Cassandra Summit: Data Modeling A Scheduling App

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The task of a data modeler is to create order out of chaos without excessively distorting the truth. The finished product should be data model that describes the structure, manipulation and integrity aspects of the data to be stored. To properly create a data model, the modeler will transform said chaos through three distinct stages. The first is a Conceptual Data Model, then a Logical Data Model, and lastly, a Physical Data Model. This presentation will cover all three stages. It will also walk through the creation of a full blown data model for a service scheduling application to be built with a Cassandra backend. This presentation is based on a 3 part blog series I wrote for DataScale.

Technology

Data Modeling A Scheduling Application
Adam Hutson
Data Architect, DataScale Inc.

© DataStax, All Rights Reserved.
Who am I & What do we do?
2
Adam Hutson
Data Architect @ DataScale -> www.datascale.io
DataStax MVP for Apache Cassandra
DataScale provides hosted data platforms as a service
Offering Cassandra & Spark, with more to come
Currently hosted in Amazon & Azure

© DataStax, All Rights Reserved.
Data Modeling Stages
• Maps concepts, relationships,
& constraints
• Consists of entity classes with
characteristic attributes
• Nothing to do with a database
4

© DataStax, All Rights Reserved.
Data Modeling Stages
7

© DataStax, All Rights Reserved.
Data Modeling Stages
8

© DataStax, All Rights Reserved.
Data Modeling Stages
9

© DataStax, All Rights Reserved.
Scheduling Application Definition
What is it?
Application to schedule service appointments.
Who is it for?
Any employee of the service company.
What does it do?
Sets & retrieves appointments for service.
Client/Service detail requests.
Provider/Service detail requests.
Services delivered/scheduled over time.
11

© DataStax, All Rights Reserved.
Conceptual Model
13

© DataStax, All Rights Reserved.
Logical Model
15

© DataStax, All Rights Reserved.
Desired Queries
17
• Add new client information
• Get client info by name or phone
• Create appointment for specific date/time, client, service, & service technician
• Get all scheduled appointments for specified client name or phone
• Get all available times to schedule appointment for specified service & service technician
• Get all scheduled appointments for specified service technician

© DataStax, All Rights Reserved.
Physical Model
19
Add new client information

© DataStax, All Rights Reserved.
Physical Model
20
Add new client information

© DataStax, All Rights Reserved.
Physical Model
21
Get client info by name or phone

© DataStax, All Rights Reserved.
Physical Model
22
Get client info by name or phone

© DataStax, All Rights Reserved.
Physical Model
23
Create appointment for specific date/time, client, service, & service technician

© DataStax, All Rights Reserved.
Physical Model
24
Create appointment for specific date/time, client, service, & service technician

© DataStax, All Rights Reserved.
Physical Model
25
Get all scheduled appointments for specified client name or phone

© DataStax, All Rights Reserved.
Physical Model
26
Get all scheduled appointments for specified client name or phone

© DataStax, All Rights Reserved.
Physical Model
27
Get all available times to schedule appointment for specified service & service technician

© DataStax, All Rights Reserved.
Physical Model
28
Get all available times to schedule appointment for specified service & service technician

© DataStax, All Rights Reserved.
Physical Model
29
Get all scheduled appointments for specified service technician

© DataStax, All Rights Reserved.
Physical Model
30
Get all scheduled appointments for specified service technician

© DataStax, All Rights Reserved.
Physical Model
31
End Product: A complete script to create your entire Data Model in Cassandra

Thank You!
Questions?
Adam Hutson @AdamHutson
adam@datascale.io @DataScaleInc

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Boost PC performance: How more available memory can improve productivity

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naman860154

The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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Cassandra Summit: Data Modeling A Scheduling App

1. Data Modeling A Scheduling Application Adam Hutson Data Architect, DataScale Inc.

2. © DataStax, All Rights Reserved. Who am I & What do we do? 2 Adam Hutson Data Architect @ DataScale -> www.datascale.io DataStax MVP for Apache Cassandra DataScale provides hosted data platforms as a service Offering Cassandra & Spark, with more to come Currently hosted in Amazon & Azure

3. Data Modeling Stages

5. © DataStax, All Rights Reserved. Data Modeling Stages • Maps concepts, relationships, & constraints • Consists of entity classes with characteristic attributes • Nothing to do with a database 5 • Entities become tables • Attributes become columns/ fields • Relationships become key • Entity Relationship Diagram

6. © DataStax, All Rights Reserved. Data Modeling Stages • Maps concepts, relationships, & constraints • Consists of entity classes with characteristic attributes • Nothing to do with a database 6 • Entities become tables • Attributes become columns/ fields • Relationships become key • Entity Relationship Diagram • Applies constraints of chosen database • Table structure using syntax • Data types, keys, relationships

10. Scheduling Application

11. © DataStax, All Rights Reserved. Scheduling Application Definition What is it? Application to schedule service appointments. Who is it for? Any employee of the service company. What does it do? Sets & retrieves appointments for service. Client/Service detail requests. Provider/Service detail requests. Services delivered/scheduled over time. 11

12. Conceptual Model

14. Logical Model

16. Desired Queries

17. © DataStax, All Rights Reserved. Desired Queries 17 • Add new client information • Get client info by name or phone • Create appointment for specific date/time, client, service, & service technician • Get all scheduled appointments for specified client name or phone • Get all available times to schedule appointment for specified service & service technician • Get all scheduled appointments for specified service technician

18. Physical Model

32. Thank You! Questions? Adam Hutson @AdamHutson adam@datascale.io @DataScaleInc

Cassandra Summit: Data Modeling A Scheduling App

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