Visual Data Discovery & Streaming Data: New Technologies for Real-Time Analytics
From finance to healthcare, telecom to retail, the challenge of turning data into actionable insight in real-time continues to grow alongside the increase in data organizations are retaining. While the value of real-time analytics is easily understood, many businesses are struggling with the limitations of traditional technologies and approaches. New technologies and approaches are now necessary to succeed with real-time analytics in the era of big data. Join our webcast to learn about the key technologies, how they work, and how they are enabling businesses in the real world to act on data in ways not possible ever before.
RecordedJul 23 201440 mins
Your place is confirmed, we'll send you email reminders
Andy Kriebel, Eva Murray, Paul Banoub, Emma Whyte, Josh Tapley
Hear from our expert panel how they built a strong analytics culture in their organisations to enable data-driven decision-making.
We have invited Paul Banoub (UBS, United Kingdom), Emma Whyte (The Information Lab, United Kingdom) and Josh Tapley (ComCast, United States) to discuss the following topics with us:
-How to find talented people and how to keep them engaged, challenged and motivated
-How to establish the right environment with processes and systems that foster innovation, learning, collaboration and analytical excellence
-How to setup best practices and governance while staying responsive to the organisation's need for information and insights RIGHT NOW
-How to make self-service analytics a success
During the panel discussion you have the chance to ask questions and get answers from our experts.
Presenters: Andy Kriebel, Head Coach at The Data School & Eva Murray, Head of BI and Tableau Evangelist at Exasol
Panel: Paul Banoub (Director, Analytics as a Service at UBS Investment Bank), Emma Whyte (Head of Centre of Excellence and Customer Advocacy at The Information Lab), Josh Tapley (Director, Data Visualization at Comcast)
Hélène Lyon, IBM, Distinguished Engineer, IBM Z Solutions Architect
IT is a key player in the digital and cognitive transformation of business processes delivering solutions for improved business value with analytics. This session will step by step explain the journey to secure production while adopting new analytics technologies leveraging mainframe core business assets
Using sensitive data for advanced analytics and machine learning is an effective mechanism for increasing revenue and building customer loyalty - among other benefits - but it comes with a set of considerations around utility and privacy, all of which need addressing:
- How can you extract value from your sensitive data sets?
- What privacy concerns should you consider?
- Is encryption enough to protect your data when it is shared?
Many organisations are sitting on vast amounts of sensitive, yet highly valuable data and are currently unable to maximise its value. That data could be shared with internal teams and third parties, but privacy concerns and compliance restrictions prevent the data from being utilised effectively.
Unlocking the data’s true value is a challenge, but there are a range of tools and techniques that can help. This live discussion will focus on the data analytics landscape; compliance considerations and opportunities for improving data utility in 2018 and beyond.
- A view of the data protection landscape
- Tools and techniques to unlock the value of your sensitive data
- Considerations for moving data to the cloud and sharing it with internal teams and third parties
- Opportunities for maximising data utility in 2018
Mixed reality is the result of blending the physical world with the digital world. Though it is relatively new technology and its adoption is still in initial stages. Mixed Reality devices and applications are projected to be the next technological era after smart phones.
The webinar will give a brief on Mixed Reality Potential Usecases those provide an immersive experience but also revenues streams to the creators.
Data Scientists are rare and highly valued individuals, and for good reason: making sense of data, and using the machine learning libraries requires an unusual blend of advanced skills. Why is it then that Data Scientists spend the majority of their time getting data ready for models, and a fraction actually doing the high value work?
In this talk we introduce the concept of Data Fabric, a new way to provide a self-service model for data, where data scientists can easily discover, curate, share, and accelerate data analysis using Python, R, and visualization tools, no matter where the data is managed, no matter the structure, and no matter the size.
We will talk through the role of Apache Arrow, the in-memory columnar data standard that is accelerating analytics for GPU-based processing, as well as the role of Pandas and Arrow in providing unprecedented speed in accessing datasets from Python.
David Itzkovits, CFA, Chief Executive Officer, Sanlam Global Investment Solutions
The majority of industries are embracing artificial intelligence (AI) and machine learning (ML) to ensure their clients’ experience is the best it can be. However, the mainstream asset management industry is way behind the curve.
