SlideShare a Scribd company logo
1 of 16
The$Evolu*on$of$Data$Analysis$with$
Hadoop$
Tom$Wheeler$ |$$StampedeCon$2014$
About$the$Presenta*on…$
•  What’s$ahead$
•  Defining$Hadoop$
•  Data$Processing$with$MapReduce$
•  Simplifying$Development$with$Apache$Crunch$
•  Bringing$MapReduce$to$Analysts$with$Apache$Hive$
•  GeMng$Results$Faster$with$Cloudera$Impala$
•  Finding$Data$Made$Easy$with$Apache$Solr$/$Cloudera$Search$
•  Conclusion$+$Q&A$
Important$Trends$
•  Ubiquitous$connec*vity$
•  We$produce$more$data$than$ever$
•  UserVgenerated$content$
•  Lacks$rigid$structure$
•  Inexpensive$storage$
•  Permanent$reten*on$
f
Big$Data$Can$Mean$Big$Opportunity$
•  One$tweet$is$an$anecdote$
•  But$a$million$tweets$can$signal$important$trends$
•  One$person’s$product$review$is$an$opinion$
•  But$a$million$reviews$might$reveal$a$design$flaw$
•  One$person’s$diagnosis$is$an$isolated$case$
•  But$a$million$medical$records$could$lead$to$a$cure$
What$is$Apache$Hadoop?$
•  Distributed$data$storage$and$processing$
•  Scalable,$flexible,$and$economical$
•  Open$source$
•  Inspired$by$Google$
•  Two$main$components$
•  Hadoop$Distributed$File$System$(HDFS)$
•  MapReduce$
GeMng$Data$into$HDFS$
•  HDFS$is$dis*nct$from$your$local$filesystem$
Local Filesystem
Hadoop Distributed
File System (HDFS)
Local Filesystem
What$is$MapReduce?$
•  MapReduce$is$a$programming)model)
•  You$supply$two$processing$func*ons:$Map$and$Reduce$
•  Map:$typically$used$to$transform,$parse,$or$filter$data$
•  Reduce:$typically$used$to$summarize$results$(op*onal)$
•  MapReduce$in$Hadoop$is$batchVoriented$
Why$MapReduce?$
•  MapReduce$simplifies$parallel$processing$
•  Code$is$typically$wricen$in$Java$
•  Shields$developers$from$complexity$of$distributed$compu*ng$
•  No$explicit$synchroniza*on,$network$sockets,$or$file$I/O$
•  S*ll,$it$is$tedious$to$write$MapReduce$directly…$
But$MapReduce$is$like$Assembly$Language…$
•  MapReduce$is$powerful$and$scalable$
•  But$wri*ng$MapReduce$code$directly$in$Java$can$be$tedious$
•  Business$logic$typically$comprises$just$a$frac*on$of$overall$code$
•  Many$realVworld$computa*ons$involve$a$sequence$of$jobs$
•  Chaining$mul*ple$MapReduce$jobs$increases$the$complexity$
•  Apache$Crunch$is$designed$to$address$these$problems$
What$is$Apache$Crunch?$
•  Apache$Crunch$is$a$library$that$simplifies$parallel$processing$
•  OpenVsource$implementa*on$of$Google's$internal$library$
•  Provides$a$highVlevel$API$targeted$at$Java$developers$
•  No$detailed$knowledge$of$MapReduce$required$
•  Faster$and$easier$than$wri*ng$MapReduce$code$directly$
•  Retains$the$power$and$expressiveness$of$Java$
What$is$Apache$Hive?$
•  HighVlevel$data$processing$on$Hadoop$
•  Another$alterna*ve$to$wri*ng$MapReduce$code$
•  Queries$data$in$HDFS$using$a$SQLVlike$language$
SELECT customers.cust_id, SUM(cost) AS total
FROM customers
JOIN orders
ON customers.cust_id = orders.cust_id
GROUP BY customers.cust_id
ORDER BY total DESC;
Hive$Data$and$Metadata$
•  As$with$a$database,$you$query$one$or$more$tables$
•  Hive$tables$are$just$a$façade$for$a$directory$of$data$in$HDFS$
•  Default$file$format$is$delimited$text,$but$many$others$supported$
•  Table$structure$and$loca*on$are$specified$during$crea*on$
•  Metadata$is$stored$in$an$RDBMS$
•  Tables$can$be$populated$by$loading$$
data$into$HDFS$directory$
Data$in$HDFS
mytable
1
2
Metastore
What$is$Cloudera$Impala?$
•  Massively$parallel$SQL$engine$for$Hadoop$
•  Supports$ad$hoc$/$interac*ve$queries$on$data$in$HDFS$
•  Uses$custom$execu*on$engine$instead$of$MapReduce$
•  Query$syntax$virtually$iden*cal$to$HiveQL$/$SQL$
•  Shares$metadata$with$Hive$
•  Much,$much$faster$than$Hive$
•  Impala$is$100%$open$source$(ApacheVlicensed)$
Apache$Solr$(and$Cloudera$Search)$
•  Apache$Solr$provides$highVperformance$indexing$and$search$
•  Mature$plajorm$with$widespread$deployment$
•  Requires$licle$technical$skill$for$end$users,$yet$s*ll$powerful$
•  Cloudera$integrates$Solr$to$search$data$in$HDFS $$
•  CDH$offers$scalability$and$reliability$
•  Distributed$data$storage$and$indexing$
•  Cloudera$Search$is$open$source,$just$like$Apache$Solr$itself$
Conclusion$
•  Thanks$for$having$me!$
•  Any$ques*ons?$
The Evolution of Data Analysis with Hadoop - StampedeCon 2014

