Dating, as is often said, is a numbers game. And organizations such as Match.com, and Zoosk rely on very sophisticated technology as they sift through vast customer bases to create the most compatible couples. Specially, they rely on data to build the most nuanced portraits of their members that they can, so they can find the best matches. This is a business-critical activity for dating sites — the more successful the matching, the better revenues will be. One of the ways they do this is through graph databases. These differ from relational databases as they specialize in identifying the relationships between multiple data points. This means they can query and display connections between people, preferences and interests very quickly.
In this session you will see how in many ways dating sites are getting better performance and more value out of their data than financial institutions by using Neo4j.
8 Secrets to Perfect Your Personal Brand OnlineJonathan Rick
Whether you know it or not, you’re carrying around a digital brand. But you have a choice in the matter: you can brand yourself, or you can be branded. You can do things to own your identity, or you can let default settings shape your name.
I think the latter is preferable. And so I’d to share eight easy ways to better brand yourself online.
"Meet me Alone, I'm real, let's talk to meet now.
I'm on-line presently ~>>>>>>> Aloneme01@outlook.com <<<<<<<<<<
don't worry, no demand any cc charge."
8 Paid Promotion Tactics That Will Get You To Quit Organic TrafficKane Jamison
If your content marketing launches aren't getting the results you want consistently, these paid media tactics will help you show a faster ROI from content marketing.
8 Secrets to Perfect Your Personal Brand OnlineJonathan Rick
Whether you know it or not, you’re carrying around a digital brand. But you have a choice in the matter: you can brand yourself, or you can be branded. You can do things to own your identity, or you can let default settings shape your name.
I think the latter is preferable. And so I’d to share eight easy ways to better brand yourself online.
"Meet me Alone, I'm real, let's talk to meet now.
I'm on-line presently ~>>>>>>> Aloneme01@outlook.com <<<<<<<<<<
don't worry, no demand any cc charge."
8 Paid Promotion Tactics That Will Get You To Quit Organic TrafficKane Jamison
If your content marketing launches aren't getting the results you want consistently, these paid media tactics will help you show a faster ROI from content marketing.
As long as you have more than 2,000 followers, you're bound to have fake followers among them.
It's important to identify and weed them out as they damage your engagement levels.
Don't miss out on the opportunity to hear Larry Kim's encore presentation from his TWICE SOLD OUT session at INBOUND! Larry will cover how to use unusual tips, strategies and process to get 10-100x more value from your paid campaigns!
During this webinar you’ll learn:
How to drive exponentially more traffic to your content
Convert 3-5x more of clicks into leads & sales – all for less than $50 per campaign
Critical insights into how the algorithm of Paid Social Media REALLY WORK
As the amount of personal data we produce continues to grow, so does the sophistication of the technology used to collect it. However, this ever-expending ecosystem of customer data is becoming so complex that few people actually understand how it all works, creating a widening divide between the data haves and haven-nots. To level the playing field, we’ll explain how customer data is used for personalization and targeted marketing in words that even a 5-year-old can understand—literally. In this session, we’ll tell the story of Parker, a data manifestation who travels through the strange world of the digital information on a journey to find his way home. Along the way, we’ll explain concepts like Customer Data Platforms (CDPs), predictive modeling, data on-boarding and more. It’s a story the whole family can enjoy, including technologists, marketers and privacy advocates.
Shopping Goes Social - how our habits as consumers are changingDaniel Ord Rasmussen
Our habits as consumers are changing offline as well as online. We "hack" retail by finding loopholes, coupons, deals and tricks that get us what we want. We circumvent artificial boundaries such as borders by "spoofing" locations and we receive products via legal middle-men.
At the same time these online tricks are moving offline again with the advent of location based marketing via Foursquare and Facebook.
This presentation gives a quick overview of an emerging field that is changing rapidly.
With regards to web based dating from AnastasiaDate.com, the majority of the individuals get befuddled about whether they ought to go with the equivalent or not.
