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Explore DASCA’s comprehensive certification paths tailored for professionals in:
Validate your expertise in designing, building, and managing Big Data infrastructure.
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Master the tools and techniques for advanced data analysis and insight generation.
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Become an expert in data science methodologies and applications.
SDS™ Brochure PDS™ BrochureChoose your qualification and experience level to find the DASCA certification that aligns with your career goals.
Learn about the steps to earn your DASCA certification, from application to becoming a certified professional.
DASCA certification exams are available online worldwide, accessible in 180+ countries with 5th-generation TEI technology.
Find answers to common questions about DASCA certifications, exam process and policies.
Showcase your DASCA certification with digital badges recognized worldwide.
Discover how DASCA Accreditation enhances data science and AI education, ensuring global recognition and academic excellence.
Understand how DASCA Accreditation sets the benchmark for excellence in data science and AI education, aligning institutions with global industry standards.
Examine the framework that upholds high benchmarks for curriculum, faculty expertise, and industry relevance in data science and AI programs.
Understand the institutional and program-level requirements to assess your readiness for pursuing DASCA Accreditation.
Explore the step-by-step process to achieve DASCA Accreditation through a rigorous, globally benchmarked, and digitally powered evaluation.
Discover how DASCA Accreditation enhances institutional reputation, academic quality, and global competitiveness in data science and AI education.
Access comprehensive guides, support tools, and subsidy programs designed to assist institutions throughout their accreditation journey.
Learn about the global network of academic and industry experts who support institutions in delivering high-quality data science and AI education.
Get answers to common questions about institutional eligibility, the accreditation process, ongoing compliance and more.
Begin your DASCA accreditation journey and position your institution among global leaders in data science and AI education.
The SBDA™ certification is an industry-preferred credential that powers the growth of professional careers in data analytics, business intelligence, and related functions. The SBDA™ certification journey deepens and enriches vendor-neutral and cross-platform skills, knowledge, and capabilities in cutting-edge data science, offering a comprehensive coverage of the latest tools and techniques in big data analytics used across the entire spectrum of client environments, ensuring you are well-prepared for any data challenge.
SBDA™ is the qualification for you if you are currently in roles that involve setting up data analytics operations, conducting research, analysis, and visualization of data, management of information, or overseeing information systems in an organization. To be eligible, you must also have at least a Bachelor’s/ undergraduate degree in Information Systems/ Computer Application/ Business, Management/ Statistics/ Mathematics/ Economics/ Applied Mathematics from a nationally or internationally accredited/ recognized institution.
If you are actively engaged in data analytics, SBDA™ is particularly well-suited to complement your professional pursuits.
Go to SBDA™ CandidacyThe SBDA™ certification program fee is subject to change without notice and does not cover the training fee charged by training companies, universities, or institutions that offer exam preparation training for the SBDA™ exam. DASCA is a standards and credentialing body and is not involved in training delivery, nor does it control any aspect of training/education. DASCA does not govern, mandate, or control the training fee or program fee charged for any certification program by any training company or education provider. Any additional online resources provided by independent publishers in some markets are for optional reference and are not associated with DASCA exams or the official DASCA exam-prep handbooks provided to candidates.
This is a one-time fee covering the SBDA™ certification exam, standard exam preparation resources (Handbook 1: Foundations of Big Data Analytics, Handbook 2: Advanced Big Data Analytics), SBDA™ credential kit, digital badge, and shipping of materials. Additionally, the digital access and hosting cost of third-party optional study resources are included in the SBDA™ fee package wherever applicable. Refund requests made within 24 hours of payment will be subject to a US$ 80 processing fee. No refunds will be issued for registration cancellation requests after 24 hours of registration.
*We honor military and veterans with special fee.
Register NowCandidates are provided high-quality exam-preparation resources for convenient and effective self-study.
Candidates are given 6 months for exam preparation with recommended self-study of 8-10 hrs/week.
Candidates receive an exclusive Digital Badge to showcase and receive recognition for their achievement.
SBDA™ is a globally recognized vendor-neutral and cross-platform certification.
