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Verizon Centralizes Data
into a Data Lake in Real
Time for Analytics
© 2017 Attunity
Sanjay Kumar
General Manager, Telecom - Hortonworks
Arvind Rajagopalan
Director – Global Technology Services – Verizon
Jordan Martz
Director of Technology Solutions - Attunity
Guest Speakers
© 2017 Attunity
• Hortonworks - Hortonworks Data Platform (HDP) for the
telecommunications market
• Verizon - How we centralized data into a data lake for analytics
• Attunity - Migrating real-time data
• All - Q&A
Agenda
• Hortonworks Data Platform (HDP) for
the telecommunications market
5 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
The	New	Landscape	of	the	Telecom	Industry
Service	Providers
Social	Media	&	Mobile:	
Explosion	of	rich	customer	
data	through	Social	Media	
and	Mobile	Apps	for	
customer	sentiment	&	
Interests	
Customer	Expectation:	
With	the	cultural	impact	of	
web	and	mobile,	customers	
are	expecting	greater	levels	
of	service	and	
responsiveness
Competitive	Differentiation:
As	other	service	providers	deliver	
similar	levels	of	telecom	service	and	
coverage,	other	areas	of	service	levels	
are	needed
New	Digital	Ecosystem:	
Greater	value	of	Data	on	
digital	ecosystem	for	
Customers	and	Partners	
driving	Data	Monetization
Internet	Of	Things:
Explosion	of	data	from	
IOT	with	benefits	aligned	
with	insight	not	
correlated	to	data	
volumes
6 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Service Providers Areas of Focus
Customer	Experience	&	Marketing
- Enhance	End-to-end	Experience	of	Customer
- Become	Trusted	Partner	to	Customer	
- Awareness	of	customer’s	needs	when	and	where	needed
New	Business	&	Consumer	Services
- New	Digital	&	Infrastructure	Services	
- Data	Monetization
- M2M,	IoT,	Analytics-as-a	service
Network	Optimization
- Move	to	Software	Driven	Networks
- Leverage	Network	Data	Assets
- Self	optimizing	and	provisioning Customer
Network Service
7 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
DATA-CENTRIC
Old	Model:	App-Centric
Limitations:
• Multiple	copies	of	data
• Difficult	cross-system	integration
• Upper-limit	on	data	volumes	
before	harming	performance
New	Model:	Data-Centric
Advantages:
• One	version	of	the	data
• No	need	for	cross-app	integration
• System	scales	linearly
APP-CENTRIC
App1 App	2 App	3 App	4 App	5 App	6
App	Centric	will	break	down	
with	x10,	x100,x1000…
Need	to	shift	to	Data	Centric
8 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
The	Future	of	Data
Actionable	Intelligence
D AT A 	 I N 	 M O T I O N
STORAGE
STORAGE
GROUP	2GROUP	1
GROUP	4GROUP	3
D ATA 	 AT 	 R E S T
INTERNET
OF
ANYTHING
Combining	Data-in-Motion	and	Data-at-Rest	
powers	Actionable	Intelligence
9 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Streaming	
Injestion
(HDF)
Streaming:	Network	
Probes,	Click	Stream,	
Sensor,	Location	
Batch:	Call	
Detail	Records	
On-Line:	Customer
Sentiment	
Unstructured:	Txt,
Pictures,	Video,
Voice2Text	
Clickstream
Web	&	Social
Geolocation
Event	Records
Call	Logs
Files,	emails
Server	Logs
Existing	OSS/BSS/DWH
App	1 App	2 App	3 App	4 App	5 App	6
IOT Solutions
Analytic
Services
Network
Planning
Optimization
Contextual
Marketing
360 Customer
Awareness
Data	Driven	Business	
DELIVERY
Personal	Data	Analysis	&	
Customer	Insight	Services
To	Customers	&	Partners
10 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Social	
Media
Sentiment
Call	Center
Interaction
Lifestyle	&	
Interests
Streaming	
Injestion
(HDF)
Streaming:	Network	
Probes,	Click	Stream,	
Sensor,	Location	
Batch:	Call	
Detail	Records	
On-Line:	Customer
Sentiment	
Unstructured:	Txt,
Pictures,	Video,
Voice2Text	
How	to	See	What	the	Customer	Sees	and	
Respond	with	Awareness
– View	from	The	Customer	(360	degree	view)
• Quality	of	Service	Experience	 (Network	details)
• Call	Center	dialog	(voice	to	text	analysis)
• Customer	Interaction	Channel	(CRM,	Billing)
• Customer’s	Sentiment	(what	they	are	saying	on	social	
media)
– Understanding	Current	State	of	the	Customer
• All	key	customer	metrics	attributes	and	references	
within	a	dynamic	customer	profile	
• Net	Promoter	Score	(dynamically	computed)
• Churn	Score
• Appetite	for	Information	&	other	Customer	Metrics
• Target	Advertising	Profile
– Next	Best	Actions
• Context	aware	promotions
• Churn	risk	response
• Retail	Store	with	State	of	the	Customer
• Omni-channel	correlated	actions
Quality
of	Service
via
Network
Customer
Experience
Via
BSS
11 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Business	Functions
Customer
Go-to-market
Cyber
Security
Hadoop-
as-a-service
M2M/IoT
Solutions
Personal	
Intelligence
Industry
Brokering
IT	Operations
EDW	Data	Offload HDP	
Landing	Zone
HDP	
Data	Lake
Real-time	Streaming
HDP	Data	Lake
360 Customer
Household
View
Dynamic
Customer
Profile
Next Best
Action
Location &
Context Based
CEM
- Customer	Experience
Target
Audience
Profile
Context Aware
Target
Marketing
Location &
Context Based
Promotions
- Marketing
Threat
Detection
Real-Time
Threat
Analytics
Dynamic
Pattern
Detection
- Security
Next Best
Network
Investment
Equipment
Predictive
Maintenance
Customer
Aware Network
Provisioning
- Network
Customer
Sentiment &
Churn
Dynamic
Network
Provisioning
Network
Decommissioning
© 2017 Attunity
C
R
M
Streaming
Injestion
(HDF)
Call Center Voice to Text
Social Media Feeds (Twitter..)