This Marketing Report looks at how those
operating in the UK beauty sector are using
email not only to generate sales, but also
to drive traffic and build relationships. We
have looked at how businesses who operate
in this sector acquire new email addresses,
what data they collect at subscription and
how they welcome new subscribers to the
brand. In addition, we explore the often
controversial subject of email frequency,
alongside the issue of responsive design,
and also look at abandoned basket emails.
7 Ridiculously Awesome Ways to Rule LinkedIn By Larry KimMarketing Land
From the SocialPro Conference in Las Vegas, Nevada, November 18-19, 2015. SESSION: Connecting With LinkedIn. PRESENTATION: 7 Ridiculously Awesome Ways to Rule LinkedIn! - Given by Larry Kim, @larrykim - WordStream, Founder & CTO. #SocialPro #22A1
Recorded webinar: neotechnology.com/webinar-five-graphs-love
The iDating industry cares about interactions and connections. Those two concepts are closely linked. If someone has a connection to another person, through a shared friend or a shared interest, they are much more likely to interact. Graph databases are optimized for querying connections between people, things, interests, or really anything that can be connected.
Dating sites and apps worldwide have begun to use graph databases to achieve competitive gain. Neo4j provides thousand-fold performance improvements and massive agility benefits over relational databases, enabling new levels of performance and insight. Amanda Laucher discusses the five graphs of love, and how companies like eHarmony, Hinge and AreYouInterested.com, are now using graph algorithms to create more interactions and connections.
Below are the 40 Questions that will Guarantee, You’ll Never Have A Boring Date:
1. Ask them to give you two “truths” and a lie. Then try to guess which one is a lie.
2. If you could write a note to your younger self, what would you say in only two words?
Read more : http://www.datersearch.com/blog/
As long as you have more than 2,000 followers, you're bound to have fake followers among them.
It's important to identify and weed them out as they damage your engagement levels.
Don't miss out on the opportunity to hear Larry Kim's encore presentation from his TWICE SOLD OUT session at INBOUND! Larry will cover how to use unusual tips, strategies and process to get 10-100x more value from your paid campaigns!
During this webinar you’ll learn:
How to drive exponentially more traffic to your content
Convert 3-5x more of clicks into leads & sales – all for less than $50 per campaign
Critical insights into how the algorithm of Paid Social Media REALLY WORK
As the amount of personal data we produce continues to grow, so does the sophistication of the technology used to collect it. However, this ever-expending ecosystem of customer data is becoming so complex that few people actually understand how it all works, creating a widening divide between the data haves and haven-nots. To level the playing field, we’ll explain how customer data is used for personalization and targeted marketing in words that even a 5-year-old can understand—literally. In this session, we’ll tell the story of Parker, a data manifestation who travels through the strange world of the digital information on a journey to find his way home. Along the way, we’ll explain concepts like Customer Data Platforms (CDPs), predictive modeling, data on-boarding and more. It’s a story the whole family can enjoy, including technologists, marketers and privacy advocates.
Shopping Goes Social - how our habits as consumers are changingDaniel Ord Rasmussen
Our habits as consumers are changing offline as well as online. We "hack" retail by finding loopholes, coupons, deals and tricks that get us what we want. We circumvent artificial boundaries such as borders by "spoofing" locations and we receive products via legal middle-men.
At the same time these online tricks are moving offline again with the advent of location based marketing via Foursquare and Facebook.
This presentation gives a quick overview of an emerging field that is changing rapidly.
With regards to web based dating from AnastasiaDate.com, the majority of the individuals get befuddled about whether they ought to go with the equivalent or not.
This Marketing Report looks at how those
operating in the UK beauty sector are using
email not only to generate sales, but also
to drive traffic and build relationships. We
have looked at how businesses who operate
in this sector acquire new email addresses,
what data they collect at subscription and
how they welcome new subscribers to the
brand. In addition, we explore the often
controversial subject of email frequency,
alongside the issue of responsive design,
and also look at abandoned basket emails.