SBDA™ candidates can conveniently register for and schedule their SBDA™ certification exam, and access policy resources and support on their personal and exclusive myDASCA digital dashboard.
Certification exams can be taken in a private, secure location at a convenient schedule, with digital proctoring ensuring continuous security and integrity.
Learn more about SBDA™ by downloading the program brochure.
I have been in the world of analytics for almost a decade now, DASCA curriculum and methodology stands out as the best I have ever come across. I wish I had a DASCA certification training handbook when starting my career as a Data Analyst, I learnt data analytics the hard way since I don't have access to a comprehensive and structured material to guide my learning. I recommend DASCA certification to anyone who wants an easy walk into the space of Big Data Analytics.
I am delighted to say that I have succeeded in achieving the ABDA™ designation after the rigorous training and preparations for the exam. Of course, it was not an easy journey, but it is one of my best decisions to enroll in the program to obtain professional recognition as a big data analyst and also improve my knowledge and skills. At the time I started this program, I had the basic knowledge of ML and big data as a graduate specializing in Statistics. The scope of the study materials for ABDA™ and SBDA™ was a lot beyond that. I had to sharpen my skills and understanding in many areas related to Data Science, and it served me well in my career as a consultant in developing Banking and Finance related business solutions. I really appreciate the rich content of study materials provided for the exam preparations. Stepping from merely passing the exam, they allowed me to get hands-on experience in many practical scenarios that Data Science techniques can be applied to. Finally, I hope this will open many doors in my career, and I am looking forward to achieving the next levels in this path, like SBDA™.
The SBDA™ certification program requires candidates to have a rich general understanding of current information technology trends and information and intelligence use cases in today's industries. Candidates must also understand the influential role that modern data science plays in shaping data analytics applications in everyday life, business, and industry.
The rigor of the SBDA™ program demands that candidates have a strong formal knowledge of advanced statistical techniques and be adept at calculating central tendencies, dispersions and averages, permutations and combinations, and probabilities, as well as creating graphs, charts, histograms, and scatter plots. Candidates must also be comfortable working with databases and spreadsheets. Having a basic knowledge of programming and skills in using spreadsheet programs and statistical software for calculations will be a meaningful plus.
Review the minimum qualifications and work experience required to determine your eligibility for SBDA™:
Should have completed a Bachelor's Degree in Computer Science/ Mathematics/ Statistics/ Engineering/ Applied Sciences/ Economics/ Finance/ Management/ Social Sciences/ Computer Application/ Information Systems or related disciplines from any nationally or internationally accredited institution.
Minimum 2 years of experience in working with data/ Statistics/ Business Analytics/ Business Intelligence/ Computing
Should have completed a Master's Degree in Computer Science/ Mathematics/ Statistics/ Engineering/ Applied Sciences/ Economics/ Finance/ Management/ Social Sciences/ Computer Application/ Information Systems or related disciplines from any nationally or internationally accredited institution.
Minimum 1 year of experience in working with data/ Statistics/ Business Analytics/ Business Intelligence/ Computing
Should have completed a Bachelor's Degree in Computer Science/ Mathematics/ Statistics/ Engineering/ Applied Sciences/ Economics/ Finance/ Management/ Social Sciences/ Computer Application/ Information Systems or related disciplines from any of the DASCA-accredited or DASCA-recognized Institutions.
Minimum 1 year of experience in working with data/ Statistics/ Business Analytics/ Business Intelligence/ Computing
Current & past Students of Master's Degree programs in Computer Science/ Mathematics/ Statistics/ Engineering/ Applied Sciences/ Economics/ Finance/ Management/ Social Sciences/ Computer Application/ Information Systems or related disciplines from any of the DASCA-accredited or DASCA-recognized Institutions.
Experience not Mandatory; basic proficiency in working with data/ Statistics/ Business Analytics/ Business Intelligence/ Computing
Use the Candidacy Self-Check Tool to find out which DASCA certification best aligns with your education and professional experience.
Need expert guidance? Schedule a call with a program advisor.
All SBDA™ candidates are provided with resources to study from and prepare for their SBDA™ certification exam. The access to these resources is activated after the completion of registration and fee payment formalities.
