Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA

Data 101

9:00am–12:30pm
Strata Business Summit
Location: LL20C

Today’s business environment requires shifting from using data operationally—reporting on inventory, checking the results of marketing campaigns, tracking issues and resolutions, and the like—to using data strategically—instrumenting, experimenting, and testing throughout the organization. Managers must understand data topics such as machine learning, visualization, and real-time processing and be ready to make decisions about popular tools like Spark, Kafka, and Hadoop. Data 101 introduces you to core principles of data architecture, teaches you how to build and manage successful data teams, and inspires you to do more with your data through real-world applications. Setting the foundation for deeper dives on the following days of Strata + Hadoop World, Data 101 reinforces data fundamentals and helps you focus on how data can solve your business problems.

Tuesday, 03/14/2017

7:30am

7:30am–8:15am Tuesday, 03/14/2017
Location: LL Foyer and Executive Concourse
Coffee break (7:30am - 9am) (45m)

9:05am

9:05am–9:30am Tuesday, 03/14/2017
Data 101, Data-driven business management, Strata Business Summit
Location: LL20 C Level: Non-technical
Edd Wilder-James (Google)
Average rating: ****.
(4.00, 2 ratings)
Deep learning is white-hot at the moment, but why does it matter? Developers are usually the first to understand why some technologies cause more excitement than others. Edd Wilder-James relates this insider knowledge, providing a tour through the hottest emerging data technologies of 2017 to explain why they’re exciting in terms of both new capabilities and the new economies they bring. Read more.

9:30am

9:30am–10:00am Tuesday, 03/14/2017 Secondary topics:  Streaming
Ellen Friedman (MapR Technologies)
Average rating: ****.
(4.67, 3 ratings)
Life doesn’t happen in batches. Being able to work with data from continuous events as data streams is a better fit to the way life happens, but doing so presents some challenges. Ellen Friedman examines the advantages and issues involved in working with streaming data, takes a look at emerging technologies for streaming, and describes best practices for this style of work. Read more.

10:00am

10:00am–10:30am Tuesday, 03/14/2017
Big data and the Cloud, Data 101, Strata Business Summit
Location: LL20 C Level: Non-technical
Secondary topics:  Cloud
Jim Scott (NVIDIA)
Average rating: ****.
(4.00, 5 ratings)
The cloud is becoming pervasive, but it isn’t always full of rainbows. Defining a strategy that works for your company or for your use cases is critical to ensuring success. Jim Scott explores different use cases that may be best run in the cloud versus on-premises, points out opportunities to optimize cost and operational benefits, and explains how to get the data moved between locations. Read more.

10:30am

10:30am–11:00am Tuesday, 03/14/2017
Location: Executive Concourse
Morning break sponsored by Google (30m)

11:00am

11:00am–11:30am Tuesday, 03/14/2017
Data 101
Location: LL20 C
GABRIELA QUEIROZ (R-Ladies)
Average rating: ****.
(4.33, 6 ratings)
Data science is not only about machine learning. To be a successful data person, you also need a significant understanding of statistics. Gabriela de Queiroz walks you through the top five statistical concepts you need to know to work with data. Read more.

11:30am

11:30am–12:00pm Tuesday, 03/14/2017 Secondary topics:  AI, Deep learning
Melanie Warrick (Google)
Average rating: ****.
(4.80, 5 ratings)
Melanie Warrick explores the definition of artificial intelligence and seeks to clarify what AI will mean for our world. Melanie summarizes AI’s most important effects to date and demystifies the changes we’ll see in the immediate future, separating myth from realistic expectation. Read more.

12:00pm

12:00pm–12:30pm Tuesday, 03/14/2017
Data 101
Location: LL20 C
Aneesh Karve (Quilt)
Average rating: *****
(5.00, 3 ratings)
Seemingly harmless choices in visualization design and content selection can distort your data and lead to false conclusions. Aneesh Karve presents a quantitative framework for identifying and overcoming distortions by applying recent research in algebraic visualization. Read more.

12:30pm

12:30pm–1:30pm Tuesday, 03/14/2017
Location: 230 A-C
Lunch (1h)

3:00pm

3:00pm–3:30pm Tuesday, 03/14/2017
Location: Executive Concourse
Afternoon break (30m)