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Extract Conference 2015: Rob Symes

Extract Conference 2015: Rob Symes
Recorded Jun 17 2015 2 mins
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Presented by
Rob Symes, CEO, The Outside View
Presentation preview: Extract Conference 2015: Rob Symes

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  • Introduction to Blockchain: Bitcoin, Ethereum, Ledgers, and more Oct 9 2017 2:00 pm UTC 60 mins
    David Siegel, Blockchain, decentralization and business agility expert
    Still confused about this whole Blockchain thing? Interested in investing in digital currencies, but not sure where to start? Want to get a better idea of the threats and opportunities?

    David Siegel is a Blockchain, decentralization and business agility expert who has been a high-level management & strategy consultant to companies like Sony, Hewlett Packard, Amazon, NASA, Intel, and many start-ups. David has been praised for being able to explain Blockchain in the most simple and interesting way.

    What you will learn:
    -What is Bitcoin?
    -What is the blockchain?
    -What is Ethereum? What is Ether?
    -What is a distributed application?
    -What is a smart contract?
    -What is a triple ledger?
    -What about identity and security?
    -What business models are at risk?
    -What are the opportunities?
    -What should we do?
  • Data+Coding: Analytics in SQL for beginners (with live demos) Sep 26 2017 1:00 pm UTC 60 mins
    Tomi Mester, Data Analyst, data36.com
    Tired of the limitations of Excel? Google Spreadsheets are not good enough for you anymore?

    If you are interested in being to a Data Scientist or an Analyst - or simply just run some more advanced analytics projects on your own - SQL is a must. It's easy to learn and super useful. Not to mention, that almost every online company is using it.

    On this webinar, I'll quickly show you how it works and how can you learn it by yourself. During the session I'll do some live coding, so you can see SQL in action!
  • The Cognitive Bank: Leveraging Advanced Analytics and Artificial Intelligence Sep 21 2017 12:00 pm UTC 60 mins
    Vivek Bajaj, Global VP of Solutions for IBM Financial Services
    Today the payments industry faces a rebirth by necessity. Financial institutions process massive volumes of customer and payments transaction data, much of it unstructured and untapped.

    Cognitive Systems have the ability to understand, reason and learn. In Financial Services applying cognitive capabilities to real world payments issues like safer and faster payments is yielding significant results. Furthermore Risk and Compliance and segment of one engagement are areas where ROI is tremendous when leveraging advanced analytics and artificial intelligence in cohesion.

    Learn from real world use cases of how financial institutions globally have gained significant competitive advantage by becoming a truly Cognitive Bank.
  • A Guide to Machine Learning Patterns and Data Visualizations Aug 24 2017 5:00 pm UTC 60 mins
    Dr. Umesh Hodeghatta Rao, CTO, Nu-Sigma Analytics Labs
    Data visualization must be intuitive in order for non-IT business leaders to see data patterns. Representing data in a graphical or pictorial format is easy, but constructing the data in the best and most logical way can be tricky.

    In this session, Umesh will talk about how to represent data simply to make quicker and better business decisions. He will walk through several data visualization techniques through business cases and examples. By the end of the session, you will not only know different data visualization techniques, but also have an understanding of circumstances under which each technique should be used and the best way to represent particular data sets for different business cases.
  • Data Visualization for Predictive Analytics Aug 24 2017 2:00 pm UTC 60 mins
    Andy Kriebel, Eva Murray, Benedetta Tagliaferri, Matthew Reeve
    What does the future hold?

    Predictive Analytics - everyone is talking about it and many organisations claim to be doing it. But are they? And what insights do they gain to then make tactical or strategic changes? How can analysts work with decision makers by sharing results in a visually effective and meaningful way while also informing them about possible courses of action?

    This webinar is presented by Andy Kriebel, Head Coach at the Data School and Eva Murray, Tableau Evangelist at Exasol. Guest speakers on Predictive Analytics are Benedetta Tagliaferri, Consulting Analyst at The Information Lab and Matthew Reeve, Chief Data Wrangler at Exasol.

