Vertica Analytics Database general overview

Stratebi
StratebiTeacher Master Big Data and Business Intelligence at EOI um Stratebi
Analytics is the key to unlock digital
transformation…
Amit Manor, Vertica Channel Director EMEA
Table of Contents
 Why Now, Why Change
 What is Vertica
 How Vertica Delivers Business Values
 Next Steps
2
Our Time is Now!
3
• Traditional DW companies are struggling
• Freedom to Deploy Everywhere
• Machine learning is everywhere
• Hadoop hangover
• Open source technologies are not free!
Legacy EDWs Data Lakes
Declining performance at scale
Built on aging technology
Expensive w/ proprietary hardware
Limited deployment options
Cheap storage of Big Data
Limited analytics capabilities
Poor performance
Lacks governance & security
Raison d’être
Bridging the gap between high cost legacy EDWs and Hadoop data
lakes
What Is Vertica and how we
transform the Enterprises
6
A History Of Innovation
6
The journey from Ingres to Postgres to C-Store
What is Vertica?
7
SQL Database
Load and store data in
a data warehouse
designed for blazing
fast analytics
Query Engine
Ask complex analytical
questions and get fast
answers regardless of
where the data resides
Vertica is an advanced analytics platform built for the scale and complexity of today’s data-driven
world. It combines the power of a high-performance, MPP query engine with advanced analytics
and machine learning.
Analytics & ML
Create, train and deploy
advanced analytics and
machine learning models
at massive scale
8
An Open Architecture with Rich Ecosystem Integrations
Future-proof your analytics
9
The data storage decisions you make today won’t impact your ability to execute in the future
SQL Database
++
Analytics & ML
Access one unified analytics engine and license across all infrastructure choices
Choose your Deployment Choose your Consumption
On Prem
Choose your Cloud
Compute StorageHardware AgnosticHybrid Cloud
Query Engine
End-to-end machine learning management
10
Vertica supports the entire predictive analytics process
Data Analysis Data Preparation Modeling Evaluation Deployment
• Statistical Summary
• Time Series
• Sessionize
• Pattern Matching
• Date/Time Algebra
• Window Partition
• Sequences
• And more…
• Outlier Detection
• Normalization
• Imbalanced Data
Processing
• Sampling
• Missing Value
Imputation
• And More…
• SVM
• Random Forests
• Logistic Regression
• Linear Regression
• Ridge Regression
• Naïve Bayes
• Cross Validation
• And More…
• Model-level Stats
• ROC Tables
• Error Rate
• Lift Table
• Confusion Matrix
• R-Squared
• MSE
• And More…
• Deploy Anywhere
• In Database Scoring
• Massively Parallel
Processing
• Speed
• Scale
• Security
• And More…
SQL Database
++
Analytics & ML Query Engine
How Vertica delivers business
value
12
Smart
Buildings
Health / EMR
Analytics
Ride
Share
Customer
Analytics
Network
Optimization
Predictive
Maintenance
Route
Optimization
Wearable
Analytics
Smart
Agriculture
Software
Optimization
Clickstream
Analytics
Security
Analysis
A Day in The Life of Vertica
Vertica powers the applications and services that enable our data-driven world
Three Cross-Industry Business Strategies – At A Glance
Examples by Industry where analytics is required to compete
Strategy Healthcare Retail Telco IoT
Marketing/Ad
Serving
IT
Infrastructure
Financial
Services
I. CUSTOMER
EXPERIENCE
MANAGEMENT
Faster service
Lower bills
Population
Health Initiatives
Enhanced
Shopping
Experience
Subscriber
expansion
Predictive
Maintenance
Ad targeting
Application
Performance
Investment
management
and modelling
II. OPERATIONAL
ANALYTICS
Hospital
Efficiency
Pricing and
Inventory
Management
Infrastructure
Optimization
Supply Chain
Efficiency
