NSCC Instructor · Halifax, NS

Patrick Scott
Dolinger

Data Obsessed Coder — teaching the next generation of Business Intelligence & Analytics professionals at the Nova Scotia Community College.

🎓 M.Ed. — University of North Texas
💼 Cognos · Microsoft · IBM
📅 Analytics since 2000
🗄️ Lifelong Learner
Skills I Teach BI & Analytics Course Site →
25+
Years working in the analytics & BI industry
6
Core skills taught in the certificate program
2
Graduate degrees in Education
BI & Analytics
1-Year Graduate Certificate — NSCC
Curriculum

Skills I Teach

The six core competencies that form the foundation of a career in Business Intelligence and Analytics. Click any card to read more.

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Structured Query Language (SQL)

The essential language for querying, managing, and transforming data in relational databases.

SQL language skills are the basic building blocks to perform a variety of data analytics and data science tasks. The SQL language gives the analyst the power to convert data into information. SQL is used for the creation of databases, the reading of data, and management of relational database systems.

Mastering SQL is a primary skill for the data analyst — and one that remains in demand regardless of which other tools or languages come and go.
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Reporting and Analysis

Turning raw data into the dashboards, scorecards, and reports that drive business decisions.

Reporting and analysis are the words you will often see on job postings. Businesses continue to invest in this capability because it affords them visibility into the health of their operations and allows them to mitigate risk when making go-forward decisions.

As data volumes grow, demand for skilled report authors and analysts will continue to grow as well.
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Inferential Statistics

The science of drawing conclusions from data — a skill that sets confident analysts apart.

Inferential statistics is a discipline every analyst can benefit from mastering. The more confident an analyst is in their statistical skills, the more confident they will be in presenting findings to business leaders.

A solid grounding in inferential statistics enables a deeper understanding of both traditional analytics and the statistical learning models used in data science.
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ETL — Extract, Transform, Load

Moving and shaping data from source systems into environments optimized for reporting.

Extraction, Transformation, and Loading (ETL) is the process of moving data from transactional data stores into optimized environments for reporting and analysis. Although often viewed as a tactical administrative process, knowledge of proper data modeling significantly increases the value an ETL practitioner brings to a project.
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Data Modeling

The architectural foundation that determines the success of every reporting and analytics project.

Successful reporting, analysis, and data science projects often credit the state of the data model for their success. Conversely, projects that face challenges and delays often trace their issues back to a poor data model.

The Kimball and Inmon warehouse strategies are well-established, and modern tools allow for easy implementation of good practices aligned to either methodology — or a hybrid approach.
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Programming in Python & R

Extending analytical skills into predictive analytics, machine learning, and data science.

Advanced analysts often extend their skills into the predictive analytics space — commonly referred to as "Data Science." Statistical and machine learning can be accomplished with the aid of powerful libraries within Python and R.

Python has taken the lead in industry demand due to advancements in libraries that make machine learning more accessible. The recommendation: learn Python deeply, then learn R syntax as needed. The concepts transfer; the syntax is the easy part.
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Background

About Me

I have had the opportunity to work for some of the greatest technology companies in the industry. I will always owe a debt of gratitude for the opportunities at Cognos, Microsoft, and IBM. I began working in the analytics space in the summer of 2000 after a short career as a systems developer, and have been passionate about working with data ever since.

It is the field I want to teach — to develop new analysts who will carry this same passion forward in their careers. Analytics skills are in high demand, driven by the sheer volume of business data being collected. Trained analysts are required to unleash the information within that data, and that demand shows no sign of dampening.

Education was my first passion. Holding Bachelor's and Master's Degrees in Education from the University of North Texas, being able to pursue both passions at this point in my career is genuinely rewarding. It is great to see students find success in the field.

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M.Ed. & B.Ed. — University of North Texas
Bachelor's and Master's Degrees in Education
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Industry Experience — Cognos, Microsoft, IBM
Analytics and BI practitioner since 2000
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NSCC — Nova Scotia Community College
Instructor, BI & Analytics Graduate Certificate Program
Course Resource

Business Intelligence & Analytics

A comprehensive introduction to the BI & Analytics landscape — concepts, tools, skills, career paths, and curated learning resources for new students.

Visit the Course Site →
Covers: All-Time Horizons · Data Science Pillars · Technologies (Power BI, SQL Server, Python) · Analytical Skills · Career Guidance
Get in Touch

Contact Me

Whether you're a prospective student, a colleague, or someone interested in the BI & Analytics program — I'd love to hear from you.

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Email
patrick.dolinger@nscc.ca
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LinkedIn
Connect with me
📖
Course Site
BI & Analytics Resource