More Related Content

Viewers also liked

Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)
Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)
Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)Spark Summit
 
Hadoop and Hive in Enterprises
Hadoop and Hive in EnterprisesHadoop and Hive in Enterprises
Hadoop and Hive in Enterprisesmarkgrover
 
A Non-Standard use Case of Hadoop: High Scale Image Processing and Analytics
A Non-Standard use Case of Hadoop: High Scale Image Processing and AnalyticsA Non-Standard use Case of Hadoop: High Scale Image Processing and Analytics
A Non-Standard use Case of Hadoop: High Scale Image Processing and AnalyticsDataWorks Summit
 
Introduction to Spark (Intern Event Presentation)
Introduction to Spark (Intern Event Presentation)Introduction to Spark (Intern Event Presentation)
Introduction to Spark (Intern Event Presentation)Databricks
 
Part 1: Lambda Architectures: Simplified by Apache Kudu
Part 1: Lambda Architectures: Simplified by Apache KuduPart 1: Lambda Architectures: Simplified by Apache Kudu
Part 1: Lambda Architectures: Simplified by Apache KuduCloudera, Inc.
 
Large-scale social media analysis with Hadoop
Large-scale social media analysis with HadoopLarge-scale social media analysis with Hadoop
Large-scale social media analysis with Hadoopjakehofman
 
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Cloudera, Inc.
 
Big Data - The 5 Vs Everyone Must Know
Big Data - The 5 Vs Everyone Must KnowBig Data - The 5 Vs Everyone Must Know
Big Data - The 5 Vs Everyone Must KnowBernard Marr
 
Big image analytics for (Re-) insurer
 Big image analytics for (Re-) insurer Big image analytics for (Re-) insurer
Big image analytics for (Re-) insurerFlavio Trolese
 
Impala 2.0 - The Best Analytic Database for Hadoop
Impala 2.0 - The Best Analytic Database for HadoopImpala 2.0 - The Best Analytic Database for Hadoop
Impala 2.0 - The Best Analytic Database for HadoopCloudera, Inc.
 
Cloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for HadoopCloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for HadoopCloudera, Inc.
 
Impala: Real-time Queries in Hadoop
Impala: Real-time Queries in HadoopImpala: Real-time Queries in Hadoop
Impala: Real-time Queries in HadoopCloudera, Inc.
 
