BDW16 London - Jonny Voon, Innovate UK - Smart Cities and the Buzz Word Bingo
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With predictions from the United Nations that 66 percent of the world population, including an extra 2.5 billion people, living in urban areas our cities are getting extra attention. If we want to avoid dystopian megacities of the future, then we must begin the technology transformation in our cities now.
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BDW16 London - Nondas Sourlas, Bupa - Big Data in Healthcare
The document discusses Bupa's use of analytics in healthcare, including risk modelling and care management, and referral management. For risk modelling and care management, Bupa uses predictive modelling to identify high-risk patients for targeted outreach programs, which have led to reductions in outpatient visits, tests, and surgical procedures, saving 9-10% in care costs. For referral management, Bupa profiles over 18,000 consultants based on claims data to guide over 700,000 pre-authorizations, achieving estimated healthcare savings of 9-11% of guided spend.
BDW16 London - Roland Major, Transport for London - Cloud Search Secured
At Transport for London (TfL) we move people and things around London. As our city grows, we come under more focus to get the most efficient use of our networks, as well as keeping them moving. This is where data analytics make all the difference. We have a wide range of information which we use for operational purposes as well as incident-related investigations while meeting the obligations under the Freedom of Information Act.
This presentation covers the evolving architecture and services we are building at TfL to pull together our diverse information sets for a better support of operational decision making. Also, we put forward our post-event analysis as well as detailed investigations where things might have gone wrong while remaining compliant with our regulatory obligations.
It’s all about spatiality and security. Time and location are the keys to bringing information sets together, to identify related facts or to correlate them. This is being delivered while working with both restricted and confidential-rated data with very different security needs. Bringing all these together required some unusual approaches to segregation and integration while working with the existing governance processes.
BDW16 London - Vojta Rocek, Trologic - Challenging Big Data
Many big data projects ultimately make life harder, not easier, for the end user. Businesses everywhere are swamped with data, decisions are slower and still based on gut feeling, and moreover, 95 % of company data is noise.
If you are going through the same pains and wish for a world where your BI can answer what are the top opportunities right now, which market segment has the greatest potential, and what is being done about the top five disasters, you should come listen this talk.
Vojta will briefly demo a solution that brings all these benefits. He will show you how you can cut costs in hospitals, improve profitability in banking and insurance and drive revenue in retail and FMCG.
BDW16 London - Scott Krueger, skyscanner - Does More Data Mean Better Decisio...
We have seen vast improvements to data collection, storage, processing and transport in recent years. An increasing number of networked devices are emitting data and all of us are preparing to handle this wave of valuable data.
Have we, as data professionals, been too focused on the technical challenges and analytical results?
What about the data quality? Are we confident about it? How can we be sure we are making good decisions?
We need to revisit methods of assessing data quality on our modernized data platforms. The quality of our decision making depends on it.
BDW16 London - William Vambenepe, Google - 3rd Generation Data Platform
1. The document discusses Google Cloud's 3rd generation data platform and services for managing large-scale data and analytics workloads. It focuses on managed services that allow users to focus on insights rather than infrastructure maintenance.
2. The platform includes services for data ingestion, processing, storage and analytics including Cloud Pub/Sub, Dataflow, BigQuery, Dataproc, Bigtable and Cloud Storage. It aims to provide a serverless platform with auto-optimized usage and pay per use pricing model.
3. Over 15 years Google has developed technologies for tackling big data problems including papers, open source projects and cloud products. Core components of their data platform are discussed including the Beam programming model and Dataflow for unified
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The Basel Committee on Banking Supervision (BCBS) and local regulators has been focussed on making banks more safe and resilient. A whole raft of new capital charges and constraints on liquidity and leverage have been introduced: Basel II.5, Basel III, Dodd-Frank, FRTB (“Basel IV”), etc. These have significantly increased the risk data management capabilities banks must have—capabilities that only big data tools can provide.
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BDW16 London - Mishal Patel, NHS - Modernising Routine Breast Cancer Using Bi...
Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to able to harness this large influx of data is of paramount. Traditionally, the systematic collection of medical images for research from heterogeneous sites has not been commonplace within the NHS and is fraught with challenges including; data acquisition, storage, secure transfer and correct anonymisation. Here we describe the development and implementation of a national centralised oncology image database and discuss the central issues associated with large-scale image acquisition from heterogeneous sites.
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BDW16 London - Charlie Ballard, TripAdvisor - TripAdvisor and Constant Change...
The world of travel is changing more rapidly than ever before, as consumers are inspired by low costs and social media to fly further away, more often, and for longer stays, and in general see more of the world.
This is all in addition to massive changes on the supply side with the rise of the sharing economy, downward price pressure and increased demand for diversification.
With the travel industry in such flux, long-term strategic planning can be an incredible challenge for any travel company. How can the travel industry predict ‘the next big thing’? With such global travellers, how does a hotel know where to invest next? What trending data can be safely relied on in this market?
As the world’s largest travel site, TripAdvisor is in a unique position to help the world’s travel industry better understand and react to these changes, but how does TripAdvisor play a role when its primary mission has always been to provide a voice to the traveller?
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BDW17 London - Totte Harinen, Uber - Why Big Data Didn’t End Causal Inference
Ten years ago there were rumours of the death of causal inference. Big data was supposed to enable us to rely on purely correlational data to predict and control the world. In this talk, I argue that the rumours were strongly exaggerated. Causal inference is becoming increasingly relevant thanks to improvements in inference methods and–ironically–the availability of data. Far from becoming marginalised, causal inference is today more relevant than it’s ever been.
BDW17 London - Rita Simoes, Boehringer Ingelheim - Big Data in Pharma: Sittin...
As far as data is concerned, Pharmaceutical Companies have always been clear-sighted and assertive on what insights to get from it, how, and what to do about it. And then the Big Data Era came in, with its frantic pace, transforming multiple industries all around but, for a number of reasons (privacy and data protection issues on top but not alone) keeping the Pharma Industry behind. How to run the extra mile to keep up with the powerful changes Big Data brings along has become a major concern. Strategic opportunities seem to be around the corner. Is the time to bridge gaps finally here?
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Hello London, the ground-breaking media partnership between Transport for London (TfL) and Exterion Media, gives new opportunities for brands to talk to the London audience in innovative ways and generates vital revenue for London’s transport network.
TfL and Exterion have been working together in the Hello London partnership for a year. Part of the collaboration was around the utilisation of data collected by TfL to better inform advertising investment decisions.
This has led to ground-breaking work in the Out-of-Home advertising sector and the first example of this is Taps Segmentation. Developed by the TfL Data Science team, it allows Exterion to understand demographic patterns at stations based on aggregated contactless and Oyster card usage. This de-personalised data can be analysed for different times of the day and is a game changer – allowing Exterion to rethink how both their classic and digital inventory can be packaged and tailored specifically for clients.
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Data Science is now well established in our businesses, and everyone considers data as a key asset and critical for our competitiveness.
However, Data Science is not easy to manage, very often projects failed and the investment made is not seeing as profitable.
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DISCOVER
UNDERSTAND
EVOLVE
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BDW17 London - Tom Woolrich, Financial Times - What Does Big Data Mean for th...
Content:
1. A brief history of the FT
2. What does Big Data mean to the FT?
3. The benefits of Big Data & how we use it
4. How we do it
5. What’s next for us?
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