This presentation will give an introduction to AI & ML, looking at what it is and how it is being used with real world examples. The presentation will then look at how the financial industry is currently using AI and the developments in progress.
We will end with how Sanlam believes AI can help the asset and wealth management businesses.
Peter Bruce, President and Founder, The Institute for Statistics Education at Statistics.com
Artificial Intelligence (AI) is a hot topic, and there is widespread alarm that AI will replace humans in the analytical process. Adam Selipsky, the CEO of Tableau, terms this a myth, and said recently that AI's role will remain that of an assistant to the analytics professional.
In this talk we go beyond that, and look at some interesting aspects of the human role as an integral component of machine learning and statistical modeling.
We discuss how human expertise "supervises" machine learning, how reliance on multiple sources can deliver surprising expertise, and when that system can go wrong.
Vicki Howe, Head of Product Development, HouseMark; Jason Lee, CEO, illumr
This session explores what artificial intelligence can add to data analysis in the social housing sector. Is it better than traditional statistical techniques?
HouseMark is the leading provider of data analysis and insight solutions to social housing providers. Illumr took part in HouseMark’s accelerator programme introducing innovative technology start-ups to the social housing sector. HouseMark have worked with illumr to test out the appetite for AI and explore what insights can be gained using data typically held by social housing providers.
Dr Tom Parsons, Research Director and Mitchell Murphy, Data Scientist from Spotlight Data
Researchers generate huge amounts of valuable unstructured data and articles from research every day. The potential for this information is huge: cancer and pharmaceutical breakthroughs, advances in technology and cultural research that can improve the world we live in.
This webinar discusses how text mining and Machine Learning can be used to make connections across this broad range of files and help drive innovation and research. We discuss using Kubernetes microservices to analyse the data and then applying Machine Learning and graph databases to simplify the reuse of the data.
Eva Murray (Head of BI, Exasol), Andy Kriebel (Head Coach, The Data School), Amy Lee Walton (Designer, Mapbox)
Learn how to use maps to effectively visualize data for your audience.
Whether you work with big data or small data and regardless of the tools you use, you have probably at some point created a map to show where customers are located, which bus routes are the most efficient for getting to work or how people voted in your region.
Together with our friends from Mapbox we want to help you get better at putting data on the map!
Join us for this live webinar to learn when to use a map and when it’s better not to; find out some best practices for maps and how to use Mapbox maps in Tableau.
We’ll also show you how to build great interactivity with maps in Tableau dashboards and share some tips and tricks for working with maps.
JS Gourevitch, Luca Schnettler, Erik Abrahamsson, Petra Wildermann, Matt Carstens, David Lethenborg
The data economy and digital technologies are deeply transforming almost all areas of our lives. One of the most heavily transformed revolve around insurance and healthcare with a number of really interesting development possibly redefining the way we take care of ourselves and the way we consumer and use insurance as well.
From harnessing the power of data to better help mental health patients, carers and medical personnel with their treatments to assessing the risk of developing broad range of illnesses and engaging better with users to propose them personalised healthy life plans to using big data and analytics to track down and prepare for epidemics to using data to better cover cars and drivers with car insurances and finally using social media data for insurers to better engage with customers, this webinar will propose a fascinating exploration of the opportunities, risks, new models supporting the digital transformation in banking.
Moderated by Jean-Stéphane Gourévitch
Luca Schnettler, CEO and Founder, HealthyHealth (UK)
Erik Abrahamsson, CEO and Co-founder, Digital Fineprint (UK)
Petra Wildermann, Business Development Director, Metabiota (Switzerland)
Matt Carstens, Sales Director, Urbanstats (US)
David Lethenborg, CEO, Monsenso (Denmark)
Internet of Things (IoT) envisions that everything in the physical world is connected seamlessly and is securely integrated through Internet. New products are innovated under the umbrella of IOT and opening up different opportunities. This webinar will discuss the future potential of IOT and the trend in which it is moving in adoption and standardisation.
David Sheehan, Senior Customer Scientist, MoneySuperMarket
Football (or soccer to any American readers) is full of clichés: “It’s a game of two halves”, “taking it one game at a time” and “Liverpool have failed to win the Premier League”. You’re less likely to hear “Treating the number of goals scored by each team as independent Poisson processes, statistical modelling suggests that the home team have a 60% chance of winning today”.
