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IBM Spark Technology Center
Apache Big Data NA 2016
Leveraging Open Source Analytics for making game changing decisions
Luciano Resende IBM | Spark Technology Center
IBM Spark Technology Center 2
Apache Big Data Evolution
http://pepperdata.com/2014/06/the-10-hottest-words-at-hadoop-summit-2014/
IBM Spark Technology Center 3
Apache Big Data Evolution
IBM Spark Technology Center 4
Apache Big Data Evolution
IBM Spark Technology Center 5
The Analytics
Operating System
IBM Spark Technology Center
Enhanceit! Offerit!
Leverageit!
SparkTechnologyCenter@SF
ShippingwithBigInsights/
SparkasaService
Insideourproducts
At IBM, We Love Spark!
OpensourcedApache
SystemML
OpensourcedApacheQuarks
IBM Spark Technology Center
IBM is Building on Apache Spark IBM Analytics
IBM Commerce
IBM Watson
IBM Research
IBM Cloud
Image source: http://zdnet2.cbsistatic.com/hub/i/r/2015/06/15/1a23c9cd-74bc-4c8b-9e83-da45e977d97d/thumbnail/770x578/4a70eb03e79c794393d1d7d26bb34687/ibm-apache-spark.gif
IBM Spark Technology Center 8
How our customers are leveraging
open source analytics
IBM Spark Technology Center
The Weather Company Data volumes from weather are growing ! – ~30 billion API requests per day
– ~120 million active mobile users
- #3 most active mobile user base
– ~360 PB of traffic daily
– Billions of events per day (~1.3 M per sec)
– Keep data forever
The use case – Efficient batch + streaming analysis
– Self-service data science
– BI / Visualization tool support
IBM Spark Technology Center
Healthcare Enterprise Health Care Data Lakes – Improve how health care is delivered
– Collect and combine data from dozens of sources
– Clinical, Operational, Financial
– Inside and outside your enterprise
Benefits – Better medical outcomes for patients
– Control cost and improve quality
SystemML on Spark – Predictive Risk Modeling
– Right patient intervention relating to adverse heath events
10
IBM Spark Technology Center
Spark maps Customer Experience “journey”
The Challenge – Improve Customer satisfaction rates
– Multiple channels for customer iteractions
– Very large volumes of data
The need – Create a 360 degree view of a customer
– Stich all interactions across channels –
“Customer Experience Journey”
– Classify interaction sentiment and take necessary actions
PUB / SUB MQTT / WebSockets / Flume / Kafka
` ` `
Journey
Dashboards
Interaction & Journey Data
Voice & Text Data
IBM Spark Technology Center
12 Image source: http://az616578.vo.msecnd.net/files/2016/03/21/6359412499310138501557867529_thank-you-1400x800-c-default.gif