The DASCA official exam preparation resources provided to registered SBDA™ candidates include:
In addition to the above, independent third-party publishers and content providers offer online resources for reference, practice, and learning. Using these resources is optional and not essential for SBDA™ exam preparation, and the DASCA fee package covers the cost of digital LMS access and cloud hosting of such material. Please report any instance or experience in which you were asked to pay separately for any of these study and exam-prep resources or you observed any attempt by a person, store, or entity to sell any of these resources. It is reiterated that these DASCA resources are meant to be provided directly only to individuals formally registered in the SBDA™ certification program, and they are NOT for sale in the open market or available in bookstores anywhere in the world. The images are for representation only.
The two handbooks on Big Data Analytics included in the official DASCA exam preparation kit are the recommended and essential readings for the online SBDA™ certification examination. These handbooks have been developed based on the DASCA Essential Knowledge Framework (DASCA-EKF™) to ensure effective preparation for the SBDA™ certification exam and, at the same time, help Big Data Analysts and application developers build a longer–lasting base of knowledge and a more in-depth perspective of the most advanced concepts in data science that underlie data analytics technologies. In addition to the handbooks, SBDA™ candidates are provided with a candidate guide and practice tests on their myDASCA dashboard.
The content in the two official DASCA handbooks is clustered into eight sections covering all prescribed SBDA™ exam areas and aims to cultivate in learners a strong generic and platform-based understanding of the concepts, tools, and technologies of handling, managing, processing, and visualizing large volumes of streaming data.
Introduces essential business analytics concepts and how they drive organizational decision-making. Covers key analytics terminology, common business metrics (KPIs), types of analysis (descriptive, diagnostic, predictive, prescriptive), and the analytics lifecycle. Includes real-world examples of how analytics solves business problems across departments (marketing, operations, finance, etc.).
Creates the foundation for understanding how data translates to business value. Associates need to understand the "why" behind analytics work and how their analysis connects to business outcomes. This module ensures analysts can speak the language of business and understand stakeholder needs.
Develops skills in creating effective visualizations and communicating insights. Covers dashboard design principles, choosing appropriate chart types, visualization tools (Tableau, Power BI, Excel, Python Matplotlib), presentation techniques, and storytelling frameworks. Emphasizes making data accessible to non-technical audiences and driving action through insights.
Even perfect analysis is worthless if stakeholders can't understand it. This module ensures analysts can translate complex findings into clear, compelling visuals and narratives that influence decision-makers. Visualization is often the most visible and impactful part of an analyst's work.
Focuses on hands-on data preparation using SQL and spreadsheets. Covers writing SQL/Python queries (from basic to advanced), data cleaning techniques, joining and aggregating data, working with date/time data, string manipulation, and creating derived metrics. Includes common SQL patterns for business reporting and analysis.
Data rarely comes in the exact format needed for analysis. This module teaches the everyday skills analysts use to access, clean, and reshape data. SQL remains the most universal language for working with structured data across nearly all business environments.
Provides practical experience with the everyday tools of business analysis. Covers advanced spreadsheet techniques (Excel/Google Sheets formulas, pivot tables, What-If analysis), reporting tools, A/B testing methodology, cohort analysis, funnel analysis, and financial analysis basics (profit margins, ROI calculations, forecasting).
These are the practical analytical techniques and tools analysts use daily across industries. Associates need a strong foundation in these universal methods before moving to more specialized or advanced approaches. These skills deliver immediate value in any business setting.
Explores frameworks for using data to make and influence business decisions. Covers analytical problem framing, hypothesis testing for business questions, statistical significance (in practical terms), analysis planning, stakeholder management, and requirements gathering. Emphasizes critical thinking and avoiding common analytical pitfalls and biases.
Successful analysts don't just provide data—they drive decisions. This module bridges technical skills with business impact by teaching analysts how to frame problems, structure analysis to answer specific questions, and present findings in ways that lead to action.
Provides a practical understanding of the data systems analysts work with. Covers data warehouses like Postgres, MySQL, business intelligence platforms, reporting systems, dashboarding tools, data catalogs, basic ETL concepts, and working with APIs. Focuses on how analysts interact with these systems rather than building them.
