Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK

Schedule: Visualization and user experience sessions

9:00–17:00 Tuesday, 22 May 2018
Data Case Studies
Location: Capital Suite 2/3
Dan Jeavons (Shell), Hollie Lubbock (Fjord), Jivan Virdee (Fjord), fausto morales (Arundo), Marty Cochrane (Arundo), Jane McConnell (Teradata), Paul Ibberson (Teradata), Michael Troughton (Conduce), Jonathan Genah (DHL Supply Chain), Allison Nau (Cox Automotive UK), Dave Fitch (The Data Lab), Maria Assunta Palmieri (Data Reply ), Niranjan Thomas (Dow Jones), Erik Elgersma (FrieslandCampina), Viola Melis (Typeform), carme artigas (Synergic Partners), Nuria Bombardo (Pepsico)
Hear practical insights from household brands and global companies: the challenges they tackled, approaches they took, and the benefits—and drawbacks—of their solutions. Read more.
13:30–17:00 Tuesday, 22 May 2018
Making data visual: A practical session on using visualization for insight
Location: Capital Suite 9 Level: Non-technical
Secondary topics:  Visualization, Design, and UX
Danyel Fisher (Honeycomb.io), Miriah Meyer (University of Utah)
Average rating: ****.
(4.00, 4 ratings)
Danyel Fisher and Miriah Meyer explore the human side of data analysis and visualization, covering operationalization, the process of reducing vague problems to specific tasks, and how to choose a visual representation that addresses those tasks. Along the way, they also discuss single views and explain how to link them into multiple views. Read more.
12:05–12:45 Wednesday, 23 May 2018
Data visualization in a big data world
Location: Capital Suite 14 Level: Intermediate
Secondary topics:  Visualization, Design, and UX
Jeff Fletcher (Cloudera)
Average rating: ****.
(4.73, 11 ratings)
As big data adoption grows, Apache Hadoop, Apache Spark, and machine learning technologies are increasingly being used to analyze ever-larger datasets, but we still have to keep telling stories about the data and making sure the message is clear. Jeff Fletcher details the tools and techniques that are relevant to data visualization practitioners working with large datasets and predictive models. Read more.
14:55–15:35 Wednesday, 23 May 2018
The business leader’s guide to designing indispensable analytics solutions and data products
Location: Capital Suite 14 Level: Beginner
Secondary topics:  Visualization, Design, and UX
Brian O'Neill (Designing for Analytics)
Average rating: ****.
(4.00, 2 ratings)
Gartner says 85%+ of big data projects will fail. Your own company may have even spent millions on a recent project that isn’t really delivering the value or UX everyone hoped for. Brian O'Neill explains why CDOs, PMs, and business leaders who leverage design to prioritize utility, usability, and customer value will realize the best ROIs and demonstrates how to start evaluating your UX. Read more.
16:35–17:15 Wednesday, 23 May 2018
Architectural design for interactive visualization
Location: Capital Suite 14 Level: Beginner
Secondary topics:  Visualization, Design, and UX
Bargava Subramanian (Binaize), Amit Kapoor (narrativeVIZ)
Average rating: *****
(5.00, 1 rating)
Creating visualizations for data science requires an interactive setup that works at scale. Bargava Subramanian and Amit Kapoor explore the key architectural design considerations for such a system and discuss the four key trade-offs in this design space: rendering for data scale, computation for interaction speed, adapting to data complexity, and being responsive to data velocity. Read more.
12:05–12:45 Thursday, 24 May 2018
A heretical monitoring view: Using PostgreSQL to store Prometheus metrics and visualizing them in Grafana
Location: Expo Hall Level: Intermediate
Secondary topics:  Time Series and Graphs
Erik Nordström (Timescale)
Erik Nordström explains how and why to use PostgreSQL as a Prometheus backend to support complex questions (and get a proper SQL interface), offers an overview of pg_prometheus, a custom Prometheus datatype, and prometheus-postgresql-adapter, a remote storage adaptor for PostgreSQL, and shares his experience with TimescaleDB, which enables PostgreSQL to scale for classic monitoring volumes. Read more.
16:35–17:15 Thursday, 24 May 2018
Deep learning in the browser: Explorable explanations, model inference, and rapid prototyping
Location: Capital Suite 13 Level: Intermediate
Amit Kapoor (narrativeVIZ), Bargava Subramanian (Binaize)
Amit Kapoor and Bargava Subramanian lead three live demos of deep learning (DL) done in the browser—building explorable explanations to aid insight, building model inference applications, and rapid prototyping and training an ML model—using the emerging client-side JavaScript libraries for DL. Read more.
16:35–17:15 Thursday, 24 May 2018
Human-in-the-loop data science with Jupyter widgets
Location: Capital Suite 14 Level: Intermediate
Pascal Bugnion (ASI Data Science)
Jupyter widgets let you create lightweight, interactive graphical interfaces directly in Jupyter notebooks. Pascal Bugnion demonstrates how to use Jupyter widgets to implement human-in-the-loop machine learning with highly interactive user interfaces. Read more.