Introduction to Big Data/Machine Learning
Introduction to Big Data/Machine LearningIntroduction to Big Data/Machine Learning
Introduction to Big Data/Machine LearningLars Marius Garshol
 
Cloudera Impala technical deep dive
Cloudera Impala technical deep diveCloudera Impala technical deep dive
Cloudera Impala technical deep divehuguk
 

Viewers also liked (20)

Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)
Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)
Spark in the Hadoop Ecosystem-(Mike Olson, Cloudera)
 
Hadoop and Hive in Enterprises
Hadoop and Hive in EnterprisesHadoop and Hive in Enterprises
Hadoop and Hive in Enterprises
 
A Non-Standard use Case of Hadoop: High Scale Image Processing and Analytics
A Non-Standard use Case of Hadoop: High Scale Image Processing and AnalyticsA Non-Standard use Case of Hadoop: High Scale Image Processing and Analytics
A Non-Standard use Case of Hadoop: High Scale Image Processing and Analytics
 
Introduction to Spark (Intern Event Presentation)
Introduction to Spark (Intern Event Presentation)Introduction to Spark (Intern Event Presentation)
Introduction to Spark (Intern Event Presentation)
 
Video Analysis in Hadoop
Video Analysis in HadoopVideo Analysis in Hadoop
Video Analysis in Hadoop
 
Big Data Trends
Big Data TrendsBig Data Trends
Big Data Trends
 
Part 1: Lambda Architectures: Simplified by Apache Kudu
Part 1: Lambda Architectures: Simplified by Apache KuduPart 1: Lambda Architectures: Simplified by Apache Kudu
Part 1: Lambda Architectures: Simplified by Apache Kudu
 
Large-scale social media analysis with Hadoop
Large-scale social media analysis with HadoopLarge-scale social media analysis with Hadoop
Large-scale social media analysis with Hadoop
 
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
Hive, Impala, and Spark, Oh My: SQL-on-Hadoop in Cloudera 5.5
 
Big Data - The 5 Vs Everyone Must Know
Big Data - The 5 Vs Everyone Must KnowBig Data - The 5 Vs Everyone Must Know
Big Data - The 5 Vs Everyone Must Know
 
Big Data: Issues and Challenges
Big Data: Issues and ChallengesBig Data: Issues and Challenges
Big Data: Issues and Challenges
 
Big image analytics for (Re-) insurer
 Big image analytics for (Re-) insurer Big image analytics for (Re-) insurer
Big image analytics for (Re-) insurer
 
What is big data?
What is big data?What is big data?
What is big data?
 
Impala 2.0 - The Best Analytic Database for Hadoop
Impala 2.0 - The Best Analytic Database for HadoopImpala 2.0 - The Best Analytic Database for Hadoop
Impala 2.0 - The Best Analytic Database for Hadoop
 
Cloudera impala
Cloudera impalaCloudera impala
Cloudera impala
 
Cloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for HadoopCloudera Impala: A Modern SQL Engine for Hadoop
Cloudera Impala: A Modern SQL Engine for Hadoop
 
Impala: Real-time Queries in Hadoop
Impala: Real-time Queries in HadoopImpala: Real-time Queries in Hadoop
Impala: Real-time Queries in Hadoop
 
Introduction to Big Data/Machine Learning
Introduction to Big Data/Machine LearningIntroduction to Big Data/Machine Learning
Introduction to Big Data/Machine Learning
 
Cloudera Impala technical deep dive
Cloudera Impala technical deep diveCloudera Impala technical deep dive
Cloudera Impala technical deep dive
 
Big data ppt
Big  data pptBig  data ppt
Big data ppt
 

Similar to The Evolution of Data Analysis with Hadoop - StampedeCon 2014

DMPTool Workshop University of Georgia
DMPTool Workshop University of GeorgiaDMPTool Workshop University of Georgia
DMPTool Workshop University of GeorgiaSherry Lake
 
Defcon 22-graham-mc millan-tentler-masscaning-the-internet
Defcon 22-graham-mc millan-tentler-masscaning-the-internetDefcon 22-graham-mc millan-tentler-masscaning-the-internet
Defcon 22-graham-mc millan-tentler-masscaning-the-internetPriyanka Aash
 
Why Personal Clouds Need A Network
Why Personal Clouds Need A NetworkWhy Personal Clouds Need A Network
Why Personal Clouds Need A NetworkPhil Wolff
 
FIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docx
FIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docxFIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docx
FIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docxmydrynan
 
Importance_of_the_end_user
Importance_of_the_end_userImportance_of_the_end_user
Importance_of_the_end_userNoah Spahn
 
Characteristics of a good researcher - am i a researcher?
Characteristics of a good researcher - am i a researcher?Characteristics of a good researcher - am i a researcher?
Characteristics of a good researcher - am i a researcher?Dr. Mazlan Abbas
 
KazooCon 2014 - Building Your Business: Behind the Numbers!
KazooCon 2014 - Building Your Business: Behind the Numbers!KazooCon 2014 - Building Your Business: Behind the Numbers!
KazooCon 2014 - Building Your Business: Behind the Numbers!2600Hz
 
WSO2Con USA 2015: Safe for Work: The Internet of Dirty Things
WSO2Con USA 2015: Safe for Work: The Internet of Dirty ThingsWSO2Con USA 2015: Safe for Work: The Internet of Dirty Things
WSO2Con USA 2015: Safe for Work: The Internet of Dirty ThingsWSO2
 
Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...
Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...
Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...Jennifer Davis
 
API's, Freebase, and the Collaborative Semantic web
API's, Freebase, and the Collaborative Semantic webAPI's, Freebase, and the Collaborative Semantic web
API's, Freebase, and the Collaborative Semantic webDan Delany
 
Devops kc meetup_5_20_2013
Devops kc meetup_5_20_2013Devops kc meetup_5_20_2013
Devops kc meetup_5_20_2013Aaron Blythe
 
With Great Data Comes Great Responsibility
With Great Data Comes Great ResponsibilityWith Great Data Comes Great Responsibility
With Great Data Comes Great ResponsibilityAndrea Wiggins
 
Bug Bounty Programs For The Web
Bug Bounty Programs For The WebBug Bounty Programs For The Web
Bug Bounty Programs For The WebMichael Coates
 

Similar to The Evolution of Data Analysis with Hadoop - StampedeCon 2014 (20)

DMPTool Workshop University of Georgia
DMPTool Workshop University of GeorgiaDMPTool Workshop University of Georgia
DMPTool Workshop University of Georgia
 
Defcon 22-graham-mc millan-tentler-masscaning-the-internet
Defcon 22-graham-mc millan-tentler-masscaning-the-internetDefcon 22-graham-mc millan-tentler-masscaning-the-internet
Defcon 22-graham-mc millan-tentler-masscaning-the-internet
 
Why Personal Clouds Need A Network
Why Personal Clouds Need A NetworkWhy Personal Clouds Need A Network
Why Personal Clouds Need A Network
 
FIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docx
FIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docxFIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docx
FIN$410$–$Fall$2015$ $ $$Major&Project&2&Individual!Spre.docx
 
Importance_of_the_end_user
Importance_of_the_end_userImportance_of_the_end_user
Importance_of_the_end_user
 
Characteristics of a good researcher - am i a researcher?
Characteristics of a good researcher - am i a researcher?Characteristics of a good researcher - am i a researcher?
Characteristics of a good researcher - am i a researcher?
 
KazooCon 2014 - Building Your Business: Behind the Numbers!
KazooCon 2014 - Building Your Business: Behind the Numbers!KazooCon 2014 - Building Your Business: Behind the Numbers!
KazooCon 2014 - Building Your Business: Behind the Numbers!
 
20091110startup2startup
20091110startup2startup20091110startup2startup
20091110startup2startup
 
WSO2Con USA 2015: Safe for Work: The Internet of Dirty Things
WSO2Con USA 2015: Safe for Work: The Internet of Dirty ThingsWSO2Con USA 2015: Safe for Work: The Internet of Dirty Things
WSO2Con USA 2015: Safe for Work: The Internet of Dirty Things
 
Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...
Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...
Magic Myth and the DevOps, ANTIDOTES TO LEARNED HELPLESSNESS AND FEAR CULTURE...
 
