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BERKELEY SCHOOL OF BUSINESS, ARTS & SCIENCES

Certified Data Analyst

The Certified Data Analyst certification equips learners with essential skills in data interpretation, visualization, and analytics to drive strategic business outcomes. It prepares professionals to use tools like SQL, Excel, and Python for impactful decision-making.

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Overview

The Certified Data Analyst credential empowers professionals to extract actionable insights from data using tools like SQL, Excel, Python, and BI platforms. It builds a foundation in statistical methods, data visualization, and predictive analytics. This certification is ideal for those aiming to support strategic decision-making across industries. Graduates are equipped to thrive in data-driven roles with analytical precision and business acumen.

Offered By

Berkeley School of Business Arts & Sciences
 

What is the Eligibility?

Typically, there are no specific prerequisites for this certification. It is suitable for individuals interested in Certified Data Analyst, regardless of their background

Who can do?
anyone who is interested to learn about following concepts can pursue Certified Data Analyst:
Data cleaning techniques, Statistical analysis basics, Data visualization tools, Business intelligence concepts, SQL for data querying, Python for data analysis, Dashboard creation in Power BI, Real-world data projects.
individuals with the following designations:
After earning the Certified Data Analyst credential, individuals can pursue roles such as Junior Data Analyst, Business Intelligence Analyst, Data Specialist, Reporting Analyst, and eventually move into senior roles like Data Scientist or Analytics Manager. This certification lays the groundwork for career mobility across sectors such as finance, healthcare, marketing, and tech..

Course structure

Module 1: Foundations of Data Analytics

This module introduces the fundamentals of data analysis, including types of data, analytical thinking, and the role of data in business decision-making. Learners gain a solid grounding in the analytics lifecycle and data-driven strategies.

Module 2: Data Management and Cleaning

Focuses on preparing data for analysis through techniques like data cleaning, normalization, and transformation using Excel and SQL. Students learn to ensure data accuracy and consistency for meaningful analysis.

Module 3: Statistical Analysis and Interpretation

Covers descriptive and inferential statistics, data sampling, and hypothesis testing. Learners use statistical methods to extract insights, detect trends, and support business conclusions.

Module 4: Tools for Data Analysis – Excel, SQL, and Python

Students develop technical proficiency in Excel functions, SQL queries, and Python libraries such as Pandas and NumPy. This module emphasizes hands-on projects and real-world application of tools.

Module 5: Data Visualization and Business Intelligence

Explores dashboard design, storytelling with data, and tools like Tableau and Power BI. Learners apply techniques to present analytical results clearly and effectively for stakeholders.

Lecture plan

Module 1: Foundations of Data Analytics (3Hours)

Module 1: Foundations of Data Analytics (3Hours)

Module 2: Data Management and Cleaning (3Hours)

Module 2: Data Management and Cleaning (3Hours)

Module 3: Statistical Analysis and Interpretation (3Hours)

Module 3: Statistical Analysis and Interpretation (3Hours)

Module 4: Tools for Data Analysis – Excel, SQL, and Python (3Hours)

Module 4: Tools for Data Analysis – Excel, SQL, and Python (3Hours)

Module 5: Data Visualization and Business Intelligence (3Hours)

Module 5: Data Visualization and Business Intelligence (3Hours)

Learning Methodology

Berkeley offers expertly developed learning materials tailored to meet participants' needs, ensuring comprehensive coverage of the syllabus and optimal exam preparation.

‣ Tailored Material: Guides are designed to cover the entire syllabus, offering full preparation and deep understanding.

‣ In-Depth Content: Unlike superficial outlines, our materials provide fully developed theories and concepts, equipping participants with complete knowledge.

‣ Strategic Study: We help participants prioritize study time by indicating the weight of each topic, allowing efficient focus on crucial areas.

‣ Difficulty Levels: Topics are labeled as "Awareness" or "Proficiency," guiding participants to allocate time based on the required depth of knowledge.

‣ Comprehensive Coverage: Our materials include detailed theory and a glossary of technical terms to clarify complex concepts.

‣ Effective Learning Techniques: Visual aids and memorization techniques ensure long-lasting retention, helping candidates succeed.

Berkeley’s methodologies equip participants with the essential knowledge and tools for both exams and future success.

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Lectures

Our lecture plan integrates structured learning with interactive teaching methods, promoting engagement and collaboration. This approach ensures a comprehensive understanding of concepts, fostering critical thinking and practical application in real-world scenarios.

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Practice Session

Practice sessions offer hands-on experience through guided exercises, enhancing skills and reinforcing knowledge. This practical approach ensures mastery of concepts, promoting.

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Mock Examination

Mock examinations simulate real test conditions, providing valuable practice and assessment. This helps identify strengths and weaknesses, ensuring thorough preparation and boosting confidence for actual exams.

berkeley's performance standards

Evaluates and ensure the quality of the training program and all its deliverables.  This is measured through the following indicators:
‣ Instructors' experience and style in presenting and explaining topics.
‣ Variety and balance of teaching methods (such as discussions, case studies, mock exams and videos) used in the course to ensure retention and to match the learning objectives.
‣ Level of interactivity.
‣ Feedback from program participants
‣ Full compliance with Institute standards and guidelines for preparation and study requirements and methodology.
‣ Progress reports from the training program provider.

Success Stories

“As a strong advocate for education and human development, I commend Berkeley for its exceptional commitment to empowering future leaders. The institution stands as a symbol of excellence, innovation, and opportunity. Students who walk its halls are nurtured with knowledge, values, and vision—qualities that contribute to building a stronger and more prosperous future for our nation.”- H.H. Shaikh Khalifa Al Hamid

Visit our Alumni

Alumni Benefits

‣ Exclusive Networking Events: Access invitations to industry-leading events and thought-leadership gatherings featuring renowned speakers.


‣ Monthly Updates: Stay informed with a newsletter highlighting the latest research, events, and activities from the school.


‣ LinkedIn Community Access: Join the Executive Education LinkedIn group for networking and professional development opportunities.


‣ Educational Discounts: Enjoy a 20% discount on open-enrollment programs and access to workshops focused on emerging trends.


‣ Global Alumni Network: Connect with a diverse alumni community through the Berkeley School’s online network and engage in country and interest groups.

Is It Worth the Investment?

UK: £35,000 – £60,000

USA: $60,000 – $95,000

UAE: AED 120,000 – AED 240,000

Canada: CAD 55,000 – CAD 85,000

KSA: SAR 90,000 – SAR 160,000

Salaries vary based on experience, industry, and location. Certified Data Analysts are in high demand, and compensation reflects their technical expertise and business impact.

What You Earn

You will get a certificate of completion, which is highly reputed and accepted by employers

Fundamental Knowledge

Builds core competencies in data processing and analysis.

Technical Skills

Strong focus on tools like SQL, Python, Power BI, and Excel.

Industry Relevance

Highly sought-after in tech, finance, healthcare, and marketing industries.

Career Advancement

Opens pathways to senior analytics and data science roles.

Future Trends

Aligned with AI, machine learning, and big data trends.

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FAQ: Certified Data Analyst

contact us for more information or to apply for admission. Seats fill up quickly, so we encourage early registration!

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