    The webinar will look at some examples of predictive analysis and will show data visualization examples that are actionable and can drive further questions and discussions in an organisation.
  • Ask the Visualization Expert: Live Q&A on Advanced Data Visualization Aug 24 2017 1:00 pm UTC 45 mins
    Carl Edwards, BI Consultant, Brett Churchill, BI Consultant
    Looking to take your graphs to the next level? Want to make sure you choose the right visualization? Plagued by the challenges of geospatial heat maps?

    Get your questions ready and join this session where data experts Carl and Brett will go over the common questions they get asked and answer all the data visualization issues you've been plagued with, including how to:

    -Use location-based data to put your visualization on the map
    -Uncover new relationships, patterns and opportunities
    -Identify emerging trends
    -Answering comparative business questions with set analysis
    -Understand best practices for creating an aesthetically-pleasing and useful visualization
  • Artificial Intelligence: Methods, Applications and Impacts Aug 23 2017 6:00 pm UTC 45 mins
    Arinze Akutekwe, PhD Data Scientist, BAS EMEIA – Intelligent Enterprise - Analytics at Fujitsu
    Artificial intelligence has greatly changed the way we live since the 20th century. It involves the science and engineering of making machines intelligent and autonomous using computer programs.

    The processing power of computers has been on the exponential increase with cost of processors and storage decreasing. This has made research and developments efforts in AI areas such as deep learning, once thought to be impossible possible.

    In this webinar, we will examine current methods, application domains of specific methods, their impacts on our daily lives and try to answer questions on ethics of applying these technologies.
  • Hunting Criminals with Hybrid Analytics, Semi-supervised Learning, & Feedback Aug 23 2017 5:00 pm UTC 60 mins
    David Talby, CTO, Atigeo
    Fraud detection is a classic adversarial analytics challenge: As soon as an automated system successfully learns to stop one scheme, fraudsters move on to attack another way. Each scheme requires looking for different signals (i.e. features) to catch; is relatively rare (one in millions for finance or e-commerce); and may take months to investigate a single case (in healthcare or tax, for example) – making quality training data scarce.

    This talk will cover a code walk-through, the key lessons learned while building such real-world software systems over the past few years. We'll look for fraud signals in public email datasets, using IPython and popular open-source libraries (scikit-learn, statsmodel, nltk, etc.) for data science and Apache Spark as the compute engine for scalable parallel processing.

    David will iteratively build a machine-learned hybrid model – combining features from different data sources and algorithmic approaches, to catch diverse aspects of suspect behavior:

    - Natural language processing: finding keywords in relevant context within unstructured text
    - Statistical NLP: sentiment analysis via supervised machine learning
    - Time series analysis: understanding daily/weekly cycles and changes in habitual behavior
    - Graph analysis: finding actions outside the usual or expected network of people
    - Heuristic rules: finding suspect actions based on past schemes or external datasets
    - Topic modeling: highlighting use of keywords outside an expected context
    - Anomaly detection: Fully unsupervised ranking of unusual behavior

    Apache Spark is used to run these models at scale – in batch mode for model training and with Spark Streaming for production use. We’ll discuss the data model, computation, and feedback workflows, as well as some tools and libraries built on top of the open-source components to enable faster experimentation, optimization, and productization of the models.
  • Ask the Data Expert: Live Q&A on All Things Machine Learning & AI Aug 23 2017 2:00 pm UTC 60 mins
    Wim Stoop, Cloudera
    Join this webinar where data expert Wim Stoop from Cloudera will answer all of your Machine Learning & AI questions live.

    Wim will also go over some frequently asked questions on Machine Learning and AI such as:

    -Is AI going to eclipse Hadoop?
    -What are some tips and tricks for mastering deep learning?
  • Putting AI into LeAdershIp Aug 23 2017 12:00 pm UTC 45 mins
    Prof. Dr. Michael Feindt, Founder & Chief Scientific Officer, Blue Yonder
    Artificial Intelligence (AI) is not a technology for the future; it’s a huge business opportunity for today. But how can your organisation become a trailblazer for AI innovation, transforming the way you work to deliver immediate – and lasting – bottom line value?

    Former CERN scientist, Prof. Dr. Michael Feindt, is one of the brightest minds in Machine Learning. Join him for a 30-minute masterclass in how to apply AI to your business.