20100201hplabs
20100201hplabs20100201hplabs
20100201hplabs
 
20100201hplabs
20100201hplabs20100201hplabs
20100201hplabs
 
API's, Freebase, and the Collaborative Semantic web
API's, Freebase, and the Collaborative Semantic webAPI's, Freebase, and the Collaborative Semantic web
API's, Freebase, and the Collaborative Semantic web
 
Devops kc meetup_5_20_2013
Devops kc meetup_5_20_2013Devops kc meetup_5_20_2013
Devops kc meetup_5_20_2013
 
With Great Data Comes Great Responsibility
With Great Data Comes Great ResponsibilityWith Great Data Comes Great Responsibility
With Great Data Comes Great Responsibility
 
Wiggins Plenary PPSR2012
Wiggins Plenary PPSR2012Wiggins Plenary PPSR2012
Wiggins Plenary PPSR2012
 
20090422 Www
20090422 Www20090422 Www
20090422 Www
 
20091203gemini
20091203gemini20091203gemini
20091203gemini
 
20091203gemini
20091203gemini20091203gemini
20091203gemini
 
Bug Bounty Programs For The Web
Bug Bounty Programs For The WebBug Bounty Programs For The Web
Bug Bounty Programs For The Web
 

More from StampedeCon

Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...
Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...
Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...StampedeCon
 
The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017
The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017
The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017StampedeCon
 
Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017
Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017
Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017StampedeCon
 
Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...
Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...
Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...StampedeCon
 
How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017
How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017
How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017StampedeCon
 
Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017
Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017
Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017StampedeCon
 
Foundations of Machine Learning - StampedeCon AI Summit 2017
Foundations of Machine Learning - StampedeCon AI Summit 2017Foundations of Machine Learning - StampedeCon AI Summit 2017
Foundations of Machine Learning - StampedeCon AI Summit 2017StampedeCon
 
Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...
Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...
Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...StampedeCon
 
Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...
Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...
Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...StampedeCon
 
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017StampedeCon
 
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017
AI in the Enterprise: Past,  Present &  Future - StampedeCon AI Summit 2017AI in the Enterprise: Past,  Present &  Future - StampedeCon AI Summit 2017
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017StampedeCon
 
A Different Data Science Approach - StampedeCon AI Summit 2017
A Different Data Science Approach - StampedeCon AI Summit 2017A Different Data Science Approach - StampedeCon AI Summit 2017
A Different Data Science Approach - StampedeCon AI Summit 2017StampedeCon
 
Graph in Customer 360 - StampedeCon Big Data Conference 2017
Graph in Customer 360 - StampedeCon Big Data Conference 2017Graph in Customer 360 - StampedeCon Big Data Conference 2017
Graph in Customer 360 - StampedeCon Big Data Conference 2017StampedeCon
 
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017StampedeCon
 
Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017
Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017
Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017StampedeCon
 
Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...
Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...
Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...StampedeCon
 
Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...
Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...
Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...StampedeCon
 
Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016StampedeCon
 
Creating a Data Driven Organization - StampedeCon 2016
Creating a Data Driven Organization - StampedeCon 2016Creating a Data Driven Organization - StampedeCon 2016
Creating a Data Driven Organization - StampedeCon 2016StampedeCon
 
Using The Internet of Things for Population Health Management - StampedeCon 2016
Using The Internet of Things for Population Health Management - StampedeCon 2016Using The Internet of Things for Population Health Management - StampedeCon 2016
Using The Internet of Things for Population Health Management - StampedeCon 2016StampedeCon
 

More from StampedeCon (20)

Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...
Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...
Why Should We Trust You-Interpretability of Deep Neural Networks - StampedeCo...
 
The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017
The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017
The Search for a New Visual Search Beyond Language - StampedeCon AI Summit 2017
 
Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017
Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017
Predicting Outcomes When Your Outcomes are Graphs - StampedeCon AI Summit 2017
 
Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...
Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...
Novel Semi-supervised Probabilistic ML Approach to SNP Variant Calling - Stam...
 
How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017
How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017
How to Talk about AI to Non-analaysts - Stampedecon AI Summit 2017
 
Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017
Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017
Getting Started with Keras and TensorFlow - StampedeCon AI Summit 2017
 
Foundations of Machine Learning - StampedeCon AI Summit 2017
Foundations of Machine Learning - StampedeCon AI Summit 2017Foundations of Machine Learning - StampedeCon AI Summit 2017
Foundations of Machine Learning - StampedeCon AI Summit 2017
 
Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...
Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...
Don't Start from Scratch: Transfer Learning for Novel Computer Vision Problem...
 
Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...
Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...
Bringing the Whole Elephant Into View Can Cognitive Systems Bring Real Soluti...
 
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017
 
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017
AI in the Enterprise: Past,  Present &  Future - StampedeCon AI Summit 2017AI in the Enterprise: Past,  Present &  Future - StampedeCon AI Summit 2017
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017
 
A Different Data Science Approach - StampedeCon AI Summit 2017
A Different Data Science Approach - StampedeCon AI Summit 2017A Different Data Science Approach - StampedeCon AI Summit 2017
A Different Data Science Approach - StampedeCon AI Summit 2017
 
Graph in Customer 360 - StampedeCon Big Data Conference 2017
Graph in Customer 360 - StampedeCon Big Data Conference 2017Graph in Customer 360 - StampedeCon Big Data Conference 2017
Graph in Customer 360 - StampedeCon Big Data Conference 2017
 
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
 
Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017
Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017
Doing Big Data Using Amazon's Analogs - StampedeCon Big Data Conference 2017
 
Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...
Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...
Enabling New Business Capabilities with Cloud-based Streaming Data Architectu...
 
Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...
Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...
Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyz...
 
Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016
 
Creating a Data Driven Organization - StampedeCon 2016
Creating a Data Driven Organization - StampedeCon 2016Creating a Data Driven Organization - StampedeCon 2016
Creating a Data Driven Organization - StampedeCon 2016
 
Using The Internet of Things for Population Health Management - StampedeCon 2016
Using The Internet of Things for Population Health Management - StampedeCon 2016Using The Internet of Things for Population Health Management - StampedeCon 2016
Using The Internet of Things for Population Health Management - StampedeCon 2016
 

Recently uploaded

UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPathCommunity
 
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Nikki Chapple
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesKari Kakkonen
 
A Framework for Development in the AI Age
A Framework for Development in the AI AgeA Framework for Development in the AI Age
A Framework for Development in the AI AgeCprime
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Farhan Tariq
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfpanagenda
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfIngrid Airi González
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxLoriGlavin3
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
Scale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterScale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterMydbops
 
React Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App FrameworkReact Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App FrameworkPixlogix Infotech
 
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical InfrastructureVarsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructureitnewsafrica
 
Design pattern talk by Kaya Weers - 2024 (v2)
Design pattern talk by Kaya Weers - 2024 (v2)Design pattern talk by Kaya Weers - 2024 (v2)
Design pattern talk by Kaya Weers - 2024 (v2)Kaya Weers
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality AssuranceInflectra
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...Wes McKinney
 
Decarbonising Buildings: Making a net-zero built environment a reality
Decarbonising Buildings: Making a net-zero built environment a realityDecarbonising Buildings: Making a net-zero built environment a reality
Decarbonising Buildings: Making a net-zero built environment a realityIES VE
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsNathaniel Shimoni
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxLoriGlavin3
 

Recently uploaded (20)

UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to Hero
 
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examples
 
A Framework for Development in the AI Age
A Framework for Development in the AI AgeA Framework for Development in the AI Age
A Framework for Development in the AI Age
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdf
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
Scale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterScale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL Router
 
React Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App FrameworkReact Native vs Ionic - The Best Mobile App Framework
React Native vs Ionic - The Best Mobile App Framework
 
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical InfrastructureVarsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructure
 
Design pattern talk by Kaya Weers - 2024 (v2)
Design pattern talk by Kaya Weers - 2024 (v2)Design pattern talk by Kaya Weers - 2024 (v2)
Design pattern talk by Kaya Weers - 2024 (v2)
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
 
Decarbonising Buildings: Making a net-zero built environment a reality
Decarbonising Buildings: Making a net-zero built environment a realityDecarbonising Buildings: Making a net-zero built environment a reality
Decarbonising Buildings: Making a net-zero built environment a reality
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directions
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
 

The Evolution of Data Analysis with Hadoop - StampedeCon 2014