7 Ridiculously Awesome Ways to Rule LinkedIn By Larry KimMarketing Land
From the SocialPro Conference in Las Vegas, Nevada, November 18-19, 2015. SESSION: Connecting With LinkedIn. PRESENTATION: 7 Ridiculously Awesome Ways to Rule LinkedIn! - Given by Larry Kim, @larrykim - WordStream, Founder & CTO. #SocialPro #22A1
Recorded webinar: neotechnology.com/webinar-five-graphs-love
The iDating industry cares about interactions and connections. Those two concepts are closely linked. If someone has a connection to another person, through a shared friend or a shared interest, they are much more likely to interact. Graph databases are optimized for querying connections between people, things, interests, or really anything that can be connected.
Dating sites and apps worldwide have begun to use graph databases to achieve competitive gain. Neo4j provides thousand-fold performance improvements and massive agility benefits over relational databases, enabling new levels of performance and insight. Amanda Laucher discusses the five graphs of love, and how companies like eHarmony, Hinge and AreYouInterested.com, are now using graph algorithms to create more interactions and connections.
Below are the 40 Questions that will Guarantee, You’ll Never Have A Boring Date:
1. Ask them to give you two “truths” and a lie. Then try to guess which one is a lie.
2. If you could write a note to your younger self, what would you say in only two words?
Read more : http://www.datersearch.com/blog/
This is the result of an extensive study on the users of dating apps like Tinder, OKCupid, Zoosk and others. We were studying how people use the apps, how they present themselves, and whether or not they feel successful. We conducted this study over the course of a month to gain design insights and directions.
Comparison of Tinder, Match.com, Zoosk, Bumble and Other Dating Apps on Faceb...Unmetric
They offer opportunities to engage with prospective partners, but how engaging are the content and campaign strategies of the top dating apps on Facebook? We benchmarked their performances to find out.
Decoding Monetization Methods For Dating AppsInMobi
Swipe right - the new age dating gesture, has permeated the mobile world. Today, users end up spending almost 90 minutes of their day sifting through myriad potential partners, in search of the perfect match. This is greater than the average time spent by a user on traditional social networking sites, creating an alternate social network that is distinctly different from its older cousin.
How can mobile developers building dating apps tap into this growing opportunity? Dating apps enjoy long user engagement sessions and access to deep user data, presenting a unique opportunity for monetization that is yet to be realized fully. Recently, players like Starbucks and 20th Century Fox launched cheeky, innovative advertising campaigns on dating apps - lighting the way for several other advertisers. Even developers who are not building dating apps, can learn from the mechanics of this app category.
Join this webinar to :
Learn best practices around designing the app experience for your dating app
Get a comprehensive overview of monetization methods for dating apps
Learn how to leverage mobile advertising effectively to maximize user engagement & revenues
Learn how other app categories too can benefit from the mechanics of successful dating apps
Even if you can’t make the presentation, do sign-up and we will send you a recording of the webinar.
How to Leverage Customer Data for Successful Paid Media Campaigns: The ROI of...Tinuiti
According to Forbes, only 13% of companies have a high degree of confidence that they are maximizing their available customer data. A marketers’ greatest tool is customer data, as it provides critical insights, makes marketing teams more effective, and allows brands to tailor support to each individual customer. Tune in to our webinar as we unpack how to properly leverage technology to unify first, second, and third party data to map your customers’ journey, connect off and online touchpoints, and advance your marketing strategy to increase your ROI on paid media efforts.
2023 Maryland Real Estate Buyer Luxury Presentation. The Golden Girl has 40 +/- years experience covering Southern Maryland to Anne Arundel County including Calvert County, Charles County, St. Mary's County and P.G. County. Here are the Golden Results tools, steps and plan to find your Maryland Luxury GOLDEN RESULTS home. You'll Retrieve Golden Results with Cheryl Ritchie, Associate Broker, RE/MAX Leading Edge, www.GoldenResults.com GoldenGirl@GoldenResults.com for the Golden Results YOU deserve.
Charity scams are on the rise. Learn to protect yourself with key tips from the FTC, including how to research charities and the safest ways to donate.
Key Takeaways:
- research before donating
- don’t let anyone pressure you
- don’t click any unfamiliar links
- donate via check or credit card (never use wire transfers or gift cards)
- review your statements to be sure you were charged the correct amount
We are Web Scraping Expert company providing data scraping, data mining, data cleaning, email research, data validation, lead generation, online business directory scraping.
