For the last few years, we have helped design and develop high performance realtime data products for ecommerce sites that operate globally. 

Working side by side with data teams, we have learned how the specific business requirements of ecommerce impact how you need to treat data and turn it into a real-time product: from the way you ingest it to how you publish and consume it. Providing instant access to consistent numbers and analysis about the business has become an immense competitive advantage for the teams we work with. It fundamentally changes how they operate.

You will find this course interesting if you work in data analytics in general, but especially if you are in ecommerce or another realtime at-scale business.

Challenges inherent to any analytics project at scale:

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• Dealing with large quantities of data: billions of ingested rows and trillions of rows scanned daily with high-frequency ingestion.
• Achieving high-concurrency consumption: several hundred, or more, requests per second serving real-time dashboards and/or automations.
• Data reconciliation: deduplication techniques and the ability to rewrite history at the scale and speed mentioned above.

Specific to ecommerce:

• Stock and catalog management
• Handling the order life cycle
• Reporting consistent results over different currencies and time zones
• Preparing for special events like Black Friday

Additional "small" details:

• Achieving “realtime”: sub-second API endpoints, responses, and chart rendering. 
• How to keep costs down even as data and use cases grow.
• How to be flexible enough to adapt to new use cases.

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