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...is a collective term for characteristics that the two institutions share.
·-- PUBLISHER -----·> O'Reilly Media, Inc.
·-- LECTURESHIP ---·> Strata Data Conference 2017
London, United Kingdom
·-- LECTURE DATE --·> 05-2017
05-2017 {Published}
·-- PERIOD in HRS--·> 01+
·-- SCALE ---------·> 32x50mb
·-- LECTURE LINK --·> https://goo.gl/TeY7pD
Strata is the largest data conference series in the world; the place
where cutting-edge science and new business fundamentals intersectùand
merge. This video compilation gives you total access to each of the 112
sessions, 19 tutorials, and 16 keynotes delivered at Strata London 2017.
Broad and deep as the Thames itself, you'll hear presentations on stream
processing and analytics, deep learning, big data and the Cloud, data-
driven business management, and cybersecurity. You'll enjoy overviews of
technologies and platforms like MicrosoftÆs Azure HDInsight, O'Reilly's
Oriole, BMC's Control-M, Google's TensorFlow, AWS Lambda, Twitter's
Heron, Intel's BigDL, as well as talks on almost every Apache ecosystem
tool available today, including Arrow, Beam, Cassandra, Druid, Flink,
Flume, HAWQ, Hive, Impala, Kafka, Kinetica, Kudu, MXNet, Presto, Spark,
Spark ML, Spark Streaming, and Spark SQL.
But Strata is more than topics and technologies, it's the people who
speak: Big Data visionaries like Luke Han (CEO, Kyligence) on Apache
Kylin use cases in China; Reynold Xin (Chief Architect, Databricks) on
Spark's API and engine evolutions; Eric Tilenius (CEO, Blue Talon) on
the EU's GDPR's potential for better data security; Duncan Ross
(Director, TES Global) on doing good with big data; M. C. Srivas (Chief
Data Architect, Uber) on the real-time intelligence that drives Uber;
and Anthony Goldbloom (CEO, Kaggle) on lessons learned from the million
(!) data scientists who participate in Kaggle's machine learning
competitions. This compilation gives you a front row view to each of
these speakers and to all of the 211 data leaders who spoke at Strata
London 2017. Highlights include:
Strata Business Summit ù A set of 36 sessions specifically curated for
the senior-level business executive and strategist, the Summit is the
missing MBA for data-driven business. It includes clear-eyed guidance
from Tim O'Reilly (Founder, O'Reilly Media) on the future of AI as a
jobs generator; every Executive Briefing; five tutorials (an intro to
data architecture's core principles, a how-to on developing a modern
enterprise data strategy, and so on); sessions on data lakes,
interactive visualizations, and natural language generation; overviews
of Spark, Docker, Containers, and Notebooks; and a wealth of big data
and reg tech case studies from Cox Automotive, EasyJet, Barclays,
Santander, Transport for London, and more.
Executive Briefings: six high-level overviews on data as the driver of
business value, including hard-nosed evaluations of cloud strategies by
Manuel Sevilla (CTO, Capgemini); Carme Artigas (Synergic Partners/CEOE
Innovation Board) on proven tactics for accelerating big data adoption;
Nicolaus Henke (Senior Partner, McKinsey) on what CEO's really think
about AI; and an insider's look at EU General Data Protection
Regulation's privacy obligations by AurΘlie Pols (Co-Chair, IEEE Data
Privacy Process).
Hardcore Data Science Day: eight hours on advanced techniques in deep
learning, NLP, and algorithm design with sessions on Microsoft's
LightGBM, Google's CausalImpact, Intel's BigDL, Toupee, and more from
data science leaders like David Barber (UCL) and Angie Ma (ASI Data
Science).
19 tutorials: long form sessions including Spark Camp, the all-day intro
to Apache Sparks core concepts and machine learning library; Anima
Anandkumar (AWS) on distributed deep learning with Apache MXNet; Tim
Berglund (Confluent) on building real-time streaming pipelines with
Kafka Connect and Kafka Streams; Bargava Subramanian (Red Hat) on
interactive data visualizations using Visdown; Aimee Gott (Mango
Solutions) on scaling R data analysis with Spark and sparklyr; and four
senior engineers from Cloudera on deploying and managing Hive, Spark,
and Impala in the public cloud.
39 Data Science & Advanced Analytics Sessions: covering topics like the
state of TensorFlow in 2017 by Sherry Moore (Google Brain Team); deep
learning in day- to-day practice by Mikio Braun (Zalando SE); and What
"50 Years of Data Science" leaves outùa practical, balanced view of what
building data science capability means today by Sean Owen (Cloudera
London).
23 Data Engineering and Architecture Sessions: illuminating solutions
from data pros like Jacques Nadeau (Dremio/Apache Drill PMC) on creating
virtual data lakes with Apache Arrow; John Akred and Stephen O'Sullivan
(Silicon Valley Data Science) on architecting a data platform; and Tyler
Akidau (Google) on realizing the promise of portability with Apache
Beam.