| Level | Topic | Type |
|---|---|---|
| 100 | Access and analyze data in Netezza Performance Server | Article |
| 101 | Load and access data from your cloud data warehouse | Code pattern |
| 102 | Predict energy prices with in-database analytics | Code pattern |
This developer data science learning path targets a modern data warehousing use case where analytics and data warehousing are combined in one solution. You will learn how to load and access data from your Netezza data warehouse using methods such as loading from a notebook to a table using Python packages, or directly querying a file on cloud object storage through external tables. We will then create a project to analyze, visualize, and build a machine learning model using the in-built data science and statistical algorithms available on Netezza Performance Server. This can be replicated using a Netezza system on-prem (Netezza on IBM Cloud Pak for Data) or Netezza on Cloud (Netezza on Cloud Pak for Data, on IBM Cloud, AWS, and Azure).
To get started, click on a card below, or see the table above for a complete list of topics covered.
Access and analyze data in Netezza Performance Server
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Learn about:
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Load and access data from your cloud data warehouse
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Learn how to:
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Predict energy prices with in-database analytics
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Learn how to:
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