This webinar will introduce some basic statistical models that have been devised to predict the results of football matches. It won't help you make lots of money, but you will learn about programming, statistics and modelling through this fun intuitive topic.
Mari Hermanns, Head of Business Intelligence at Solaris Bank
Today most companies collect more data than ever and as we all know: data is the new oil. However gaining insights and turning them into action is easier said than done. In my experience this is a challenge for many companies, including innovative FinTechs.
In order to create a data driven business and organisational culture it is important to integrate data collection and an appreciation for data driven truth from the starting of a venture. This webinar is a brief overview of the hurdles and challenges BI faces in growing FinTech companies and how they can be overcome. Furthermore this webinar will briefly mention new BI trends and tools and how they could impact businesses.
Big Data has increased the demand for big data management solutions that operate at scale and meet business requirements. Big Data organizations realize quickly that scaling from small, pilot projects to large-scale production clusters involves a steep learning curve. Despite tremendous progress, critically important areas including multi-tenancy, performance optimization, and workflow monitoring remain areas where the operations team still needs management help.
Intended for enterprises who already have a data lake or are setting up their first data lake, this presentation will discuss how to implement data lakes with operations tools that automatically optimize clusters with solutions for monitoring, performance tuning, and troubleshooting in production environments.
Sean is the co-founder and CTO of Pepperdata. Previously, Sean was the founding GM of Microsoft’s Silicon Valley Search Technology Center, where he led the integration of Facebook and Twitter content into Bing search. Prior to Microsoft, Sean managed the Yahoo Search Technology team, the first production user of Hadoop. Sean joined Yahoo through the acquisition of Inktomi, and holds a B.S. in Engineering and Applied Science from Caltech.
Public cloud deployments have become irresistible in terms of flexibility, low barriers to entry, security, and developer friendliness. But the sheer inertia of traditional data lakes make them difficult to transition to cloud. In this talk we'll look at examples of how leading companies have made the transition using open source technologies and hybrid strategies.
Instead of following a "lift and shift" strategy for moving data lake workloads to the cloud, there are new considerations unique to cloud that should be considered alongside traditional approaches related to compute (eg, GPU, FPGA), storage (object store vs. file store), integrations, and security.
Viewers will take away techniques they can immediately apply to their own projects.
Many organisations aspire to become digital, data driven enterprises. In these organisations data is viewed as a critical asset, both to generate new digitally based products and services, and to guide and improve business operations and decision making. But many companies are failing to live up to this aspiration. They struggle to develop and implement data strategies that align with, and help to deliver, new business strategies.
This webinar will explore what becoming ‘data driven’ really means, examines some of the reasons why many organisations are failing to realise their ambitions, and propose ways of overcoming the challenges. Key to these is a strong emphasis on the increasingly critical importance of established data management disciplines, especially Data Governance, Data Quality and MDM, which all have a critical role to play in the digital business of the future.
This session will explore:
•What is a data driven organisation and how does it differ from a traditional company?
•The main challenges of creating a data driven organisation
•Building a data driven capability - the role of business and IT
•The central importance of a business aligned Data Strategy and how to achieve it
•Why a successful data strategy needs an integrated focus on Data Governance, Data Quality and MDM
Maloy Manna, PM Engineering, AXA Data Innovation Lab, Paris
The concept of Data lakes evolved to address challenges and opportunities in managing big data.
Organizations are investing massive amounts of time and money to upgrade existing data infrastructures and build data lakes whether on-premises or in the cloud.
This talk will discuss architectures and design options to implement data lakes with open source tools. Also covered are challenges of upgrade & migration from existing data warehouses, metadata management, supporting self-service and managing production deployments.
Hélène Lyon, IBM, Distinguished Engineer, IBM Z Solutions Architect
As an Enterprise customer, you are potentially using IBM Z in a hybrid cloud implementation. Let's understand how to benefit from cloud access to mainframe data without moving it outside z; thereby improving security, reducing integration challenges and answering your GDPR auditor's needs.
Managing and analyzing data to inform business decisions
Data is the foundation of any organization and therefore, it is paramount that it is managed and maintained as a valuable resource.
Subscribe to this channel to learn best practices and emerging trends in a variety of topics including data governance, analysis, quality management, warehousing, business intelligence, ERP, CRM, big data and more.