Improved customer
interest based on
target marketing
Dynamic
resource
management
Real-time
Comparative
Analytics
III. ASSURANCE
AND FRAUD
DETECTION
Healthcare fraud
detection
Payer protection
Provider
malpractice
Credit card fraud
loss prevention
Voice, video and
data reliability
SIM Card Fraud
Smart Meter
Management
Spam prevention
Ad Delivery
Traffic
optimization
and Authorized
Access
Management
Authorized
access and fraud
detection
Telecommunications – Use Cases
14
Analyze billions of
usage records to
understand overall network
health and identify areas to
optimize network
performance and reliability
Assess network load
patterns, predict how new
services will impact
bandwidth, and what new
capacity might be needed
under future scenarios
Analyze CDR and
customer data to develop
targeted promotions that
attract and retain new and
existing customers, reduce
churn and increase
profitability
Network Monitoring
and Optimization
Capacity Planning and
Management
Customer Behavior and
Churn Analytics
Comply with new and
emerging regulations
regarding historical data
retention and mandated
response SLAs for
government queries
Regulatory
Compliance
15
 In AT&T’s Next Generation White Paper, they
wrote
“Vertica has emerged as the primary alternative to engineered
Teradata Data Warehouse workloads. Vertica is a software-
only solution that deploys on commodity servers. Initiatives are
currently underway looking for Teradata candidate instances to
migrate to alternative solutions like Vertica. Vertica is
architected to provide continuous data loading and querying
capabilities to thousands of concurrent users.”
 They continued:
“There are several “anchor” architectural elements that have
emerged in the DW/Big Data ecosystem which we consider a
part of our long-term strategy. Among them are Vertica,
Hortonworks Data Platform and MicroStrategy Analytics.”
Telco - AT&T
Success in IOT/Manufacturing
• BMW uses Vertica to analyse
patterns in sensor data to
minimize app defects
• Vertica powers analytics for
Trane Intelligent Services
business
• Eight times faster than Hive and a
tight integration with Hadoop
allowed us to best German-based
Exasol
• Delivers efficient and faster car
development through a more
effective error analysis from the
telematics on the test fleet.
• Use of Eon allowed Philips to
scale from 500 TBs to over a PB
of data economically
• Focus on improving patient
monitoring equipment, reduce
costs and improve customer
satisfaction.
• Increases customer value with
equipment monitoring, event
mitigation, & energy
performance services
• Helps customers reduce energy
& maintenance costs
• Vertica delivers predictive
maintenance on over 30,000
Imaging Devices WW.
And the most mature OEM
program in analytics…
18
Allow user-defined
functions (UDx)
Require minimal
administration
Manage huge data
volumes Deliver fast analytics Embed machine learning
Support data scientists
Handle high user
concurrency
OEM software vendors need an embedded analytics software
platform that can:
Automated Analytics
Open architecture
Optimized data storage
Easy set-up and administration
Blazing fast analytics
Massive scalability
Vertica Platform as Analytics OEM Engine
OEM engine to drive real-time analytics and ML to
monetize all of your data at massive scale
In-database advanced
analytics and ML
Value Proposition: OEM Engine for ISVs
Vertica OEM Customers - Worldwide
20
 Catch Media implemented a data analytics
platform capable of tracking hundreds of
millions of users, with tens of billions of data
event transactions processed in near-real-time
on a monthly basis, with no data aggregation or
reduction in query performance or feature
limitations.
