www.amazon.com/author/paulbabicki
Graph Database
via whatis.com
A graph
database, also called a graph-oriented database, is a type of
NoSQL database that uses graph theory to store, map and query relationships.
A graph
database is essentially a collection of nodes and edges. Each node represents
an entity (such as a person or business) and each edge represents a
connection or relationship between two nodes. Every node in a graph database
is defined by a unique identifier, a set of outgoing edges and/or incoming
edges and a set of properties expressed as key/value pairs. Each edge is
defined by a unique identifier, a starting-place and/or ending-place node and
a set of properties. The mantra of graph database enthusiasts is "If you
can whiteboard it, you can graph it."
Graph databases are well-suited for
analyzing interconnections, which is why there has been a lot of interest in
using graph databases to mine data from social media. Graph databases are
also useful for working with data in business disciplines that involve
complex relationships and dynamic schema, such as supply chain management,
identifying the source of an IP telephony issue, distinguishing fraudulent
behavior from valid instances of similar transactions and creating
"customers who bought this also looked at..." recommendations.
The
concept behind graphing a database is often credited to 18th century
mathematician Leonhard Euler.
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Good Netiquette And A Green Internet To All! =====================================================================|
Graph Database
via whatis.com
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A graph
database, also called a graph-oriented database, is a type of
NoSQL database that uses graph theory to store, map and query relationships. A graph database is essentially a collection of nodes and edges. Each node represents an entity (such as a person or business) and each edge represents a connection or relationship between two nodes. Every node in a graph database is defined by a unique identifier, a set of outgoing edges and/or incoming edges and a set of properties expressed as key/value pairs. Each edge is defined by a unique identifier, a starting-place and/or ending-place node and a set of properties. The mantra of graph database enthusiasts is "If you can whiteboard it, you can graph it." 
Graph databases are well-suited for
analyzing interconnections, which is why there has been a lot of interest in
using graph databases to mine data from social media. Graph databases are
also useful for working with data in business disciplines that involve
complex relationships and dynamic schema, such as supply chain management,
identifying the source of an IP telephony issue, distinguishing fraudulent
behavior from valid instances of similar transactions and creating
"customers who bought this also looked at..." recommendations.
|
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===============================================================In addition to this blog, Netiquette IQ has a website with great assets which are being added to on a regular basis. I have authored the premiere book on Netiquette, “Netiquette IQ - A Comprehensive Guide to Improve, Enhance and Add Power to Your Email". My new book, “You’re Hired! Super Charge Your Email Skills in 60 Minutes. . . And Get That Job!” has just been published and will be followed by a trilogy of books on Netiquette for young people. You can view my profile, reviews of the book and content excerpts at:
www.amazon.com/author/paulbabicki
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