Cloud-Native Analytics with Databricks/Snowflake Training Course

Cloud-Native Analytics with Databricks/Snowflake Training Course

Introduction

In today's data-driven landscape, organizations are increasingly tasked with analyzing complex and sensitive datasets—ranging from healthcare to financial and behavioral data—without compromising privacy, ethics, or compliance. Cloud-Native Analytics with Databricks/Snowflake Training Course equip data professionals, researchers, and analysts with the tools, methodologies, and governance frameworks necessary to safely and effectively process sensitive data using cloud-native platforms. Learners will explore scalable pipelines, zero-copy data sharing, differential privacy, and automated governance on Databricks and Snowflake—two of the most powerful data cloud platforms today.

By focusing on real-world case studies in sensitive domains such as public health, criminal justice, and social behavior, this program ensures participants gain both practical and ethical competencies. This course leverages cloud-native analytics, data lakehouse architectures, Delta Lake, Snowpark, and Apache Spark to facilitate advanced research workflows. Participants will gain hands-on experience with secure data pipelines, privacy-preserving analytics, and compliance-driven data operations, making them industry-ready for handling regulated and ethically complex data environments.

Course Objectives

1. Understand the fundamentals of cloud-native analytics for sensitive research.
2. Learn secure data ingestion pipelines using Apache Spark and Delta Lake.
3. Deploy governance and compliance protocols with built-in controls on Databricks/Snowflake.
4. Implement privacy-preserving machine learning techniques.
5. Utilize Snowpark and Python APIs for secure data transformation.
6. Integrate real-time analytics with auto-scaling compute engines.
7. Leverage data lakehouse architecture for ethical research.
8. Automate sensitive data masking and anonymization workflows.
9. Apply data sharing and collaboration within legal frameworks using Snowflake’s Secure Data Sharing.
10. Perform high-performance querying on sensitive datasets.
11. Build reproducible pipelines with CI/CD for data science in sensitive domains.
12. Evaluate case-specific ethical considerations in AI/ML applications.
13. Establish a multi-cloud strategy for sensitive data processing.

Target Audience

1. Data Scientists
2. Policy Analysts
3. Data Engineers
4. Public Health Researchers
5. Compliance Officers
6. AI/ML Practitioners
7. Academic Researchers
8. Cloud Architects

Course Duration: 5 days

Course Modules

Module 1: Introduction to Sensitive Data and Cloud-Native Platforms

• Define sensitive topics and ethical frameworks
• Overview of Databricks and Snowflake for research
• Legal, regulatory, and ethical considerations (HIPAA, GDPR, etc.)
• Data classification strategies
• Real-world use cases and impact of sensitive data research
• Case Study: Analyzing public health data during a pandemic

Module 2: Data Ingestion & Secure Storage in Databricks

• Connecting sensitive data sources securely
• Data ingestion pipelines with Delta Live Tables
• Schema enforcement and evolution
• Row- and column-level security implementation
• Best practices in cloud storage for regulated data
• Case Study: Ingesting justice system records for recidivism studies

Module 3: Data Sharing & Collaboration with Snowflake

• Secure Data Sharing architecture in Snowflake
• Role-based access controls (RBAC)
• Reader accounts for cross-institution collaboration
• Audit trails and data activity monitoring
• Compliance-friendly collaboration templates
• Case Study: Cross-border research in human rights data

Module 4: Privacy-Preserving Analytics & Anonymization

• Anonymization vs. pseudonymization
• Techniques: k-anonymity, differential privacy
• Tokenization, masking, and encryption
• Generating synthetic datasets for training
• Evaluating re-identification risks
• Case Study: Behavioral analysis in sensitive LGBTQ+ studies

Module 5: Real-Time Data Processing with Apache Spark

• Real-time stream processing concepts
• Apache Spark Structured Streaming
• Optimizing throughput for high-volume sensitive data
• Handling latency in privacy-preserving environments
• Secure checkpointing and recovery
• Case Study: Real-time surveillance for infectious diseases

Module 6: Snowpark for Python & ML on Sensitive Data

• Introduction to Snowpark APIs
• Secure in-database processing with Python
• Building ML workflows in Snowflake
• Version control and reproducibility in ML
• Guardrails for bias detection and fairness
• Case Study: Predictive modeling in financial fraud detection

Module 7: Governance & Compliance Automation

• Data stewardship frameworks
• Automated data audits and compliance logs
• Tagging sensitive fields with Snowflake/Unity Catalog
• Governance dashboards and monitoring
• Integrating compliance tools (Alation, Collibra)
• Case Study: Automating audit workflows in healthcare analytics

Module 8: Multi-Cloud Strategy & CI/CD for Sensitive Data

• Architecting for AWS, Azure, GCP compatibility
• CI/CD pipelines for data engineering in sensitive workflows
• Managing secrets and keys in multi-cloud environments
• Containerized deployment with Docker/Kubernetes
• Hybrid deployment use-cases and pitfalls
• Case Study: Multi-region analysis of educational outcomes

Training Methodology

• Interactive instructor-led sessions (live or virtual)
• Hands-on labs with Databricks and Snowflake environments
• Use of real-world anonymized datasets for simulations
• Group assignments to design ethical research workflows
• Quizzes and evaluations based on use-case implementation
• Capstone project using sensitive data best practices

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.