🏄‍♂️ Dmitry Anoshin

Surfalytics

Surfalytics = Surfing + Analytics. Inspired by West Coast surfing spots and Pacific ocean vibes. Created with goal to help you start a new career in data analytics space, develop data engineering and analytics skills through coaching. It will teach you not just dry skills, but will keep your focus to deliver significant value to businesses in the analytics realm as well as help to get fair compensation for the work you're passionate about.

There are several key producs:

1. Membership in a community with the goal of landing the job, preparing for the interview and getting the best offer. Every month, we do a Data Engineering and Analytics project and discuss our progress on the journey.

2. Community support to
2.1. Land 1st job in data
2.2. Move from analyst to engineer
2.3. Promote from middle to senior and beyond

3. Free course based on my 14 years of experience in Data Engineering and Data Analytics

Data Engineering and Analytics Mentor

University of Victoria

Instructor | Cloud Computing, Analytics and Data Engineering

Rock Your Data

- Data Team building and solving bottlenecks in team delivery
- Building Data Engineering Solutions with Modern Data Stack
- Data Infrastructure and Data Ops (DevOps)
- Data Security and Compliance

Advisory Board Member

Microsoft

- Building Delta Lake on top Databricks and Azure for Microsoft Gaming
- Structured Streaming
- Self-Service BI

Data Engineering & ML

Amazon

- Designed and Implemented Cloud Data Platform for Alexa Quality Metrics
- Designed and Implemented ML platform into production for Customer Perception, Onsite Experience and Churn
- Analytics Modernization with AWS
- Data privacy and Security
- Tracked and Optimized solution cost

Locations: Vancouver, Cambridge, Seattle

Communities:
- Lead Amazon Tableau User Group with 2k+ users.
- Lead Amazon BI Tech Talk community with 100+ BI teams globally.

Packt

•	Author of "Azure Data Factory Cookbook" - Build and manage ETL and ELT pipelines with Microsoft Azure's serverless data integration service. Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data Factory.
•	Author of "Tableau Desktop Certified Associate: Exam Guide" - This book helps to develop your Tableau skills and prepare for Tableau certification with tips from industry experts.

•	Author of "Tableau Cookbook 2019.x" - This book has over 600 pages and includes over 115 recipes that help you to master Tableau Desktop, Prep, and Server.
•	Author of "Mastering Business Intelligence with Microstrategy" - This book is intended to master the craft of Business Intelligence using the best BI platform and discover the full potential of Microstrategy 10 in order to increase performance and improve the user experience.

•	Author of "SAP Lumira Essentials" - Learn data discovery techniques, build amazing visualizations, create fantastic stories and share these visualizations through an electronic medium with one of the most powerful tools – SAP Lumira. 

•	Author of "Learning Hunk"​ - Explore, analyze and visualize Big Data in Hadoop or NoSQL data stores with powerful full-featured big data analytics platform Hunk. 

•	Reviewer of "Learning Tableau 2019"​
•	Reviewer of "Mastering Tableau 2019.1"​
•	Reviewer of "SAP BusinessObjects Reporting Cookbook"​
•	Reviewer of "Creating Universes with SAP Business Objects"​
•	Reviewer of "Learning SAP Business Objects Dashboards"
•	Reviewer of "Splunk 7 Essentials 3rd Edition"

Author & Technical Reviewer

Apress

Jumpstart Snowflake A Step-by-Step Guide to Modern Cloud Analytics. This book is about modern analytics in cloud data warehouse age. It covers cloud analytics fundamentals and highlights modern analytics requirements. The book helps you to start with Snowflake and explore unique features and architecture. and learn more about the modern analytics ecosystem. You will review the analytics solution architectures and migration/modernization scenarios.

Author

Wawanesa Insurance

Toolbox: Tableau, Microstrategy, Oracle, Erwin Data Modeller, Informatica PowerCenter

Data Engineering & BI

Forex Club

DI toolbox: Tableau, Amazon Redshift, Postgresql, Pentaho DI, Tealium, DMP, Klipfolio, Adobe SiteCatalyst, Google Analytics, Adjust

Data Engineer

Teradata

• Delivered technical concepts, designed & developed of BI/ETL/DWH, Splunk, Web Analytics, Campaign Management, Data Science, BigData Analytics
• Designed and Implemented BI architecture and developed the full life cycle of the Business Intelligence part of the corporate BI solution for 1,000+ end users

Data Engineering Leader with 14 years of experience working in Business Intelligence, Data Warehouse & Data Integration, BigData, Cloud, and ML space across North America and Europe.

Leading Data Engineering initiatives, working on a petabyte size data platform built using cloud and big data technologies for supporting machine learning experiments, data science models, business intelligence reporting, and data exchange with internal and external partners. Handling privacy compliance and security-critical data sets.

Apart from work, I am teaching a Cloud Computing course at the University of Victoria, mentoring high school students at CS faculty, and volunteering my time for coaching people with analytics engineering skills in the CIS region. Moreover, I am the author of analytics books and speaker at data related conferences and user groups.

Data Engineering and Analytics Chief Instructor

Surfalytics = Surfing + Analytics. Inspired by West Coast surfing spots and Pacific ocean vibes. Created with goal to help you start a new career in data analytics space, develop data engineering and analytics skills through coaching. It will teach you not just dry skills, but will keep your focus to deliver significant value to businesses in the analytics realm as well as help to get fair compensation for the work you're passionate about.

There are several key producs:

1. Membership in community with the goal to land the job, prepare for the interview and get best offer. Every Saturday we do a Data Engineering and Analytics projects and discuss our progress on the journey.

2. Career consultations from Dmitry with focus on
2.1. Land 1st job in data
2.2. Move from analyst to engineer
2.3. Promote from middle to senior and beyond

3. Free course based on my 14 years experience in Data Engineering and Data Analytics

🚀 Apache Spark 4.1 is Here!

The latest Spark release focused on faster streaming, smarter pipelines, and enhanced PySpark! Here are the highlights:

Key Features ⚡

🧰 Spark Declarative Pipelines (SDP)
⚙️ Define what you want, let Spark handle the how. No more manual dependency management, parallelism, or retry logic. Write in Python or SQL and let the framework do the heavy lifting.

🚄 Real-Time Mode for Structured Streaming
⚙️ Sub-second latency is now official! Achieve single-digit millisecond p99  ⚙️ latency for stateless queries. Just flip a config—no code rewrite needed.

🐍PySpark Improvements 
⚙️ Arrow-native UDFs/UDTFs for zero-copy execution
⚙️ Built-in Python worker logging for easier debugging
⚙️ Filter pushdown for Python Data Sources

🛂 Spark Connect Enhancements
⚙️ Spark ML is now GA with intelligent model caching, compressed execution plans, and support for larger datasets.

📊SQL Maturity 
⚙️ SQL Scripting is GA with loops, error handlers, and cleaner syntax
⚙️ VARIANT data type with shredding: 8-30x faster reads on semi-structured data
⚙️ Recursive CTEs for hierarchical queries
⚙️ New KLL and Theta sketches for approximate aggregations

Available now on spark.apache.org and Databricks Runtime 18.0!

Staff AI Data Engineer | Data Infrastructure for AI | Data Engineering & Analytics System Design Community | 8x tech book author

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