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F11 - Using Jupyter Notebook for Db2 Administration

Session Number: 5060
Track: Ala Carte - I
Session Type: Podium Presentation
Primary Presenter: Ember Crooks [Xtivia]
Time: May 02, 2018 (01:05 PM - 02:05 PM)
Room: Congress A

Session Code: F11
Speaker Bio: Ember is a DB2 Lead DBA and Delivery Manager at XTIVIA. She is responsible for the design, build, and management of a wide range of DB2 databases for multiple clients. Ember has 16+ years of experience with DB2 on Linux, Unix, and Windows platforms. She is the founder and principal author of the popular db2commerce.com technical blog where she educates herself and others through example and case study. Ember is an IBM Gold Consultant and IBM Champion in Information Management.
Audience experience level: Beginner, Intermediate, Advanced
Presentation Category: Data Management, Emerging Technology, Managing Performance
Presentation Platform: DB2 for Linux, UNIX, Windows
Audiences this presentation will apply to: Database Administrators
Technical areas this presentation will apply to: Database Performance (DB2 for LUW), SQL and XML Features
Objective 1: What Jupyter Notebook is and how to set it up
Objective 2: Use SQL Magic to connect to a Db2 database and manipulate data
Objective 3: Investigate how SQL Magic works with Db2 and what you might need other tools for
Objective 4: Learn how to use Jupyter Notebook to create your own Db2 snapshot, including reset functionality, that focuses on the performance areas you care about.

Abstract:  There are so many new technologies in the data world. How can a Db2 DBA keep up with them? We can use some of them to our own advantage. Jupyter Notebook is a tool at the heart of data science. Come to this session to learn how you can use Jupyter Notebook in your day-to-day Db2 DBA tasks, for team documentation, and providing details on DB2 or SQL performance in formats that non-DBAs find convincing and compelling.

Learn how to use Jupyter Notebook to write your own Db2 Snapshot!

The concepts presented are largely cross platform, but the speaker's experience focuses on LUW, and a Db2 LUW database is used for all examples.

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