CDRs or Network Probe
© 2017 Attunity
Customer
Sentiment &
Churn
360 Customer
Household
View
Dynamic
Customer
Profile
Next Best
Action
Location &
Context Based
CEM
Target
Audience
Profile
Context Aware
Target
Marketing
Location &
Context Based
Promotions
• How we centralized data into a data lake
for analytics
Migrating real-time data
© 2017 Attunity
Attunity Corporate Overview
Data Integration & Big Data Management Software
Accelerate data deliveryand availability
Automate data readiness for analytics
Optimize data management with intelligence
§Hadoop & Big Data
§Databases & Data Warehouses
§On premise & in the Cloud
Solutions for: Global OfficesOverview
§2000 customers in 65 countries
§250 people and growing
§NASDAQ traded (ATTU)
© 2017 Attunity
Seamless integration with Hortonworks Connected Data platforms
and solutions
Hortonworks
Connection
HortonworksSolutions
Enterprise Data
WarehouseOptimization
Cyber Security and
Threat Management
Internet of Things
and Streaming Analytics
Hortonworks Connection
Subscription Support
SmartSense
Premier Support
Educational Services
Professional Services
Community Connection
Cloud
Hortonworks Data Cloud
AWS HDInsight
Data Center
Hortonworks Data Suite
HDFHDP
© 2017 Attunity
Real-time Data Ingest with Attunity Replicate
SOURCES
OLTP,	ERP,
CRM	Systems
Documents,	
Emails
Web Logs,
Click Streams
Social	
Networks
Machine	
Generated
Sensor
Data
Geolocation	
Data
Attunity Replicate for HDP & HDF
Accelerate time-to-insights by delivering solutions
faster, with fresh data, from many sources
- Automated data ingest
- Incremental data ingest (CDC)
- Support for multiple sources
© 2017 Attunity
Attunity Replicate architecture
Transfer
TransformFilter
Batch
CDC Incremental
In-Memory
File Channel
Batch
Hadoop
Files
RDBMS
Data Warehouse
Mainframe
Cloud
On-prem
Cloud
On-prem
Hadoop
Files
RDBMS
Data Warehouse
Kafka
Persistent Store
© 2017 Attunity*Supported underearly access program
Attunity Replicate sources and targets
RDBMS
Oracle
SQL Server
DB2 iSeries
DB2 z/OS
DB2 LUW
MySQL
PostgreSQL
Sybase ASE
Informix
DW
Exadata
Teradata
Netezza
Vertica
Hortonworks
Cloudera
MapR
Hadoop
DB2 for z/OS
IMS/DB
VSAM
SQL M/P
Enscribe
RMS
HP NonStop
Mainframe
AWS RDS
Salesforce
Cloud
RDBMS
Oracle
SQL Server
DB2 LUW
MySQL
PostgreSQL
Sybase ASE
Informix
DW
Microsoft PDW
Exadata
Teradata
Netezza
Vertica
Sybase IQ
Amazon Redshift
Actian Vector
SAP HANA
Hortonworks
Cloudera
MapR
Pivotal
Amazon EMR
Hadoop
MongoDB
NoSQL
Amazon RDS
Amazon Redshift
Amazon EMR
Google Cloud SQL
Google Cloud Dataproc
Azure SQL Data
Warehouse
Azure SQL Database
Cloud
Azure Event
Hubs*
Kafka
Messaging
Targets
Sources
SAP
ECC on Oracle
ECC on SQL
ECC on DB2*
SAP
HANA
© 2017 Attunity
In Memory and File Optimized Data Transport
CDC for data-at-rest and data-in-motion
R1
R1
R2
R1
R2
R
1
R
2
Batch
CDC
Data Warehouse
Ingest-Merge
SQL
n 2 1
SQL SQL
Transactional CDC
Message
Encoded
CDC
Data Sources
Attunity	Replicate	–Change	Processing
CDC
Many Databases
and Data
Warehouses
....
