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Welcome to the Battle for the Consumer

In this modern world of marketing the continued diversification and proliferation of channels and information available to the consumer have led to a change in the attitude of business as they compete for customers. Retailers, telecommunications, financial services and technology companies are all changing the way in which they approach the customer and in turn the customer has changed their expectations of the Organisation. In this webinar we look at the drivers behind this and share some of the changes that are taking place as a result of it. Most importantly we will share our view of what will successful organisations need to change to win the battle for consumers
Recorded Nov 25 2015 41 mins
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Presented by
Mike Turner, Global Practice - Customer Intelligence
Presentation preview: Welcome to the Battle for the Consumer

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  • Unsupervised learning to uncover advanced cyber attacks Aug 22 2017 10:00 am UTC 45 mins
    Rafael San Miguel Carrasco, Senior Specialist, British Telecom EMEA
    This case study is framed in a multinational company with 300k+ employees, present in 100+ countries, that is adding one extra layer of security based on big data analytics capabilities, in order to provide net-new value to their ongoing SOC-related investments.

    Having billions of events being generated on a weekly basis, real-time monitoring must be complemented with deep analysis to hunt targeted and advanced attacks.

    By leveraging a cloud-based Spark cluster, ElasticSearch, R, Scala and PowerBI, a security analytics platform based on anomaly detection is being progressively implemented.

    Anomalies are spotted by applying well-known analytics techniques, from data transformation and mining to clustering, graph analysis, topic modeling, classification and dimensionality reduction.
  • Tensorflow: Architecture and use case Apr 11 2017 8:00 am UTC 45 mins
    Gema Parreño Piqueras. AI product developer
    The webinar drives into the introduction of the architecture of Tensorflow and the designing of use case.

    You will learn:
    -What is an artificial neuron?
    -What is Tensorflow? What are its advantages? What's it used for?
    -Designing graphs in Tensorflow
    -Tips & tricks for designing neural nets
    -Use case
  • Predicting Supply-Chain Disruptions Feb 16 2017 6:00 pm UTC 45 mins
    Dmitri Adler, Chief Data Scientist, Data Society
    If a volcano erupts in Iceland, why is Hong Kong your first supply chain casualty? And how do you figure out the most efficient route for bike share replacements?

    In this presentation, Chief Data Scientist Dmitri Adler will walk you through some of the most successful use cases of supply-chain management, the best practices for evaluating your supply chain, and how you can implement these strategies in your business.
  • Machine Learning towards Precision Medicine Feb 16 2017 1:00 pm UTC 45 mins
    Paul Hellwig Director, Research & Development, at Elsevier Health Analytics
    Medicine is complex. Correlations between diseases, medications, symptoms, lab data and genomics are of a complexity that cannot be fully comprehended by humans anymore. Machine learning methods are required that help mining these correlations. But a pure technological or algorithm-driven approach will not suffice. We need to get physicians and other domain experts on board, we need to gain their trust in the predictive models we develop.

    Elsevier Health Analytics has developed a first version of the Medical Knowledge Graph, which identifies correlations (ideally: causations) between diseases, and between diseases and treatments. On a dataset comprising 6 million patient lives we have calculated 2000+ models predicting the development of diseases. Every model adjusts for ~3000 covariates. Models are based on linear algorithms. This allows a graphical visualization of correlations that medical personnel can work with.
  • Bridging the Data Silos Feb 15 2017 6:00 pm UTC 45 mins
    Merav Yuravlivker, Chief Executive Officer, Data Society
    If a database is filled automatically, but it's not analyzed, can it make an impact? And how do you combine disparate data sources to give you a real-time look at your environment?

    Chief Executive Officer Merav Yuravlivker discusses how companies are missing out on some of their biggest profits (and how some companies are making billions) by aggregating disparate data sources. You'll learn about data sources available to you, how you can start automating this data collection, and the many insights that are at your fingertips.
  • Hype vs. reality: the truth of self-service BI Feb 15 2017 2:00 pm UTC 60 mins
    Glen Rabie, CEO, Yellowfin
    The desire to balance the needs of business users with the governance requirements of IT will kill the current concept of self-service BI.