We are enough capable to extract millions of database from online business directories.
We can show you Free Sample Before Fix the Deal. You can drop me email on info@webscrapingexpert.com.
9,000 Ways to Optimize Outcomes in Financial ServicesPrecisely
Trusted analytics and predictive data models require accurate, consistent, and contextual data. Even with the vast amount of internal business data available, financial services institutions are looking to trusted 3rd party data to fuel analytical models with new and relevant attributes to gain meaningful insights.
With over 9,000 data attributes describing the people, places, and a myriad of details for any given location, Precisely is uniquely positioned to help Financial Services companies create new and innovative insights from data. Stay ahead of the competition and gain a competitive advantage with trusted data for confident business decisions.
During this webinar, you will see how our clients are leveraging innovative strategies to unlock the power of data. Use cases will include:
Commercial Lending: How do I efficiently understand collateral?Mortgage: Improved understanding of comps in a volatile market?Credit Card: How do I drive more card transactions via location understanding? Network Optimization: Where are my customers and how do they want to interact with me?Cross Sell: Who is my customer and what products should I offer her?Investment Banking: What alternative data helps me better understand investment opportunities?ESG: How can I better understand and predict the impact of new ESG initiatives on my profitability?Improve Efficiencies: Increase accuracy of comps and create amenity scores to improve Automate Physical Appraisal Waiver decision-making
Build Intelligent Fraud Prevention with Machine Learning and GraphsNeo4j
See how financial services, banking and retail are using graph-enhanced machine learning to thwart fraud. Fraudsters are becoming increasingly sophisticated, organized and adaptive; traditional, rule-based solutions are not broad or nimble enough to deal with this reality. This session will cover several demonstrations and real-world technical examples including preventing credit card fraud, identifying money laundering and reducing false positives.
Smarter Fraud Detection With Graph Data ScienceNeo4j
Join us for this 20-minute webinar to hear from Nick Johnson, Product Marketing Manager for Graph Data Science, to learn the basics of Neo4j Graph Data Science and how it can help you to identify fraudulent activities faster.
Outrageous ideas for Graph Databases
Almost every graph database vendor raised money in 2021. I am glad they did, because they are going to need the money. Our current Graph Databases are terrible and need a lot of work. There I said it. It's the ugly truth in our little niche industry. That's why despite waiting for over a decade for the "Year of the Graph" to come we still haven't set the world on fire. Graph databases can be painfully slow, they can't handle non-graph workloads, their APIs are clunky, their query languages are either hard to learn or hard to scale. Most graph projects require expert shepherding to succeed. 80% of the work takes 20% of the time, but that last 20% takes forever. The graph database vendors optimize for new users, not grizzly veterans. They optimize for sales not solutions. Come listen to a Rant by an industry OG on where we could go from here if we took the time to listen to the users that haven't given up on us yet.
Outrageous ideas for Graph Databases
Almost every graph database vendor raised money in 2021. I am glad they did, because they are going to need the money. Our current Graph Databases are terrible and need a lot of work. There I said it. It's the ugly truth in our little niche industry. That's why despite waiting for over a decade for the "Year of the Graph" to come we still haven't set the world on fire. Graph databases can be painfully slow, they can't handle non-graph workloads, their APIs are clunky, their query languages are either hard to learn or hard to scale. Most graph projects require expert shepherding to succeed. 80% of the work takes 20% of the time, but that last 20% takes forever. The graph database vendors optimize for new users, not grizzly veterans. They optimize for sales not solutions. Come listen to a Rant by an industry OG on where we could go from here if we took the time to listen to the users that haven't given up on us yet.
