Senior Big Data Analyst

The SBDA™ certification advances your expertise in modern data analytics. It equips professionals with the skills to manage complex datasets, design dashboards, and deliver insights that drive decision-making. Globally recognized, SBDA™ positions you for senior roles in analytics, business intelligence, and data-driven strategy.

SBDA™

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Overview

The SBDA™ certification provides a globally benchmarked framework for mid-career professionals seeking to expand their analytics capabilities. It emphasizes decision support, automation, and advanced use of tools like SQL, Power BI, and Tableau. Built on vendor-neutral, cross-platform principles, SBDA™ validates your ability to conduct independent analysis, design reporting systems, and communicate insights to stakeholders across business functions.

If you hold a Bachelor’s or Master’s degree in Computer Science, Data Science, Economics, Statistics, Mathematics, Business, Management, Finance, Social Sciences, Computer Applications, Engineering, Applied Sciences, or related disciplines, and have applied experience in analytics roles or business reporting, the SBDA™ credential is your pathway to leadership in analytics and business intelligence.

Go to SBDA™ Candidacy

SBDA™ Certification Program Fee

USD 875.00

(All Inclusive)

The SBDA™ 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 SBDA™ 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 SBDA™ certification exam, access to digital exam preparation resources, and the SBDA™ 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 USD 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 USD 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.

Key Program Highlights

Exam-Preparation Resources

Candidates receive structured, high-quality exam-preparation resources through DataScienceSkool, designed to support flexible and effective self-study.
Structured Timeline

SBDA™ candidates are provided with a 6-month preparation window, with a recommended self-paced schedule of 8–10 hours per week—ideal for working professionals.
Verifiable Credentialing

Successful candidates receive a secure digital badge issued by DASCA, serving as verifiable recognition of their achievement and professional standing.
Global Credibility

SBDA™ is a vendor-neutral and cross-platform credential recognized worldwide, designed to validate real-world capabilities, not product proficiency.
End-to-End Digital Experience

From registration to exam scheduling, all processes are managed digitally via the secure myDASCA dashboard, ensuring transparency and convenience at every stage.
Remote Proctored Exam

Exams are administered online and can be taken from any secure location. Live digital proctoring ensures exam integrity and a seamless test-taking experience.

Need More Details? Download the SBDA™ Brochure

Global Network of SBDA™ Certified Professionals

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.

Edward Olayemi, SBDA™

Team Lead, Insight and Analytics at First Bank, Nigeria

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™.

Kalupahanage Dilini, ABDA™

KPMG

SBDA™ Candidacy

The SBDA™ certification is designed for professionals with some analytics experience who are looking to expand into more advanced decision-support capabilities. It emphasizes automation, stakeholder communication, and use of platforms like Power BI, Tableau, and SQL-based reporting environments. SBDA™ candidates are expected to:

Possess foundational data skills and applied experience with analytics tools.
Be able to independently conduct business analysis, visualization, and reporting.
Understand frameworks for data-driven decision-making, industry KPIs, and AI-assisted analytics tools.

For Bachelor’s Degree Holders
Minimum Qualification Required
A Bachelor's degree in Computer Science, Data Science, Economics, Statistics, Mathematics, Business, Management, Finance, Social Sciences, Computer Applications, Engineering, Applied Sciences, or related fields from a nationally or internationally accredited institution.

Minimum Work Experience
Minimum 2 years of experience working in analytics roles using tools like SQL, Excel, Power BI, or Python.
For Master’s Degree Holders
Minimum Qualification Required
A Master's degree in Computer Science, Data Science, Economics, Statistics, Mathematics, Business, Management, Finance, Social Sciences, Computer Applications, Engineering, Applied Sciences, or related fields from a nationally or internationally accredited institution.

Minimum Work Experience
Minimum 1 year of applied experience in analytics, business reporting, or data visualization.
For Bachelor's Degree Holders from DASCA-Accredited / Recognized Institutions (ExpressTrack™)
Minimum Qualification Required
A Bachelor’s degree in Data Science, Computer Science, Economics, Statistics, Mathematics, Business, Management, Finance, Social Sciences, Computer Applications, Engineering, Applied Sciences, or related fields from DASCA-Accredited/Recognized (ExpressTrack™) institutions.

Minimum Work Experience
Minimum 1 year of applied analytics experience using tools such as Excel, SQL, or Tableau/Power BI.
For Master’s Students and Alumni from DASCA-Accredited/Recognized Institutions (ExpressTrack™)
Minimum Qualification Required
Current or past students of Master’s Degree programs in Data Science, Computer Science, Economics, Statistics, Mathematics, Business, Management, Finance, Social Sciences, Computer Applications, Engineering, Applied Sciences, or related fields from DASCA-Accredited/Recognized (ExpressTrack™) institutions.

Minimum Work Experience
Not mandatory, but familiarity with reporting, dashboarding tools, and analytics scripting (Python) is recommended.

Not sure if you're eligible?

Use the Candidacy Self-Check Tool to find out which DASCA certification best aligns with your education and professional experience.

