ABDA™ is the most widely industry-trusted proof of proficiency, potential, and promise of using vendor-neutral and cross-platform data science tools and techniques in big data analytics. It is ideal for professionals currently handling roles and functions in MIS, market research, and related areas. ABDA™ is also suitable for students graduating with majors in Information Systems, Computer Application, Business, Management, Marketing, Statistics, Mathematics, Economics, or Applied Mathematics from a B-school/ Institution accredited or recognized by DASCA.
ABDA™ would be a great choice for you if you love crunching numbers and are currently in a role that involves data research and analysis, information management, or managing information systems in an organization.
Go to ABDA™ CandidacyThe ABDA™ certification program fee is subject to change without notice and does not cover any training fees charged by third-party providers, including training companies, universities, or institutions offering preparation for the ABDA™ exam. As a standards and credentialing body, DASCA is not involved in training delivery and has no role in setting or governing external training fees. Any additional resources from independent publishers in some markets are optional and not associated with DASCA exams or the digital exam-preparation resources provided via DataScienceSkool.
This is a one-time fee covering the ABDA™ certification exam, access to digital exam preparation resources, and the ABDA™ credential kit (physical certificate, commemorative lapel pin, and DASCA Code of Ethics booklet), along with a digital badge. The fee also includes shipping of the credential kit. Refund requests made within 24 hours of payment are subject to a US$80 processing fee. No refunds will be issued for cancellations made after 24 hours of registration.
Candidates may extend their exam window by paying an administrative fee of US$100 through their myDASCA dashboard. This extension includes continued access to digital preparation resources and an additional exam attempt.
*We honor military and veterans with a special fee.
Register NowCandidates receive structured, high-quality exam-preparation resources through DataScienceSkool, designed to support flexible and effective self-study.
ABDA™ candidates are allotted a 6-month preparation window, with a recommended self-paced schedule of 8–10 hours per week—ideal for working professionals.
Successful candidates receive a secure digital badge issued by DASCA, serving as verifiable recognition of their achievement and professional standing.
ABDA™ is a vendor-neutral and cross-platform credential recognized worldwide, designed to validate real-world capabilities, not product proficiency.
From registration to exam scheduling, all processes are managed digitally via the secure myDASCA dashboard, ensuring transparency and convenience at every stage.
Exams are delivered online and can be taken from any secure location. Live digital proctoring ensures exam integrity and a seamless test-taking experience.
Learn more about ABDA™ by downloading the program brochure.
The ABDA™ 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 ABDA™ 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 ABDA™:
Should have completed at least a Bachelor's Degree in Computer Science/ Mathematics/ Statistics/ Engineering/ Applied Sciences/ Economics/ Finance/ Management/ Social Sciences/ Information Systems/ Computer Application or related disciplines from any nationally or internationally accredited institution.
Experience not Mandatory; basic proficiency in working with data/ Statistics/ Business Analytics
Should have completed an Associate Degree/ Diploma in Computer Science/ Mathematics/ Statistics/ Engineering/ Applied Sciences/ Economics/ Finance/ Management/ Social Sciences/ Information Systems/ Computer Application/ related disciplines from any nationally or internationally accredited institution.
Minimum 2 years of experience in information systems/ Statistics/ Business Analytics/ Business Intelligence
Current & past students of Bachelor's Degree programs in Computer Science/ Mathematics/ Statistics/ Engineering/ Applied Sciences/ Economics/ Finance/ Management/ Social Sciences/ Information Systems/ Computer Application or related disciplines from any of the DASCA-accredited or recognized Institutions.
Experience not Mandatory; basic proficiency in working with data/ Statistics/ Business Analytics
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.
Candidates registered in the ABDA™ certification program receive structured access to digital exam-preparation resources through DataScienceSkool. These include all required module-based study guides and reading materials, practice questions, and coding exercise environments.
Learning access is synchronized with the 180-day exam window granted to all candidates, ensuring uninterrupted preparation time. Where needed, candidates may extend this window by an additional 180 days. The extension* includes continued access to preparation resources and an exam attempt.
To reinforce readiness and final-stage preparation, timed practice tests are available via the candidate’s myDASCA dashboard. Candidates also gain access to a full-length mock exam 24 hours before their scheduled exam, helping them prepare effectively for exam day. Together, these resources enable focused, self-paced learning aligned with the certification exam.
*An administrative fee applies for the extension. Details available here.
Click here to register for ABDA™The ABDA™ certification exam is built on the DASCA Essential Knowledge Framework (DASCA-EKF™) — a globally benchmarked standard defining the foundational competencies, methodologies, and tools required of entry-level data analytics professionals.
The exam assesses readiness across nine key domains, covering business fundamentals, data manipulation and visualization, analytics tools and methods, decision-making, automation, industry-specific applications, and generative AI. Each domain reflects analysts ability to handle, interpret, and communicate insights from large scale datasets effectively.
Designed to validate both conceptual understanding and applied skills, the exam goes beyond tool-specific knowledge to evaluate an analysts ability to generate actionable insights, support decision making, and leverage automation and AI for efficiency. Weightings are calibrated to reflect the evolving responsibilities of a data analyst, from core analytics and reporting to practical applications across business and industry contexts.
The ABDA™ Exam Emphasizes:
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.
Earning the ABDA™ credential is a formal recognition of a candidate’s proven skills in data analytics and their readiness to analyze, interpret, and communicate insights from large-scale datasets. Certified professionals receive an official DASCA credential kit, which includes a personalized certificate, a commemorative lapel pin, and a verifiable digital badge. Together, these artifacts represent the achievement of certification and the credibility, commitment, and analytical proficiency expected of today’s data analytics professionals.
How to Showcase your Credential*The images are for representation only.
There are six key stages in your ABDA™ certification journey. Here's a quick overview of what to expect at each step:
Before you begin your application, it’s important to confirm that you meet the minimum eligibility criteria for the ABDA™ certification. Use the candidacy self-check tool [here] to evaluate your academic and professional qualifications and ensure alignment with the program’s requirements.
Once you’ve confirmed eligibility, you’ll create your myDASCA account to begin the application process. You'll be required to submit academic and professional background details and pay the applicable program fee. After your application is accepted, you’ll receive access credentials and your 180-day exam window will begin.
Note:
Once registered, you’ll receive access to DASCA’s official exam-preparation resources via DataScienceSkool. These digital materials include structured reading content, module-wise practice questions, and a full-length mock exam to help you prepare effectively and confidently.
When ready, you can schedule your exam online via your myDASCA dashboard. You’ll have up to 180 days from the date of registration to complete your exam. We recommend reviewing the exam scheduling policies before locking in your date.
After passing the ABDA™ exam, your digital badge is issued immediately. Within 3–4 weeks, you’ll also receive your official ABDA™ credential kit, which includes a printed certificate, lapel pin, and a copy of the DASCA Code of Ethics.
You will also receive guidance on how to use the ABDA™ designation after your name and how to professionally showcase your credential across platforms such as LinkedIn, email signatures, and resumes. The ABDA™ designation signifies your standing as a globally credentialed data analytics professional.
To keep your ABDA™ certification valid, you must renew it periodically or upgrade to SBDA™ before the standard credential renewal deadline. These options are available directly through your myDASCA dashboard.
Your dashboard provides visibility into your renewal timeline, so it’s important to remain mindful of key dates and plan your renewal or upgrade well in advance. DASCA will also send email reminders, but keeping your contact information updated and monitoring your dashboard ensures uninterrupted credential validity and continued recognition.
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