Los estafadores ahora están utilizando métodos más sofisticados y dinámicos con tarjetas de crédito, el blanqueo de dinero y otros tipos de fraude. El aprovechamiento de la tecnología gráfica le permitirá ver más allá de los puntos de datos individuales y descubrir patrones difíciles de detectar.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
1. What
Finance
can
learn
from
Dating
Sites
Max
De
Marzi
GOTO
Chicago
2. About
Me
• Max
De
Marzi
-‐
Neo4j
Field
Engineer
• My
Blog:
http://maxdemarzi.com
• Find
me
on
Twitter:
@maxdemarzi
• Email
me:
maxdemarzi@gmail.com
• GitHub:
http://github.com/maxdemarzi
5. Friends
of
Friends
Graph
• Real
World
Basis
• Its
Weighted
(BFF
vs
Family)
• Awesome
or
Awkward
The
Five
Graphs
of
Love
Location
Graph
• Long
Distance
Sucks
• Where
are
the
single
people
• Where
should
we
meet
Passion
Graph
• Shared
Interests
• Desired
Traits
• Long
vs
Short
Term
Safety
Graph
• True
Identity
• Liers
and
Cheaters
• Balancing
Privacy
SPAM
Graph
• Click
Bait
• Wanna
Cam?
• Professionals
1 2 3
4 5
6. The
Five
Graphs
of
Love
1Friends
2Passion
3Location
4Safety
5SPAM
14. MATCH
(:Person
{
name:“Dan”}
)
-‐[:FRIENDS]-‐>
(:Person
{
name:“Ann”}
)
FRIENDS
Dan Ann
Label Property Label Property
Node Node
Cypher
Query
Language
15. MATCH
(boss)-‐[:MANAGES*0..3]-‐>(sub),
(sub)-‐[:MANAGES*1..3]-‐>(report)
WHERE
boss.name
=
“John
Doe”
RETURN
sub.name
AS
Subordinate,
count(report)
AS
Total
Express
Complex
Queries
Easily
with
Cypher
Find
all
direct
reports
and
how
many
people
they
manage,
up
to
3
levels
down
Cypher
QuerySQL
Query
16. The
Five
Graphs
of
Love
1Friends
2Passion
3Location
4Safety
5SPAM
2Passion
Graph
23. Recommend
Love
Find
your
soulmate
in
the
graph
• Are
they
energetic?
• Do
they
like
dogs?
• Have
a
good
sense
of
humor?
• Neat
and
tidy,
but
not
crazy
about
it?
What
are
the
Top
10
Potential
Mates
for
me
• that
are
in
the
same
location
• are
sexually
compatible
• have
traits
I
want
• want
traits
I
have
39. The
Five
Graphs
of
Finance
1Payment
2Customer
3Entitlement
4Asset
5Master
Data
1Payment
Graph
40. Intuit
Payment
Graph
Discover
latent
network
from
multiple
product
data
stores
• Uniquely
identify
entities
and
their
connections
• Connections
scored
by
volume
of
trade
Empower
business-‐unit
teams
to
leverage
the
Intuit
Payment
Graph
to
build
applications
• Graph
to
be
available
for
real-‐time
queries
1Payment
41. Consumer
Profile
Facets
Identity
Name
Address
Phone
Email
Social
Facebook
Yelp
Twitter
…
Demographics
Age
Gender
…
Business
Profile
Facets
Identity
Name
Address
Phone
Email
Social
Facebook
Yelp
Twitter
…
Demographics
Category
Revenue
Employees
…
1Payment
Payment
Graph
Depends
on
the
Customer
Graph
42. 1Payment
Capturing
C2B
and
B2B
Transactions
BUSINESSBUSINESS
CONSUMER
June
1
purchase
$25.95 June
3
purchases
$650.25
48. Name
Windsor
Press,
Inc.
Address
6
North
Third
St
City
Hamburg
State
PA
Zip
19526
Phone
610-‐562-‐2267
Name
The
Windsor
Press
Address
6
North
3rd
Street
City
Hamburg
State
PA
Zip
19526-‐0465
Phone
610-‐562-‐2267
ID
002114902
Name
Windsor
Press,
Inc.
