Seattle, WA – Regus at Smith Tower

506 Second Ave, Suite 1400, Seattle, United States, 98104

The venue is located in the historic Smith Tower building in Pioneer Square, easily accessed by car via I‑5, I‑90, or I‑405, with nearby parking garages and street parking connected to the tower. From Seattle–Tacoma International Airport (SEA), a taxi or rideshare takes approximately 25–30 minutes via I‑5 North and Airport Way. Public transit is seamless: the Pioneer Square light rail station is just a 1-minute walk, and multiple King County Metro bus routes run along 2nd Avenue—making it highly convenient for attendees arriving without a car.

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Explore Our Courses

Big Data Analytics with Google Colab and Apache Spark

14 Hours

Stratio: Rocket and Intelligence Modules with PySpark

14 Hours

Data Warehousing: Concepts, Design, and Implementation

35 Hours

A Practical Introduction to Data Analysis and Big Data - 3 Days

21 Hours

Greenplum Architecture and Data Modeling

21 Hours

Greenplum Administration: Installation, Updates, and Libraries

21 Hours

Advanced Apache Iceberg

21 Hours

Apache Iceberg Fundamentals

14 Hours

Big Data Consulting

21 Hours

Azure Data Lake Storage Gen2

14 Hours

Python, Spark, and Hadoop for Big Data

21 Hours

Big Data and Advanced Analytics

42 Hours

IBM Datastage For Administrators and Developers

35 Hours

Administration of Apache Spark

35 Hours

A Practical Introduction to Data Analysis and Big Data

35 Hours

Python and Spark for Big Data (PySpark)

21 Hours

SQL For Data Science and Data Analysis

14 Hours

Administrator Training for Apache Hadoop

35 Hours

Big Data Business Intelligence for Govt. Agencies

35 Hours

Big Data Architect

35 Hours

Big Data Analytics in Health

21 Hours

Big Data Business Intelligence for Criminal Intelligence Analysis

35 Hours

Programming with Big Data in R

21 Hours

Big Data Storage Solution - NoSQL

14 Hours

Big Data & Database Systems Fundamentals

14 Hours

Big Data - Data Science

14 Hours

From Data to Decision with Big Data and Predictive Analytics

21 Hours

Data Science for Big Data Analytics

35 Hours

Hadoop For Administrators

21 Hours

Hadoop for Developers (4 days)

28 Hours

Advanced Hadoop for Developers

21 Hours

Hadoop Administration on MapR

28 Hours

Hadoop and Spark for Administrators

35 Hours

HBase for Developers

21 Hours

Infomatica with Big Data (BDM)

7 Hours

A Practical Introduction to Stream Processing

21 Hours

Machine Learning and Big Data

7 Hours

Apache NiFi for Administrators

21 Hours

Apache NiFi for Developers

7 Hours

Python and Spark for Big Data for Banking (PySpark)

14 Hours

SMACK Stack for Data Science

14 Hours

Apache Spark Fundamentals

21 Hours

Apache Spark in the Cloud

21 Hours

Spark for Developers

21 Hours

Scaling Data Pipelines with Spark NLP

14 Hours

Apache Spark SQL

7 Hours

Talend Big Data Integration

28 Hours

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