But how do I GET the data? Transparency Camp 2014Jeffrey Quigley
油
The document discusses data collection and management. It describes how Shooju is a web-based data platform that consolidates data sources, makes data searchable from one place, and seamlessly integrates with tools. It notes that most organizations spend more time cleaning and managing data than analyzing it. Common methods to collect data include APIs, scraping, and manual collection, each with advantages and disadvantages. Shooju provides cost savings, added data quality, and enables enhanced decision making by streamlining data workflows and automating processes.
A lot has changed since I gave one of these talks and man, has it been good. 2.0 brought us a lot of new CQL features and now with 2.1 we get even more! Let me show you some real life data models and those new features taking developer productivity to an all new high. User Defined Types, New Counters, Paging, Static Columns. Exciting new ways of making your app truly killer!
The data model is dead, long live the data modelPatrick McFadin
油
The document discusses how data modeling concepts translate from relational databases to Cassandra. It begins with background on how Cassandra stores data using a row key and columns rather than tables and relations. Common patterns like one-to-many and many-to-many relationships are achieved without foreign keys by duplicating and denormalizing data. The document also covers concepts like UUIDs, transactions, and how some relational features like sequences are handled differently in Cassandra.
The document provides an overview of logical data modeling presented by Chris Crisci at ESPN. It discusses what logical data modeling is, how it fits into enterprise architecture frameworks like Zachman, and key concepts like semantic analysis, normalization, and relational databases. Upcoming presentations on related topics from other experts are also announced.
This document discusses different data models used in database management systems including record-based, relational, network, hierarchical, and entity-relationship models. It provides details on each model such as how data is organized. A record-based model uses fixed-length records and fields. The relational model organizes data into tables with rows and columns. The network model links entities through multiple paths in a graph structure. The hierarchical model arranges data in a tree structure. Finally, the entity-relationship model views the real world as entities and relationships between entities.
This document discusses different types of data models, including hierarchical, network, relational, and object-oriented models. It focuses on explaining the relational model. The relational model organizes data into tables with rows and columns and handles relationships using keys. It allows for simple and symmetric data retrieval and integrity through mechanisms like normalization. The relational model is well-suited for the database assignment scenario because it supports linking data across multiple tables using primary and foreign keys, and provides query capabilities through SQL.
Data Modelling 101 half day workshop presented by Chris Bradley at the Enterprise Data and Business Intelligence conference London on November 3rd 2014.
Chris Bradley is a leading independent information strategist.
Contact chris.bradley@dmadvisors.co.uk
The document discusses data modeling, which involves creating a conceptual model of the data required for an information system. There are three types of data models - conceptual, logical, and physical. A conceptual data model describes what the system contains, a logical model describes how the system will be implemented regardless of the database, and a physical model describes the implementation using a specific database. Common elements of a data model include entities, attributes, and relationships. Data modeling is used to standardize and communicate an organization's data requirements and establish business rules.
A conceptual data model (CDM) uses simple graphical images to describe core concepts and principles of an organization at a high level. A CDM facilitates communication between businesspeople and IT and integration between systems. It needs to capture enough rules and definitions to create database systems while remaining intuitive. Conceptual data models apply to both transactional and dimensional/analytics modeling. While different notations can be used, the most important thing is that a CDM effectively conveys an organization's key concepts.
Glib Rybalko, GlobalLogics Test Lead, consultant and trainer was among 26 known Ukrainian and international experts who took a word on IT Weekend Ukraine 2013. Glib discussed features of automated software testing, benefits and feasibility of using this approach on various projects. During his speech, Glib pointed all necessary steps of automated testing implementation and gave homework for those who were interested in this field and wanted to implement it in their projects.
A presentation I've made for Computer Science students of St. Petersburg State University to talk about the professions within IT sphere. Contains several screenshots from Futurama
The document provides an overview of logical data modeling presented by Chris Crisci at ESPN. It discusses what logical data modeling is, how it fits into enterprise architecture frameworks like Zachman, and key concepts like semantic analysis, normalization, and relational databases. Upcoming presentations on related topics from other experts are also announced.