    Discover how to drive success with analytics and better separate the self-service hype from reality with Yellowfin's CEO, Glen Rabie.

    Glen will discuss:
    - The impact of the self-service pipe dream
    - Why changing BI tools won't help
    - What self-service BI should actually look like
  • Analyse, Visualize, Share Social Network Interactions w Apache Spark & Zeppelin Feb 15 2017 1:00 pm UTC 45 mins
    Eric Charles, Founder at Datalayer
    Apache Spark for Big Data Analysis combined with Apache Zeppelin for Visualization is a powerful tandem that eases the day to day job of Data Scientists.

    In this webinar, you will learn how to:

    + Collect streaming data from the Twitter API and store it in a efficient way
    + Analyse and Display the user interactions with graph-based algorithms wi.
    + Share and collaborate on the same note with peers and business stakeholders to get their buy-in.
  • Comparison of ETL v Streaming Ingestion,Data Wrangling in Machine/Deep Learning Feb 15 2017 11:00 am UTC 45 mins
    Kai Waehner, Technology Evangelist, TIBCO
    A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 50% of the whole project.

    This session compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing, streaming analytics ingestion, and data wrangling within visual analytics. Various options and their trade-offs are shown in live demos using different advanced analytics technologies and open source frameworks such as R, Python, Apache Spark, Talend or KNIME. The session also discusses how this is related to visual analytics, and best practices for how the data scientist and business user should work together to build good analytic models.

    Key takeaways for the audience:
    - Learn various option for preparing data sets to build analytic models
    - Understand the pros and cons and the targeted persona for each option
    - See different technologies and open source frameworks for data preparation
    - Understand the relation to visual analytics and streaming analytics, and how these concepts are actually leveraged to build the analytic model after data preparation
  • How to apply real-time Cloud analytics in just an hour Feb 15 2017 9:00 am UTC 60 mins
    Iver van de Zand, SAP Analytics Leader
    Cloud analytics has great momentum and that is for a reason: it allows for real-time and live analytics without needing to prepare an environment. In this webinar you will learn how to apply SAP Cloud analytics using BusinessObjects Cloud and the Digital Boardroom. Be amazed by the easiness’ of use and the great visualization capabilities.

    Iver van de Zand – SAP Analytics Leader – will provide a deep dive session on the modeling and visualization capabilities of this stunning product
  • Data Science Apps: Beyond Notebooks with Apache Toree, Spark and Jupyter Gateway Feb 14 2017 1:00 pm UTC 60 mins
    Natalino Busa, Head of Applied Data Science, Teradata
    Jupyter notebooks are transforming the way we look at computing, coding and problem solving. But is this the only “data scientist experience” that this technology can provide?

    In this webinar, Natalino will sketch how you could use Jupyter to create interactive and compelling data science web applications and provide new ways of data exploration and analysis. In the background, these apps are still powered by well understood and documented Jupyter notebooks.

    They will present an architecture which is composed of four parts: a jupyter server-only gateway, a Scala/Spark Jupyter kernel, a Spark cluster and a angular/bootstrap web application.
  • Visualization: A tool for knowledge Feb 14 2017 11:00 am UTC 45 mins
    Luis Melgar, Visual Reporter at Univision News
    During the last decades, concepts such as Big Data and Data Visualization have become more popular and present in our daily lives. But what is visualization?

    Visualization is an intellectual discipline that allows to generate knowledge through visual forms. And as in every other field, there are good and bad practices that can help consumers or mislead them.

    In this webinar, we will address:

    -What it’s Data Visualization and why it’s important
    -How to choose the right graphic forms in order to represent complex information
    -Interactivity and new narratives
    -What tools can be used
  • How to Setup and Manage a Corporate Self Service Analytics Environment Feb 14 2017 9:00 am UTC 45 mins
    Ronald van Loon, Director Business Development (Adversitement) and Ian Macdonald, Principal Technologist (Pyramid Analytics)
    As companies face the challenges arising from a surge in the number of customer interactions and data, it can be difficult to successfully manage the vast quantities of information and still provide a positive customer experience. It is incumbent upon businesses to create a consumer-centric experience that is powered by (predictive) analytics.

