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SF Data Weekly - Airflow Concepts, 4 WLM Steps in Amazon Redshift, Gaming Events Pipeline, ML Models on Structured Streaming, 10 Python Myths

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July 9 · Issue #75 · View online
SF Data Weekly
Our Pick
Making Data Analytics Work For You--Instead of the Other Way Around | McKinsey & Company
Observe, orient, decide and act, a strategic decision making model.
Data Pipelines
4 Simple Steps To Set-up Your WLM in Amazon Redshift For Better Workload Scalability - intermix.io
Defining WLM slot count and memory percentage in Amazon Redshift.
Build a Mobile Gaming Events Data Pipeline with Databricks Delta
High-level view of the designed end-to-end data pipeline.
Understanding Apache Airflow’s Key Concepts
Airflow UI screenshots: Graph View (top), Tree View (bottom) of a workflow.
Data Storage
A Journey Through Spark
Big News In Databases: SQL Still on The Rise, Cloud First, Fsyncgate and a Giant Leap for SQL
Snowflake’s Cloud Data Warehouse — What I Learned and Why I’m Rethinking the Data Warehouse
Snowflake's three main components: services, processing and storage.
Data Analysis
Accelerating Discovery with a Unified Analytics Platform for Genomics
Projected annual storage in 2025.
Learn How to Code and Deploy ML Models on Structured Streaming
A high-level view of the project's architecture.
10 Myths of Enterprise Python | PayPal Engineering Blog
Data Visualization
Designing for Data Visualization – Design at IBM
IBM's Watson Analytics data chart, also highlighting statistically significant numbers.
Data-driven Products
A Winning Combination: Pairing Video and Movement Data to Enhance Sports Data Analysis
The main visual analytics techniques for region, event and player analysis.
Data Engineering Jobs
Data Engineer - Splunk
Senior Data Engineer - WeWork Global Technology
If you want to post a job for your company, you can do it here.
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