Need expert guidance? Consult a program advisor today.

Exam-Preparation Resources

Candidates registered in the SBDA™ 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.

* Students of DASCA-accredited institutions are provided with a 365-day exam window.
† Extensions require payment of an administrative fee of USD 100. Read the policies here.

Click here to register for SBDA™

About the SBDA™ Exam

The SBDA™ certification exam is built on the DASCA Essential Knowledge Framework (DASCA-EKF™) — a globally benchmarked standard defining the advanced competencies, methodologies, and tools required of senior data analytics professionals.

The exam assesses readiness across nine key domains, covering business analytics, data manipulation, modeling and visualization, analytics tools and methods, decision-making, automation, industry-specific applications, and generative AI. Each domain reflects the competence of analysts to handle, interpret, and communicate insights from complex datasets effectively.

Designed to validate both conceptual mastery and applied expertise, the exam goes beyond tool-specific knowledge to evaluate an analyst's ability to generate actionable insights, support strategic decision making, and leverage automation and AI for efficiency. Weightings are calibrated to reflect the expanding responsibilities of senior data analysts, from advanced analytics and reporting to practical applications across business and industry contexts.

The SBDA™ exam emphasizes:

Applied understanding of business analytics strategy for actionable, high-impact insights.
Conceptual fluency in data manipulation, modeling, and analytics platforms beyond basic tools.
Effective use of data visualization and storytelling to communicate complex findings.
Practical application of predictive analytics, automation, and generative AI in business contexts.

Examination Coverage Information

Business Analytics Fundamentals
10%

Description & Practical Applications

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.).

Why It Matters

Creates the foundation for understanding how data translates to business value. Analysts 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.
Data Visualization & Storytelling
15%

Description & Practical Applications

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.

Why It Matters

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.
Data Manipulation & SQL/Python
15%

Description & Practical Applications

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.

Why It Matters

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.
Business Analysis Tools & Methods
10%

Description & Practical Applications

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).

Why It Matters

These are the practical analytical techniques and tools analysts use daily across industries. Analysts 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.
Data-Driven Decision Making
15%

Description & Practical Applications

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.

Why It Matters

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.
Analytics Platforms & Data Systems
12%

Description & Practical Applications

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.

Why It Matters

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.
Advanced Analytics & Automation
10%

Description & Practical Applications

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.

Why It Matters

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.
Industry-Specific Analytics
5%

Description & Practical Applications

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.

Why It Matters

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.
Generative AI in Data Analytics
8%

Description & Practical Applications

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.

Why It Matters

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.

Award of the SBDA™ Credential

Earning the SBDA™ credential is a formal recognition of a candidate’s advanced expertise in data analytics and their readiness to analyze, model, and communicate insights from complex, large-scale datasets. Certified professionals receive an official DASCA credential kit, which includes a physical certificate, a commemorative lapel pin, and a verifiable digital badge. Together, these represent the achievement of certification and the credibility, commitment, and analytical proficiency expected of today’s senior data analytics professionals.

How to Showcase your Credential

*The images are for representation only.

Earning the SBDA™ - A Preview of the Certification Journey

There are six key stages in your SBDA™ certification journey. Here's a quick overview of what to expect at each step:

01
Check Your Eligibility

Before you begin your application, it’s important to confirm that you meet the minimum eligibility criteria for the SBDA™ certification. Use the candidacy self-check tool here to evaluate your academic and professional qualifications and ensure alignment with the program’s requirements.
02
Complete Your SBDA™ Registration

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 successfully completing your application, you’ll receive access to your myDASCA dashboard.

Note:
- Use your legal name as per your official government-issued ID.
- Register with a personal email address to avoid missed communications.
03
Study and Prepare

Once registered, you’ll receive access to DASCA’s 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.
04
Schedule Your SBDA™ Exam

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.
05
Certification Award

After passing the SBDA™ exam, your digital badge is issued immediately. Within 3–4 weeks, you’ll also receive your official SBDA™ credential kit, which includes a physical certificate, commemorative lapel pin, and a copy of the DASCA Code of Ethics.

You will also receive guidance on how to use the SBDA™ designation after your name and how to professionally showcase your credential across platforms such as LinkedIn, email signatures, and resumes. The SBDA™ designation signifies your standing as a globally credentialed data analytics professional.
06
Maintain Your Credential

To keep your SBDA™ certification valid, you must renew it periodically before the standard credential renewal deadline. Renewal 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.

Maintain your Credential

Keep Your SBDA™ Current

Your SBDA™ credential is valid for a fixed term and must be renewed periodically to maintain its recognition. DASCA makes it simple to keep your credential active through a quick renewal process designed for senior professionals in data analytics. By renewing, you’ll retain:

Verified Global Credibility with a DASCA-issued digital badge
Ongoing Recognition by employers, peers, and industry leaders
Access to DASCA Updates on emerging tools, frameworks, and best practices

Renew Your SBDA™

Ready to take the next step? Start your SBDA™ certification journey today.

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