    Adopting a data-driven approach through a corporate self-service analytics (SSA) environment is integral to strengthening your data and analytics strategy.


    During the webinar, speakers Ronald van Loon & Ian Macdonald will:

    •Expand upon on the benefits of a corporate SSA environment
    •Define how your business can successfully manage a corporate SSA environment
    •Present supportive case studies
    •Demonstrate practical examples of analytic governance in an SSA environment using BI Office from Pyramid Analytics.
    •Discuss practical tips on how to get started
    •Cover how to avoid common pitfalls associated with a SSA environment

    Stay tuned for a Q&A with speaker Ronald van Loon and domain expert Ian Macdonald, Principal Technologist, Pyramid Analytics.
  • Marketing Analytics: Using Analytics to Become a Data-Driven Marketer Jan 26 2017 3:00 pm UTC 60 mins
    Susan Graeme - EMEA Marketing Director at Tableau
    Marketers deal with data every day in every channel. Need to segment leads by job title for an email campaign? We’ve got data for that. Want to prove which programs generate higher quality leads than others? Go ask the data.

    In this webinar, we’ll show you exactly how a data company uses analytics in its marketing efforts. Susan Graeme, Marketing Director at Tableau, will show you examples of real marketing dashboards that we at Tableau use internally to drive world class marketing programs.
  • AI in Finance: AI in regulatory compliance, risk management, and auditing Recorded: Jan 18 2017 49 mins
    Natalino Busa, Head of Applied Data Science at Teradata
    AI to Improve Regulatory Compliance, Governance & Auditing. How AI identifies and prevents risks, above and beyond traditional methods. Techniques and analytics that protect customers and firms from cyber-attacks and fraud. Using AI to quickly and efficiently provide evidence for auditing requests.

    Learn:
    Machine learning and cognitive computing for:
    -Regulatory Compliance
    -Process and Financial Audit
    -Data Management

    Recommendations:
    -Data computing systems
    -Tools and skills
  • The End of Proprietary Software Recorded: Dec 8 2016 49 mins
    Merav Yuravlivker, Co-founder and CEO, Data Society
    Is it worth it for companies to spend millions of dollars a year on software that can't keep up with constantly evolving open source software? What are the advantages and disadvantages to keeping enterprise licenses and how secure is open source software really?

    Join Data Society CEO, Merav Yuravlivker, as she goes over the software trends in the data science space and where big companies are headed in 2017 and beyond.

    About the speaker: Merav Yuravlivker is the Co-founder and Chief Executive Officer of Data Society. She has over 10 years of experience in instructional design, training, and teaching. Merav has helped bring new insights to businesses and move their organizations forward through implementing data analytics strategies and training. Merav manages all product development and instructional design for Data Society and heads all consulting projects related to the education sector. She is passionate about increasing data science knowledge from the executive level to the analyst level.
  • A Practical Guide: Building your BI Business Case for 2017 Recorded: Dec 8 2016 45 mins
    Ani Manian, Head of Product Strategy, Sisense and Philip Lima, Chief Development Officer, Mashey
    So you’ve decided you want to jump on the data analytics bandwagon and propel your company into the 21st century with better analytics, reporting and data visualization. But to get a BI project rolling you usually need the entire organization, or at the very least the entire department, to get on board. Since embarking on a BI initiative requires an investment of time and resources, convincing the relevant people in the company to take the leap is imperative. You’ll need to construct a solid business case, defend your budget request and prove the value BI can bring to your organization.

    In this webinar you’ll discover:

    - Why organizations need to invest in BI to begin with
    - How are organization deriving value from BI
    - How to build an internal business case for investing in BI
    - What are the intricacies of how to build a budget
    - How to drive your company to a purchasing decision
    - How to start realizing value from BI now
  • Predictive APIs: What about Banking? Recorded: Dec 8 2016 44 mins
    Natalino Busa, Head of Applied Data Science at Teradata
    The best services have one thing in common: a superb customer experience. Banking services are no exception to this rule, and indeed the quest for an effortless, well informed, and personalized customer experience is one of the main goals of today's innovation in digital banking services.