Modern analysts need to understand where data lives, how it flows through an organization, and how to access it efficiently. This module ensures analysts can navigate enterprise data ecosystems without needing to be data engineers.
Introduces practical applications of advanced analytics techniques. Covers basics of predictive modeling , segmentation analysis, text analytics, automated reporting, dashboard automation, analytics scripting basics (Python for business use cases), and when to use AI-assisted analytics tools. Focuses on application rather than theory.
As analysts grow, they need efficient ways to handle larger datasets and more complex analysis. This module introduces techniques that extend beyond basic reporting to provide deeper insights and save time through automation, without requiring deep statistical or programming expertise.
Explores how analytics varies across industries with popular use cases. Covers industry-specific metrics and KPIs for sectors like retail (inventory turnover, same-store sales), marketing (CAC, LTV), finance (risk metrics, portfolio analysis), healthcare (patient metrics, operational efficiency), and others.
Different industries have unique analytical challenges and metrics. This module helps analysts understand how to adapt their skills to specific business contexts and speak the language of their particular industry.
Introduces practical applications of generative AI for everyday data analytics tasks. Covers using AI tools to automate reporting, generate data summaries, assist with data cleaning, create synthetic data for testing,. Includes prompt engineering for analytics, evaluating AI outputs, and integrating AI tools with existing analytics processes.
Generative AI is transforming how analysts work by automating routine tasks and providing new capabilities. This module ensures analysts can leverage these powerful tools to increase productivity, generate new insights, and solve problems that were previously impractical to address with traditional methods.
After passing the SBDA™ certification exam, candidates will receive a credential case containing a physical certificate, a lapel pin, and a digital badge. These physical and digital representations of their achievement serve as a testament to their expertise and dedication in the field of data science and analytics.
How to Showcase your Credential
*The images are for representation only.
There are six distinct stages of your SBDA™ certification journey. Here’s a quick tour of what these stages look like. You may Contact Us for more information.
Before you begin your application, it is important to confirm your eligibility. Start by checking your candidacy here, to ensure that you meet the minimum eligibility requirements for the SBDA™ certification program.
Once you've confirmed your eligibility, the next step in starting the application process is to create your myDASCA account. This account will give you access to an easy online application process. You will need to fill out a form with accurate and complete details about your educational qualifications and work experience. After successfully submitting the online SBDA™ application form and paying the fee, you will receive a registration confirmation email and access to your myDASCA dashboard.
Note:
After you have successfully completed the SBDA™ registration process, the logistics team will contact you via your registered email address to confirm your shipping information. You must ensure and confirm that the shipping address is accurate. If any changes are needed, you should make them within 24 hours of completing your registration. You will receive the DASCA Exam Preparation Kit, which includes two Big Data Analytics handbooks for essential reading, within the standard delivery timeframe of 3-4 weeks.
Once you are ready to take the SBDA™ certification exam, you can easily schedule it online through your myDASCA dashboard. DASCA provides 180 days from the registration completion date for the candidates to study, prepare for, and take their exams. It is strongly recommended that you thoroughly familiarize yourself with the exam policies prior to scheduling the exam.
Read more about the exam scheduling policy here.
After passing the SBDA™ certification exam and meeting other conditions defined by the DASCA Professional Certifications Board (DPCB), the results are published within 10-12 business days of taking and successfully completing the exam.
Once the results are published, the Digital Badge will be made immediately available to you. You can expect to receive the SBDA™ credential kit, which includes a printed SBDA™ certificate, lapel pin, and the DASCA code of ethics booklet, within 3-4 weeks from the date of the award. You will also receive an email containing details of your digital badge, allowing you to showcase your achievement on social platforms. After receiving your award, you will be able to use the designation after your name.
Maintaining your SBDA™ certification by renewing is mandatory to ensure that it remains valid and up to date. It's best to renew your credential before the Standard Credential Renewal deadline, as this shows your continuing competence and dedication to the profession.
DASCA will send you reminder emails to renew your credential. You can easily renew by logging into your myDASCA account. Please ensure that your registered email address is current to receive all communications from DASCA.
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