 Resulted in 50% increase in engagement
through data-driven segmentation,
management of one-to-many relationships,
flexible data hosting options, and unlimited
historical data querying without the need to pre-
aggregate
Delivering data-driven
personal insight into
300+ million users
Team of serial media
entrepreneurs
Over $40 million
invested
Global
Presence
Founded 2003
U.S. (HQ- Los Angeles)
Jerusalem
Mumbai
Tokyo
About Catch Media
22
Strategic Investors
The Platform is Designed to Drive
Customer Lifetime Value
Deep Analytics and Contextual Engagement
leveraging Metadata
Catch Media Analytics & Engagement (CM A&E) End to End Platform
Tailored for the Content Industry
Catch Media Analytics & Engagement
Confidential 2018 - Catch Media Inc. |23
 300+ Millions of users tracked
 Millions of pieces of metadata processed
 10s of Billions of transactions processed and growing
 Pioneers of third party media cloud and clearinghouse and persona based customer
lifetime value workflow system
 75+ patents, 9 patent family groups
 Deployed globally including U.S.A., India, Japan, Hong Kong, Middle East, Thailand, Ukraine
 Leading telcos, content owners, e-tailers, and content distributors have signed on
Scale
Innovation
Market
Validation
24
Leading the Industry
Use cases
Challenge: Subscriber Churn
• Music subscription renewing this week
• Has the consumer been listening / using the service? What music do they like?
• How do you send a consumer a targeted playlist of songs they like in order to engage them?
Challenge: Consumer Satisfaction
• When the consumer turns on their TV, why do they have to sift through 100s of channels?
• What shows have they watched? What season / episode are they on?
• How do you present a choice of shows / channels that they would like to watch ?
Understanding meta-data and consumer content consumption behavior is key to solving
Customer Loyalty!
Technical Challenge
26
Provide a solution which in near real-time can:
• Filter, pivot and query up to date and historical data at a granular level.
• Segment audiences and provide each consumer with individualized content offerings.
• Ability to handle streams of updates from an SDK as well as large batches i.e. 1 billion records from a content
distributor
• Provide the option of deploying in private / public cloud or on-prem.
Previous solution and alternatives:
• InfiniDB – not scaleable and end of life.
• Tested Teradata, Redshift, Big Query, Green Plum and a number of other solutions.
• Twingo facilitated Catch Media piloting Vertica successfully.
Vertica benefits
27
Vertica provides Catch Media
with the necessary flexibility and capabilities
Benefits of Vertica over others:
• Ability to do joins so we can handle one to many relationships (like genres)
• Updates to data which generally big data platforms don’t like (to handle EPG updates)
• Price performance / data retrieval
• Host in cloud or on prem
• Unlimited historical querying without need for pre-aggregation
New Economy
Vertica Analytics Database general overview
The Key Use cases for Vertica
 Behavioral Analytics with AB testing
 Funnel Analytics - Understanding the
Conversion Funnel Right from the Start
 Predictive Modeling – i.e. Product
Recommendation
31
Sportium
Overview
• The first Sportium betting store in Madrid was opened in
2008. In 2013, the company launched the web version of
Sportium, starting its online journey to become the multi-
channel company of choice in the betting industry.
• Sportium also manages more than 3,000 points of sale
throughout Spain. With 350,000 betting transactions daily,
it is the number one betting provider in Spain, and looking
to expand internationally to the Latin America markets
Background of the Project
o Two fully separated BI systems for Retail and Digital channelsTecnología tradicional en
ambos entornos
o BI systems managed by third parties
o Use of Excels extension to fill the deficiencies of BI systems
o Complexity for security management
o Static reports
BI UsersRetail
Digital
Objectives of the project
Data WareHouse Sportium
o BI solution dedicated and managed by Sportium
o Unification of business data (Retail + Digital)
o Source of operational data for real-time data analysis (i.e. CRM / VIP)
o Integration with third-party analysis / BI tools
Data Analysts, BI Users, Third party users, B2B
DBETL BI
RFP – Market analysis
Scalability
8/10
Future growth
vs 4/10
Performance
7/10
Consultation
speed and
load in relation
to the current
platform
vs 7.5/10
User Experience
8/10
Utilities, Tools,
SQL etc.