This document discusses different data models used in database management systems including record-based, relational, network, hierarchical, and entity-relationship models. It provides details on each model such as how data is organized. A record-based model uses fixed-length records and fields. The relational model organizes data into tables with rows and columns. The network model links entities through multiple paths in a graph structure. The hierarchical model arranges data in a tree structure. Finally, the entity-relationship model views the real world as entities and relationships between entities.
This document discusses different types of data models, including hierarchical, network, relational, and object-oriented models. It focuses on explaining the relational model. The relational model organizes data into tables with rows and columns and handles relationships using keys. It allows for simple and symmetric data retrieval and integrity through mechanisms like normalization. The relational model is well-suited for the database assignment scenario because it supports linking data across multiple tables using primary and foreign keys, and provides query capabilities through SQL.
Data Modelling 101 half day workshop presented by Chris Bradley at the Enterprise Data and Business Intelligence conference London on November 3rd 2014.
Chris Bradley is a leading independent information strategist.
Contact chris.bradley@dmadvisors.co.uk
The document discusses data modeling, which involves creating a conceptual model of the data required for an information system. There are three types of data models - conceptual, logical, and physical. A conceptual data model describes what the system contains, a logical model describes how the system will be implemented regardless of the database, and a physical model describes the implementation using a specific database. Common elements of a data model include entities, attributes, and relationships. Data modeling is used to standardize and communicate an organization's data requirements and establish business rules.
A conceptual data model (CDM) uses simple graphical images to describe core concepts and principles of an organization at a high level. A CDM facilitates communication between businesspeople and IT and integration between systems. It needs to capture enough rules and definitions to create database systems while remaining intuitive. Conceptual data models apply to both transactional and dimensional/analytics modeling. While different notations can be used, the most important thing is that a CDM effectively conveys an organization's key concepts.
Glib Rybalko, GlobalLogics Test Lead, consultant and trainer was among 26 known Ukrainian and international experts who took a word on IT Weekend Ukraine 2013. Glib discussed features of automated software testing, benefits and feasibility of using this approach on various projects. During his speech, Glib pointed all necessary steps of automated testing implementation and gave homework for those who were interested in this field and wanted to implement it in their projects.
A presentation I've made for Computer Science students of St. Petersburg State University to talk about the professions within IT sphere. Contains several screenshots from Futurama
26. 亳亰仆舒从 仗仂亠舒 3.
亠舒亳于仆亶 (亳仆从亠仄亠仆舒仍仆亶)
a) 亠于亠 亳亠舒亳亳 仆舒亠仍亠仆 仆舒 从亳亳仆亠 亳从亳
仆亳仄舒ム 舒仆仆亠亶 仂弍舒仆仂亶 于磶 仗仂仍亰仂于舒亠仍亠亶 亟仂
从仗仆 于仍仂亢亠仆亳亶
b) 亠仗亠于仆仂亠 亠亳仂于舒仆亳亠 亳 亳仆亠亞舒亳
c) 舒从仂仂仆亠 于亠亳 仂弍亠从亳于仆舒 仄亠舒
d) 仂亞亠 亳亰仄亠磳 仂亠仆从仂亶 仂弍亠仄舒 亠舒仍亳亰仂于舒仆仆仂亞仂
e) 丼舒亳仆亠 亠舒仍亳亰舒亳亳 仄仂亞 弍 于仆亠亟亠仆 仗仂仍亰仂亶
亠仄
亠舒亳 1 亠舒亳 2 亠舒亳 3
I
C
D
R
T
I
C
D
R
T
I
C
D
R
T
26
47. 舒从亳亠 亟亳舒亞舒仄仄 亠 于 UML?
Activity
Class
State machine
Composite structure
Sequence
Object
Use case
Package
Communication
Collaboration
Component
Interaction overview
Deployment
Timing
舒从亳亠 亳亰 仆亳 从仆亠? 6 .
舒从亳亠 仗仂于亠亟亠仆亳? 7 .
舒从亳亠 于亰舒亳仄仂亟亠亶于亳? 4 .
47
48. 亳仄亠: . 于舒亳舒仆仂于 亳仗仂仍亰仂于舒仆亳
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