Presented By O'Reilly and Cloudera
Make Data Work
31 May–1 June 2016: Training
1 June–3 June 2016: Conference
London, UK

Schedule: DDBD sessions

9:10–9:50 Wednesday, 1/06/2016
Location: Capital Suite 2/3
Simon Wardley (Leading Edge Forum)
Average rating: ****.
(4.60, 5 ratings)
Simon Wardley examines the level of situational awareness within business, why it matters, and whether we can anticipate and exploit change before it hits us. Is it simply a lack of data, or are we not looking at the right things? Read more.
9:50–10:10 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Non-technical
carme artigas (Synergic Partners)
Average rating: ****.
(4.67, 3 ratings)
The most important challenge companies face in realizing the value of big data is implementing a cultural change to become a data-driven organization. Carme Artigas shares real-world examples focusing on the business side of this technology disruption to show how big data is transforming different industries including retail, insurance, telco, and digital businesses. Read more.
10:10–10:30 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Non-technical
Ellen Friedman (MapR Technologies)
Average rating: ***..
(3.50, 2 ratings)
Organizations need to build cultures comfortable with data-driven decisions, so it's increasingly important that groups with widely different knowledge bases—such as business decision makers, domain experts, and technical developers—exchange information and ideas effectively. Ellen Friedman outlines specific steps to cut through barriers and build strength in cross-team communication. Read more.
11:00–11:20 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Non-technical
Average rating: *****
(5.00, 1 rating)
Data-driven projects depend on a complex environment. You have many stakeholders with different skill sets involved, but all these skills are equally crucial to the project. Anne Sophie Roessler uses the example of the failed universal language Esperanto to explain how to help these stakeholders—most of whom use different languages and technologies and have different baselines—work together. Read more.
11:20–11:40 Wednesday, 1/06/2016
Location: Capital Suite 2/3
Tags: health, science
Taryn Fixel (ingredient1)
Average rating: ***..
(3.50, 2 ratings)
Taryn Fixel investigates the bioindividuality of food choices and explains how flexible data structures are capturing real-time food behaviors that will transform our understanding of nutrition and human health. Read more.
11:40–12:00 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Intermediate
Rachel Shadoan (Akashic Labs)
Average rating: ****.
(4.67, 3 ratings)
Informed consent is the backbone of ethical research involving human participants. In academic contexts, there are systems in place to protect human participants, but similar structures are lacking in the companies that drive the Web. Rachel Shadoan explains why adopting informed consent as an industry standard is vital, both ethically and for the validity of the research we do. Read more.
12:00–12:30 Wednesday, 1/06/2016
Location: Capital Suite 2/3
Farrah Bostic (The Difference Engine)
Average rating: *****
(5.00, 2 ratings)
We all like to say, "There's no such thing as a dumb question," and yet we—researchers, data scientists, and managers—also talk about asking the "right questions" when it comes to designing survey instruments, qualitative methods, databases, and other tools to help us make decisions. Farrah Bostic investigates where good questions come from and explains how to construct a good question. Read more.
13:30–14:00 Wednesday, 1/06/2016
Location: Capital Suite 2/3
Mona Vernon (Thomson Reuters Labs)
Average rating: ****.
(4.67, 3 ratings)
How many ways can data be monetized? Data fuels better financial outcomes for a firm. Mona Vernon explains how data-driven decision making drives better customer-experience design and more efficient operations and why data is also an asset that can be sold, traded, or used to create new marketplaces. Read more.
14:00–14:20 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Non-technical
Tags: education
Kim Nilsson (Pivigo)
Average rating: ****.
(4.00, 3 ratings)
Just as the cloud revolutionized how companies distribute and manage their data, the move from physical offices to geodistributed teams is revolutionizing hiring and work practices. Kim Nilsson explains how Pivigo’s S2DS data science program broadened its reach by running online for geodistributed data scientists across Europe and shares practical details of what did and didn’t work. Read more.
14:20–14:40 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Intermediate
Erik Nygard (Limejump Ltd)
Average rating: ***..
(3.00, 1 rating)
In order to move away from carbon-intensive fossil fuels to a greener generation mix, a transformational shift toward a smarter energy system is needed. This shift requires an unprecedented amount of data to be processed to unlock hidden capacity and demand flexibility on the network. Erik Nygard explains why this is only possible with disruptive energy tech and advanced analytics. Read more.
15:30–15:50 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Non-technical
laurent gaubert (Autodesk)
Average rating: ***..
(3.50, 2 ratings)
Autodesk's transition to a subscription business model has caused the company to rethink how it interacts with and engages its customers. Laurent Gaubert details how, in a short period of time, Autodesk has executed numerous data science projects that have enhanced its capabilities to acquire, retain, and provide more value to its customers. Read more.
15:50–16:10 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Intermediate
Majken Sander (Majken Sander)
Average rating: ****.
(4.67, 3 ratings)
Emphasizing the importance of higher awareness, education, and insight about the subjective algorithms that affect our lives, Majken Sander explores the value judgements built into algorithms, discusses their consequences, and presents possible solutions, including visionary concepts like an AlgorithmicMe that could raise awareness and guide developers, analysts, and data scientists. Read more.
16:10–16:30 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Non-technical
Pete Williams (Marks and Spencer)
Average rating: *****
(5.00, 6 ratings)
Starting a big data journey by bagging a unicorn and corralling it in your newly acquired big data stable will not necessarily lead to success or lasting change. So how do you drive value from big data? Drawing on first-hand experience at Marks and Spencer, Pete Williams shares practical examples and advice on how to take your data culture and capability from walk through trot to gallop. Read more.
16:30–16:50 Wednesday, 1/06/2016
Location: Capital Suite 2/3 Level: Intermediate
Rupert Steffner (Otto GmbH & Co. KG)
Average rating: ****.
(4.11, 9 ratings)
The latest research shows that time to manage customers is critical to success. Otto has developed a whole set of real-time applications to manage customers at interaction time. Rupert Steffner highlights the business metrics and the application architecture and outlines a real-time data management model developers of any interactive business intelligence application can use. Read more.
16:50–17:00 Wednesday, 1/06/2016
Location: Capital Suite 2/3
Alistair Croll (Solve For Interesting)
Average rating: *****
(5.00, 2 ratings)
Program chair Alistair Croll closes Data-Driven Business Day. Read more.