vs 4/10
Imtegracion
8/10
Integration
with the ETL
and BI layers
vs 7/10
Vertica - POC
Vendor Support
8/10
Support by the
provider during
the POC
vs 4/10
37
Vertica Analytics Database general overview
Success story - Taboola
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0
20
40
60
80
100
120
140
07/2015
04/2016
07/2016
08/2016
11/2016
12/2016
08/2017
04/2018
07/2018
03/2019
Taboola Growth
# Nodes Data in TB
What Next
Vertica CE
41
21
A History of Separation and Integration
Vertica Big Data Conference
Encore Boston Harbor Hotel
March 30 – April 2, 2020
www.vertica.com/bdc2020
Vertica Analytics Database general overview
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Vertica Analytics Database general overview

  • 1. Analytics is the key to unlock digital transformation… Amit Manor, Vertica Channel Director EMEA
  • 2. Table of Contents  Why Now, Why Change  What is Vertica  How Vertica Delivers Business Values  Next Steps 2
  • 3. Our Time is Now! 3 • Traditional DW companies are struggling • Freedom to Deploy Everywhere • Machine learning is everywhere • Hadoop hangover • Open source technologies are not free!
  • 4. Legacy EDWs Data Lakes Declining performance at scale Built on aging technology Expensive w/ proprietary hardware Limited deployment options Cheap storage of Big Data Limited analytics capabilities Poor performance Lacks governance & security Raison d’être Bridging the gap between high cost legacy EDWs and Hadoop data lakes
  • 5. What Is Vertica and how we transform the Enterprises
  • 6. 6 A History Of Innovation 6 The journey from Ingres to Postgres to C-Store
  • 7. What is Vertica? 7 SQL Database Load and store data in a data warehouse designed for blazing fast analytics Query Engine Ask complex analytical questions and get fast answers regardless of where the data resides Vertica is an advanced analytics platform built for the scale and complexity of today’s data-driven world. It combines the power of a high-performance, MPP query engine with advanced analytics and machine learning. Analytics & ML Create, train and deploy advanced analytics and machine learning models at massive scale
  • 8. 8 An Open Architecture with Rich Ecosystem Integrations
  • 9. Future-proof your analytics 9 The data storage decisions you make today won’t impact your ability to execute in the future SQL Database ++ Analytics & ML Access one unified analytics engine and license across all infrastructure choices Choose your Deployment Choose your Consumption On Prem Choose your Cloud Compute StorageHardware AgnosticHybrid Cloud Query Engine
  • 10. End-to-end machine learning management 10 Vertica supports the entire predictive analytics process Data Analysis Data Preparation Modeling Evaluation Deployment • Statistical Summary • Time Series • Sessionize • Pattern Matching • Date/Time Algebra • Window Partition • Sequences • And more… • Outlier Detection • Normalization • Imbalanced Data Processing • Sampling • Missing Value Imputation • And More… • SVM • Random Forests • Logistic Regression • Linear Regression • Ridge Regression • Naïve Bayes • Cross Validation • And More… • Model-level Stats • ROC Tables • Error Rate • Lift Table • Confusion Matrix • R-Squared • MSE • And More… • Deploy Anywhere • In Database Scoring • Massively Parallel Processing • Speed • Scale • Security • And More… SQL Database ++ Analytics & ML Query Engine
  • 11. How Vertica delivers business value
  • 13. Three Cross-Industry Business Strategies – At A Glance Examples by Industry where analytics is required to compete Strategy Healthcare Retail Telco IoT Marketing/Ad Serving IT Infrastructure Financial Services I. CUSTOMER EXPERIENCE MANAGEMENT Faster service Lower bills Population Health Initiatives Enhanced Shopping Experience Subscriber expansion Predictive Maintenance Ad targeting Application Performance Investment management and modelling II. OPERATIONAL ANALYTICS Hospital Efficiency Pricing and Inventory Management Infrastructure Optimization Supply Chain Efficiency Improved customer interest based on target marketing Dynamic resource management Real-time Comparative Analytics III. ASSURANCE AND FRAUD DETECTION Healthcare fraud detection Payer protection Provider malpractice Credit card fraud loss prevention Voice, video and data reliability SIM Card Fraud Smart Meter Management Spam prevention Ad Delivery Traffic optimization and Authorized Access Management Authorized access and fraud detection
  • 14. Telecommunications – Use Cases 14 Analyze billions of usage records to understand overall network health and identify areas to optimize network performance and reliability Assess network load patterns, predict how new services will impact bandwidth, and what new capacity might be needed under future scenarios Analyze CDR and customer data to develop targeted promotions that attract and retain new and existing customers, reduce churn and increase profitability Network Monitoring and Optimization Capacity Planning and Management Customer Behavior and Churn Analytics Comply with new and emerging regulations regarding historical data retention and mandated response SLAs for government queries Regulatory Compliance
