6. Vic&ms of our own success
Increasing scale
Nonstop growth in users, devices, end points
Prolifera3on of applica3ons and services
Global enterprise and service provider nets
Web-scale enterprises on the Internet
Hyperscale data centers
Increasing complexity
User/device diversity & heterogeneous networks
Increasing number of security threats
Cloud-based applica3ons and services
So5ware-defined, virtualized infrastructure
IoT adds another layer of complexity
1970 2020 1980 1990 2000 2010
Terminals
Mainframes
Minicomputers
PCs
Worksta3ons
LANs
Servers
WANs
Internet
Web 2.0
Mobile
Apps
XaaS
Cloud-na3ve
Web-scale
9. Big Data is the game changer
Huge volume of data
Distributed processing model
High velocity of data
Real-3me streaming analy3cs
Wide variety of data
Structured & semi-structured
Flexibility & performance
Schema-on-read analy3cs
Rich set of open APIs
RESTful, publish/subscribe pipelines
Machine learning & AI
Predic3ve analy3cs
Thriving open source community
13. Analy&cs-driven opera&onal & business intelligence
Streaming
telemetry
Fuse, enrich
& transform
Real-3me
analy3cs
Batch
analy3cs
Opera3onal
intelligence
Business
intelligence Big Data
IT
opera3ons
Security
opera3ons
Customer
Service
Network
opera3ons
DevOps
IT Planning
CXO
Marke3ng
Compliance
Business
opera3ons
Data at rest
Time scale: seconds / minutes
Time scale: hours / days
Analyze first,
then store
Opera3onal func3ons
Business func3ons
17. Pervasive visibility – open data models
• Network & elements
• Probes & NPBs
• Cloud infrastructure
• Apps & end points
Many data
sources
• Packet & flow data
• KPIs, network state
• Syslog, server state
• App & device data
Many data types
• Data cleansing,
filtering & processing
• Open data formats
• Modeling languages
Open data
normaliza3on
AggregaFon
InstrumentaFon
18. Big Data trends - technology
Publish/subscribe pipelines
Both data inges3on & extrac3on
Data normalizaFon / ETL
Major source of complexity
Open data formats & schemas
No one-size-fits-all data repository
In-memory, flash-based, disk-based
HDFS, NoSQL, key-value, column-oriented
No one-size-fits all analyFcs engine
Hadoop MapReduce batch processing
Spark & Storm streaming analy3cs
Support for SQL queries
Machine learning engines
19. Big Data trends - business
Industry-wide Big Data skills gap
Vendors, service providers & enterprises
Complex value chain
High degree of custom integra3on
Big Data is a moving target
Technology and product risk
Need for open, turnkey soluFons
Vendor-sourced, managed services or SaaS-based
Cloud-naFve implementaFons (public or private)
Elas3c, hyper-scalable, highly resilient
Both private cloud & public cloud