    According to what Maslow has described in his "pyramid of needs", customers are seeking a more intimate and meaningful experience where banking services can actively assist the customer in performing and managing their financial life. Predictive APIs have a fundamental role in all this, as they enable a new set of customer journeys such as automatic categorization of transactions, detecting and alerting recurrent payments, pre-approving credit requests or provide better tools to fight fraud without limiting legitimate customer transactions.

    In this talk, I will focus on how to provide better banking services by using predictive APIs. I will describe the path on how to get there and the challenges of implementing predictive APIs in a strictly audited and regulated domain such as banking. Finally, I will briefly introduce a number of data science techniques to implement those customer journeys and describe how big/fast data engineering can be used to realize predictive data pipelines.

    The presentation will unfold in three parts:

    1) Define banking services: Maslow's law, modern vs traditional banking
    2) Examples predictive and personalized banking experiences
    3) Examples of data science and data engineering pipelines for banking and financial services
  • Big data and Machine Learning in Healthcare – Actual experience, actual results Recorded: Dec 7 2016 63 mins
    Lonny Northrup, Sr. Medical Informaticist – Office of Chief Data Officer, Intermountain Healthcare
    Hear first hand from one of the nation’s leading healthcare providers, Intermountain Healthcare, on what is actually being accomplished with big data and machine learning (cognitive computing, artificial intelligence, deep learning, etc.) by leading healthcare providers.

    Intermountain has evaluated between 300 and 400 big data and analytic solutions and actively collaborates with the other leading healthcare providers in the United States to implement the solutions that are delivering improved healthcare outcomes and cost reductions.
  • From the intelligence driven datacenter to an intelligence driven business Recorded: Dec 7 2016 59 mins
    Matt Davies, Head of Marketing EMEA, Splunk, & Sebastian Darrington, EMEA Director, Big Data & Analytics Solutions, Dell EMC
    Leveraging Big Data and Analytics to create actionable insights.

    Splunk & Dell EMC will share insights into the challenges & opportunities customers are seeing in the market – with the ‘needs to’; reduce costs and improve efficiency within IT (operational analytics), improve Compliance (security analytics) & implement Shadow IT due to the business not receiving the right service from IT. CIO Priority is keeping the lights on and so on…

    Dell EMC & Splunk combined strengths are helping numerous organizations to ‘leverage Big Data and Analytics to create actionable insights’.
  • Analytics in the Cloud Recorded: Dec 7 2016 45 mins
    Natalino Busa, Head of Applied Data Science at Teradata
    Today, data is everywhere. As more data streams into cloud-based systems, the combination of data and computing resources gives us today the unprecedented opportunity to perform very sophisticated data analysis and to explore advanced machine learning methods such as deep learning.

    Clouds pack very large amount of computing and storage resources, which can be dynamically allocated to create powerful analytical environments. By accessing those analytics clusters of machines, data analysts and data scientists can quickly evaluate more hypotheses and scenarios in parallel and cost-effectively.

    The number of analytical tools which is supported on various clouds is increasing by the day. The list of analytical tools spans from traditional rdms databases as provided by vendors to analytics open sources projects such as Hadoop Hive, Spark, H2O. Next to provisioning tools and solutions on the cloud, managed services for Data Science, Big Data and Analytics are becoming a popular offering of many clouds.

    Analytics in the cloud provides whole new ways for data analysts, data scientists and business developer to interact with each other, share data and experiments and develop relevant insight towards improved business processes and results. In this talk, I will describe a number of data analytics solutions for the cloud and how they can be added to your current cloud and on-premise landscape.
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  • Title: Welcome to the Battle for the Consumer
  • Live at: Nov 25 2015 2:00 pm
  • Presented by: Mike Turner, Global Practice - Customer Intelligence
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