success and HSI Initiatives.

Certifications and Licensing for Data Analytics Graduates

Data analysts typically don’t need a certification nor a mandatory license to practice their craft. But organizations put a lot of value to professional certifications while hiring candidates. If one has completed a master’s in data analytics, it would not be a bad idea to pursue one of the certifications relating to their field of work or a graduate certificate in data analytics. A few of such are discussed below:

CertificationDescription
Associate Certified Analytics Professional (aCAP)The Associate Certified Analytics Professional (aCAP) credential is an entry-level analytics certification that shows education in the analytics process though the individual may not have practical experience yet. The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management.
Certification of Professional Achievement in Data SciencesThe Certification of Professional Achievement in Data Sciences is a non-degree program intended to develop a facility with foundational data science skills. The program consists of four courses: Algorithms for Data Science, Probability & Statistics, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization.
 Certified Analytics ProfessionalThe Certified Analytics Professional (CAP) credential is a general analytics certification that certifies end-to-end understanding of the analytics process, from framing business and analytic problems to acquiring data, methodology, model building, deployment, and model lifecycle management. It requires completion of the CAP exam and adherence to the CAP Code of Ethics.
Cloudera Certified Associate (CCA) Data AnalystA SQL developer who earns the CCA Data Analyst certification demonstrates core analyst skills to load, transform and model Hadoop data to define relationships and extract meaningful results from the raw output. It requires passing the CCA Data Analyst Exam (CCA159), a remote-proctored set of eight to 12 performance-based, hands-on tasks on a CDH 5 cluster. Candidates have 120 minutes to implement a technical solution for each task.
IBM Data Science Professional CertificateThe IBM Data Science Professional Certificate is a beginner-level certificate that demonstrates an individual’s skills in data science topics, including open-source tools and libraries, methodologies, Python databases, SQL, data visualization, data analysis, and machine learning. Earning the certificate requires completing nine courses (taking roughly three months at 12 hours per week). The candidate will complete several hands-on assignments and build a portfolio of data science projects.
Data Analyst AssociateThe Data Analyst Associate certification is one of several role-based certifications that replaces the Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics certification that Microsoft will retire in January 2021. This certificate demonstrates subject matter expertise in enabling businesses to leverage their data assets using Microsoft Power BI.
Open Certified Data ScientistThe Open CDS is an independent global certification that qualifies data scientists’ skills, knowledge, and experience. Open CDS requires candidates to demonstrate their skills and experience against a set of conformance requirements through written applications and peer interviews. It does not include training courses, and there are no written exams.

Additional Resources for Data Analytics Professionals

Post a master’s in data analytics online, data analytics professionals can further their careers and keep being relevant in this fast-paced industry by becoming members and hence accrediting themselves with a professional organization in the field of data analytics.  Apart from being a body that assists in developing and distributing knowledge, professional data science associations keep their members informed about the newest developments and innovations. Here are a few of such organizations below:

Professional OrganizationDescription
Association of Data Scientists (ADaSci)Association of Data Scientists (ADaSci) is the leading global professional body of data science and machine learning professionals. Association of Data Scientists (ADaSci) serves the scientific and professional demands of data science among professionals, including scientists, students, educators, analysts, managers, and consultants.
The American Statistical AssociationThe American Statistical Association is the world’s biggest community of statisticians. It is the second oldest, continuously running professional association in the US and was created in Boston in 1839. Its members work in corporate, government, and academia in more than 90 countries, advancing research and developing quality data and statistical work to inform public policy.
The Data Science Council of America (DASCA)The Data Science Council of America (DASCA) is a global independent, third-party association for credentialing Big Data professionals. The Data Science Council of America (DASCA) has a developed platform-independent Data Science knowledge frameworks, standards, and credentials. It certifies people who are starting or working across the range of emerging Data Science professions.
The Institute for Operations Research and the Management SciencesThe Institute for Operations Research and the Management Sciences (INFORMS) is a worldwide society for practitioners in operations research (OR), management science, and analytics and was established in 1995.

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