Address
6
N
3rd
St
City
Hamburg
State
PA
Zip
19526-‐1502
Phone
610-‐562-‐2267
Both
of
the
records
above
map
to
the
same
record
2Customer
Cleaning
and
Matching
for
360-‐Degree
Master
View
49. Synthetic
Identities
and
Fraud
Rings
145
Hickory
Rd
Pasadena,
CA
415
Hickory
St
Pasadena,
CA
626-‐407-‐1234
626-‐814-‐6532
Quickly
see
which
customers
share
the
same
contact
information 2Customer
50. 3
fake
addresses
and
3
fake
phone
addresses
can
create
9
fake
customers
2Customer
Bank
Fraud
Using
False
Personas
51. High
Speed
Fraud
-‐
1000
R/S
http://maxdemarzi.com/2014/02/12/online-‐payment-‐risk-‐management-‐with-‐neo4j/
52. High
Speed
Fraud
-‐
8000
R/S
http://maxdemarzi.com/2014/02/27/neo4j-‐at-‐ludicrous-‐speed/
53. High
Speed
Fraud
-‐
28000
R/S
http://maxdemarzi.com/2014/03/10/its-‐over-‐9000-‐neo4j-‐on-‐websockets/
60. Express
Complex
Relationship
Queries
Easily
For
a
given
fund,
return
all
assets
that
are
made
up
of
other
assets,
ordered
by
the
total
number
of
included
assets
Cypher
Query
SQL
Query
MATCH
(fund)-‐[:INCLUDES*0..n]-‐>(sub),
(sub)-‐[:INCLUDES*1..n]-‐>(asset)
WHERE
fund.ticker
=
“TRLGX”
RETURN
sub.ticker
AS
Asset_Group,
count(asset)
AS
Total
ORDER
BY
Total
DESC
61. The
Five
Graphs
of
Finance
1Payment
2Customer
3Entitlement
4Asset
5Master
Data
5Master
Data
Graph
71. Cypher
Query:
Movie
Recommendation
MATCH
(watched:Movie
{title:"Toy
Story”})
<-‐[r1:RATED]-‐
()
-‐[r2:RATED]-‐>
(unseen:Movie)
WHERE
r1.rating
>
7
AND
r2.rating
>
7
AND
watched.genres
=
unseen.genres
AND
NOT(
(:Person
{username:”maxdemarzi"})
-‐[:RATED|WATCHED]-‐>
(unseen)
)
RETURN
unseen.title,
COUNT(*)
ORDER
BY
COUNT(*)
DESC
LIMIT
25
What
are
the
Top
25
Movies
• that
I
haven't
seen
• with
the
same
genres
as
Toy
Story
• given
high
ratings
• by
people
who
liked
Toy
Story
72. Relational
Databases
Can’t
Handle
Relationships
Well
• Cannot
model
or
store
data
and
relationships
without
complexity
• Performance
degrades
with
number
&
levels
of
relationships,
and
database
size
• Query
complexity
grows
with
need
for
JOINs
• Adding
new
types
of
data
and
relationships
requires
schema
redesign,
increasing
time
to
market
…
making
traditional
databases
inappropriate
when
relationships
are
valuable
in
real-‐time
Slow
development
Poor
performance
Low
scalability
Hard
to
maintain
73. NoSQL
Databases
Don’t
Handle
Relationships
• No
data
structures
to
model
or
store
relationships
• No
query
constructs
to
support
relationships
• Relating
data
requires
“JOIN
logic”
in
the
application
• No
ACID
support
for
transactions
…
making
NoSQL
databases
inappropriate
when
relationships
are
valuable
in
real-‐time
74. Real-‐Time
Query
Performance
Performance
must
hold
steady
with
scale
Connectedness
and
Size
of
Data
Set
Response
Time
0
to
2
hops
0
to
3
degrees
Thousands
of
connections
Tens
to
hundreds
of
hops
Thousands
of
degrees
Billions
of
connections
Relational
and
Other
NoSQL
Databases
Neo4j
Neo4j
is
1000x
faster
Reduces
minutes
to
milliseconds
75. Re-‐Imagine
Your
Data
as
a
Graph
Neo4j
is
an
enterprise-‐grade
graph
database
that
enables
you
to:
• Model
and
store
your
data
as
a
graph
• Query
relationships
with
ease
and
in
real-‐time
• Seamlessly
evolve
applications
to
support
new
requirements
by
adding
new
kinds
of
data
and
relationships
Agile
development
High
performance
Vertical
and
horizontal
scale
Seamless
evolution