  • 15. 15  In AT&T’s Next Generation White Paper, they wrote “Vertica has emerged as the primary alternative to engineered Teradata Data Warehouse workloads. Vertica is a software- only solution that deploys on commodity servers. Initiatives are currently underway looking for Teradata candidate instances to migrate to alternative solutions like Vertica. Vertica is architected to provide continuous data loading and querying capabilities to thousands of concurrent users.”  They continued: “There are several “anchor” architectural elements that have emerged in the DW/Big Data ecosystem which we consider a part of our long-term strategy. Among them are Vertica, Hortonworks Data Platform and MicroStrategy Analytics.” Telco - AT&T
  • 16. Success in IOT/Manufacturing • BMW uses Vertica to analyse patterns in sensor data to minimize app defects • Vertica powers analytics for Trane Intelligent Services business • Eight times faster than Hive and a tight integration with Hadoop allowed us to best German-based Exasol • Delivers efficient and faster car development through a more effective error analysis from the telematics on the test fleet. • Use of Eon allowed Philips to scale from 500 TBs to over a PB of data economically • Focus on improving patient monitoring equipment, reduce costs and improve customer satisfaction. • Increases customer value with equipment monitoring, event mitigation, & energy performance services • Helps customers reduce energy & maintenance costs • Vertica delivers predictive maintenance on over 30,000 Imaging Devices WW.
  • 17. And the most mature OEM program in analytics…
  • 18. 18 Allow user-defined functions (UDx) Require minimal administration Manage huge data volumes Deliver fast analytics Embed machine learning Support data scientists Handle high user concurrency OEM software vendors need an embedded analytics software platform that can: Automated Analytics
  • 19. Open architecture Optimized data storage Easy set-up and administration Blazing fast analytics Massive scalability Vertica Platform as Analytics OEM Engine OEM engine to drive real-time analytics and ML to monetize all of your data at massive scale In-database advanced analytics and ML Value Proposition: OEM Engine for ISVs
  • 20. Vertica OEM Customers - Worldwide 20
  • 21.  Catch Media implemented a data analytics platform capable of tracking hundreds of millions of users, with tens of billions of data event transactions processed in near-real-time on a monthly basis, with no data aggregation or reduction in query performance or feature limitations.  Resulted in 50% increase in engagement through data-driven segmentation, management of one-to-many relationships, flexible data hosting options, and unlimited historical data querying without the need to pre- aggregate Delivering data-driven personal insight into 300+ million users
  • 22. Team of serial media entrepreneurs Over $40 million invested Global Presence Founded 2003 U.S. (HQ- Los Angeles) Jerusalem Mumbai Tokyo About Catch Media 22 Strategic Investors
  • 23. The Platform is Designed to Drive Customer Lifetime Value Deep Analytics and Contextual Engagement leveraging Metadata Catch Media Analytics & Engagement (CM A&E) End to End Platform Tailored for the Content Industry Catch Media Analytics & Engagement Confidential 2018 - Catch Media Inc. |23
  • 24.  300+ Millions of users tracked  Millions of pieces of metadata processed  10s of Billions of transactions processed and growing  Pioneers of third party media cloud and clearinghouse and persona based customer lifetime value workflow system  75+ patents, 9 patent family groups  Deployed globally including U.S.A., India, Japan, Hong Kong, Middle East, Thailand, Ukraine  Leading telcos, content owners, e-tailers, and content distributors have signed on Scale Innovation Market Validation 24 Leading the Industry
  • 25. Use cases Challenge: Subscriber Churn • Music subscription renewing this week • Has the consumer been listening / using the service? What music do they like? • How do you send a consumer a targeted playlist of songs they like in order to engage them? Challenge: Consumer Satisfaction • When the consumer turns on their TV, why do they have to sift through 100s of channels? • What shows have they watched? What season / episode are they on? • How do you present a choice of shows / channels that they would like to watch ? Understanding meta-data and consumer content consumption behavior is key to solving Customer Loyalty!
