Cassandra Community Webinar | Make Life Easier - An Introduction to Cassandra Query Language

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The document discusses Cassandra data modeling using CQL3. It explains that a keyspace contains column families which are similar to SQL tables. Columns are sorted by key and each row's columns are grouped by the row key. The document provides an example of modeling user data with rows containing user id as the key and columns for each attribute like name, email etc. It also shows an example of modeling events data with user id as row key and columns for each event type grouped by timestamp.

Technology Business

Making things easy with CQL3
Matt Stump
DataStax

id : user1 password : 4cffdce7d84fb56f
email : foobar@example.com
name : Foo

id : user1 password : 4cffdce7d84fb56f
email : foobar@example.com
name : Foo
id : user2 password : 4cffdcabef44fb56f
email : bar@example.com
name : Bar

id : user1 password : 4cffdce7d84fb56f
email : foobar@example.com
name : Foo
id : user2 password : 4cffdcabef44fb56f
email : bar@example.com
name : Bar
email_marketing : false
permissions : admin

Keyspace
is a collection of
ColumnFamilies

id : user2 password : 4cffdcabef44fb56f
email : bar@example.com
name : Bar
email_marketing : false
permissions : admin
Columns are sorted

id : user1 [event, time] : data
[event, time] : data
[event, time] : data

id : user1
[purchase, 2011-02-04] : bread
[event, time] : data
[login, 2011-02-04] : mainpage
[login, 2011-02-03] : mainpage
[purchase, 2011-02-05] : soap

id : user1
[purchase, 2011-02-04] : bread
[event, time] : data
[login, 2011-02-04] : mainpage
[login, 2011-02-03] : mainpage
[purchase, 2011-02-05] : soap
id : user2
[purchase, 2013-02-04] : apple
[event, time] : data
[login, 2013-02-03] : twitter

References
• http://www.datastax.com/docs
• http://cassandra.apache.org/doc/cql3/CQL.html
• http://www.datastax.com/dev/blog/lightweight-transactions-in-cassandra-2-0

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Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

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As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape

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04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf

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Cassandra Community Webinar | Make Life Easier - An Introduction to Cassandra Query Language

1. Making things easy with CQL3 Matt Stump DataStax

2. id : user1 password : 4cffdce7d84fb56f email : foobar@example.com name : Foo

3. id : user1 password : 4cffdce7d84fb56f email : foobar@example.com name : Foo id : user2 password : 4cffdcabef44fb56f email : bar@example.com name : Bar

4. id : user1 password : 4cffdce7d84fb56f email : foobar@example.com name : Foo id : user2 password : 4cffdcabef44fb56f email : bar@example.com name : Bar email_marketing : false permissions : admin

5. id : user1 password : 4cffdce7d84fb56f email : foobar@example.com name : Foo id : user2 password : 4cffdcabef44fb56f email : bar@example.com name : Bar email_marketing : false permissions : admin Column Family

6. ColumnFamily = SQL Table

7. id : user1 password : 4cffdce7d84fb56f email : foobar@example.com name : Foo id : user2 password : 4cffdcabef44fb56f email : bar@example.com name : Bar email_marketing : false permissions : admin Column Family id : user1 password : 4cffdce7d84fb56f email : foobar@example.com name : Foo id : user2 password : 4cffdcabef44fb56f email : bar@example.com name : Bar email_marketing : false permissions : admin Column Family Keyspace

8. Keyspace is a collection of ColumnFamilies

10. id : user2 password : 4cffdcabef44fb56f email : bar@example.com name : Bar email_marketing : false permissions : admin Columns are sorted

11. id : user2 password : 4cffdcabef44fb56f email : bar@example.com name : Bar email_marketing : false permissions : admin Columns are sorted

12.

13.

14. 2^128

15. 2^128 HASH("user1") = 3

16. 2^128 HASH("user1") = 3

17.

18. id : user1 [event, time] : data [event, time] : data [event, time] : data

19. id : user1 [purchase, 2011-02-04] : bread [event, time] : data [login, 2011-02-04] : mainpage [login, 2011-02-03] : mainpage [purchase, 2011-02-05] : soap

20. id : user1 [purchase, 2011-02-04] : bread [event, time] : data [login, 2011-02-04] : mainpage [login, 2011-02-03] : mainpage [purchase, 2011-02-05] : soap id : user2 [purchase, 2013-02-04] : apple [event, time] : data [login, 2013-02-03] : twitter

21. References • http://www.datastax.com/docs • http://cassandra.apache.org/doc/cql3/CQL.html • http://www.datastax.com/dev/blog/lightweight-transactions-in-cassandra-2-0

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