© 2017 Attunity
CDC
Demo: Data Streaming into Kafka è HDF è HDP
MSG
n 2 1
MSG MSG
Data Streaming
Transaction
logs
In memory optimized metadata management
and data transport
Bulk
Load
MSG
n 2 1
MSG MSG
Data Streaming
Message
broker
Message
broker
© 2017 Attunity
Attunity Replicate for SAP
Universal, Real-Time and Simplified Data Integration
• Replicate your SAP applicationdata in bulk or real-
time for data analytics
§ Documents, transactions and business data
§ All core and industry-specific SAP modules
• Integrate real-time withall major targets
§ DBs, data warehouses, Hadoop – cloud or on premises
§ Decode SAP data from complex source structures
§ Enable business usage on common data model
• Move external data into SAP HANA
Attunity Replicate
Bulk
Load
CDC
Core and Industry-Specific
SAP Modules
RDBMS | EDW | Hadoop
On Premises or Cloud
Hadoop Data Lake
© 2017 Attunity
Attunity Replicate Server
TransformFilter
Batch
CDC Incremental
In-Memory
File Channel
Batch
Demo: Attunity Replicate
Persistent Store
Extract relationships for Pool andCluster Tables
RDBMS
(Oracle,DB2, etc.)
Redo/ Archive
logs
or
Journal
File
----------------
Transparent
Tables
On Premises
Hadoop RDBMS
Data
WarehouseKafka
Cloud
Attunity Replicate Agent for
SAP
SAP ECC
(Enterprise Central
Component)
Data Model Mapping
Pool/Cluster table RFC
© 2017 Attunity
Demo
attunity.com
Questions?
Thanks!

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Verizon Centralizes Data into a Data Lake in Real Time for Analytics

Editor's Notes

  1. [NOTE: Insert webinar directions here.]
  2. TALK TRACK Hortonworks is powering the future of data. Whether from data at rest or data in motion, we help our customers tap into all the data. We give the world’s leading companies and government agencies actionable intelligence to do things that were never before possible. [NEXT SLIDE]
  3. Hadoop Distribution with Yarn: Allows central source of data across all mediums of ingestion and interaction Existing & Legacy Systems can Contribute and Participate: May extend the life of existing and legacy systems from enriched data New Applications interact with Data Lake, not each other: Next Generation Apps build around data and can deliver to customers and partners
  4. Sentiment from Social Media How happy are customers with carrier? Churn Score if another member of social network leaves carrier? Customer Churn Score from Call Center Voice-2-text & voice tone: How happy are customers with carrier? What events have occurred that have introduced risk of customer churn? CDR with Social Media Bad QOS that has customer not happy with carrier?; Where to prioritized repairs & care service to customer to reduce chances of Churn? CDR for location with Social Media Where was customer when bad experience occurred?
  5. Enrich the Data Lake with all available customer interaction points Develop and Revise the Models that best get your customer metrics: Net Promoter Score, Customer Churn Score, Appetite for Information, Customer Target Profile, etc Deploy the Current State of the Customer with references and customer real-time metrics Computed (ML) from the Data Lake into a Dynamic Customer Profile that is available across business groups and systems
  6. What the industry cares about: Hadoop has moved out of test Enterprise Use Case Closer to Production Business impact Enterprise + Real-time VS Sqoop + Batch Attunity + Replicate High performance connectivity to Hadoop though native APIs for data ingest and publication Automated schema generation in Hcatalog Drag & drop configuration with Click-2-Replicate design High-speed data load options: Full reload with overwrite Insert only appends Change Data Capture(CDC) In-memory data filtering and transformation Monitoring dashboard with web-based metrics, alerts and log file management
  7. One of the reasons several large technology companies trust and rely on Attunity for their own solutions is because of the robust CDC capability that Replicate provides. There are several options that are built into the product that provide flexible and optimized ways to implement change data capture. In addition to applying transactions in real-time and in-order, Replicate can handle varying volumes of changes on the source systems by applying the changes in optimized batches to improve throughput and latency In order to provide high-speed data loads into data warehouse appliances, Replicate is integrated with native data warehouse loaders for fast data ingestion into the target and then changes are merged in the target. It does not rely on sub optimal ODBC for data loading into the ware house systems. And recently, Attunity added support to write changes in message encoded format that can be published to Kafka message brokers as well.