  • 26. Technical Challenge 26 Provide a solution which in near real-time can: • Filter, pivot and query up to date and historical data at a granular level. • Segment audiences and provide each consumer with individualized content offerings. • Ability to handle streams of updates from an SDK as well as large batches i.e. 1 billion records from a content distributor • Provide the option of deploying in private / public cloud or on-prem. Previous solution and alternatives: • InfiniDB – not scaleable and end of life. • Tested Teradata, Redshift, Big Query, Green Plum and a number of other solutions. • Twingo facilitated Catch Media piloting Vertica successfully.
  • 27. Vertica benefits 27 Vertica provides Catch Media with the necessary flexibility and capabilities Benefits of Vertica over others: • Ability to do joins so we can handle one to many relationships (like genres) • Updates to data which generally big data platforms don’t like (to handle EPG updates) • Price performance / data retrieval • Host in cloud or on prem • Unlimited historical querying without need for pre-aggregation
  • 30. The Key Use cases for Vertica  Behavioral Analytics with AB testing  Funnel Analytics - Understanding the Conversion Funnel Right from the Start  Predictive Modeling – i.e. Product Recommendation
  • 31. 31
  • 32. Sportium Overview • The first Sportium betting store in Madrid was opened in 2008. In 2013, the company launched the web version of Sportium, starting its online journey to become the multi- channel company of choice in the betting industry. • Sportium also manages more than 3,000 points of sale throughout Spain. With 350,000 betting transactions daily, it is the number one betting provider in Spain, and looking to expand internationally to the Latin America markets
  • 33. Background of the Project o Two fully separated BI systems for Retail and Digital channelsTecnología tradicional en ambos entornos o BI systems managed by third parties o Use of Excels extension to fill the deficiencies of BI systems o Complexity for security management o Static reports BI UsersRetail Digital
  • 34. Objectives of the project Data WareHouse Sportium o BI solution dedicated and managed by Sportium o Unification of business data (Retail + Digital) o Source of operational data for real-time data analysis (i.e. CRM / VIP) o Integration with third-party analysis / BI tools Data Analysts, BI Users, Third party users, B2B
  • 35. DBETL BI RFP – Market analysis
  • 36. Scalability 8/10 Future growth vs 4/10 Performance 7/10 Consultation speed and load in relation to the current platform vs 7.5/10 User Experience 8/10 Utilities, Tools, SQL etc. vs 4/10 Imtegracion 8/10 Integration with the ETL and BI layers vs 7/10 Vertica - POC Vendor Support 8/10 Support by the provider during the POC vs 4/10
  • 37. 37
  • 39. Success story - Taboola 0 200 400 600 800 1000 1200 1400 1600 1800 2000 0 20 40 60 80 100 120 140 07/2015 04/2016 07/2016 08/2016 11/2016 12/2016 08/2017 04/2018 07/2018 03/2019 Taboola Growth # Nodes Data in TB
  • 42. 21 A History of Separation and Integration Vertica Big Data Conference Encore Boston Harbor Hotel March 30 – April 2, 2020 www.vertica.com/bdc2020