    You’ll learn how AI can:
    •Make sense of market and customer complexity, to deliver quick and effective decisions every single day
    •Increase workforce productivity to improve output and staff morale
    •Enhance decision-making and forecasting accuracy, for operational efficiency and improved productivity
    •Be implemented into your business quickly, easily, with minimal disruption

    Michael will also share real-life examples of how international businesses are using AI as a transformation tool, from his experience as founder of market-leading AI solution provider, Blue Yonder.
  • Tensorflow machine learning library and sample of application Aug 23 2017 8:00 am UTC 45 mins
    Marwa Ayad Mohamed ( Founder of YourChildCode ,Team lead software Engineer, Women Techmakers Cairo Lead)
    Tensorflow is an open source software library for numerical computation and machine learning.

    Join this session where Marwa will discuss:

    -Introduction to Artificial intelligence, machine learning and deep learning
    -Sample of machine learning applications
    -Tensorflow Story, Model and windows installation steps with object recognition demo.
  • Analytics Nightmares and How You Can Prevent Them Aug 22 2017 3:00 pm UTC 60 mins
    Meta S. Brown, Author, Data Mining for Dummies and President, A4A Brown, Inc.
    Analytics risks can keep you up at night. What if…
    · We make a big investment and don’t break even?
    · Management doesn’t trust the results?
    · Analysts cross data privacy boundaries?

    What a dilemma! You see the perils, yet you want the rewards that analytics can bring. The appropriate process enables you to dramatically reduce risks and maximize returns on your data and analytics investment.

    In this presentation, you will learn:
    · What causes most analytics failures
    · How you can diminish risk and maximize returns through strong analytics process
    · Why you (yes, you!) have a pivotal opportunity to establish high standards for analytics process right now
  • 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.
  • Data Analytics in Financial Services: Identifying obstacles and key issues Recorded: Jul 20 2017 61 mins
    Alex Kwiatkowski (Finastra), Peter Jackson (Southern Water), Jessica Holzbach (Penta)
    In an increasingly digitalised world, the value of information grows ever higher. Winning organisations – whether in financial services or any other vertical sector – will be those who can harness the power of data analytics to develop microscopic levels of insight and foresight into customer behaviours and operational activities in order to make progressive improvements on a continuous basis. Product development informed by factual evidence rather than educated guesswork, or real-time risk management based on a hyper-accurate picture of exposures, bring significant internal and external benefits.

    However, while banks want to get closer to their customers, is the feeling mutual? Data privacy is a very sensitive issue, and the perception of what constitutes intrusion will likely vary between individuals. Institutions, therefore, need to walk a fine line between what’s genuinely useful and what’s genuinely creepy.

    During this webinar, a panel of respected subject matter experts will discuss and dissect the key issues related to the widespread use of data analytics in financial services, identifying the obstacles which need to be overcome and the enablers that will drive FS forward successfully.
  • Managing privacy risk in advanced analytics and machine learning Recorded: Jul 20 2017 43 mins
    Charlie Cabot - Research Lead- Privitar, Jason du Preez - CEO - Privitar, Daniel Cohen - Sales Engineer - Privitar
    Personal data is a highly valuable asset. The winners of the future will be the organisations that make privacy intrinsic to data innovation. Join this webinar to learn how emerging best practices and technological solutions are helping financial institutions tackle data privacy in analytics and ML and drive commercial benefit.

    Privitar is a leading privacy engineering software company. Privitar enables organisations to use, share and derive insight data safely. Privitar creates opportunities by allowing broader use of valuable information assets for collaboration and sharing, whilst reducing the risk associated with storing, processing and using sensitive data due to data breaches, regulatory penalties and the misuse of data.
  • How data visualization can deliver clearer insights for the Finance industry Recorded: Jul 19 2017 64 mins
    Eva Murray and Andy Kriebel
    Death to Spreadsheets!

    Despite the growing popularity of data visualization tools across all industries, the finance sector still relies heavily on seeing data presented in tabular form. Analysts in financial institutions often spend a large part of their day pouring over spreadsheets, extracting numbers, pivoting tables, running macros and making adjustments before creating static reports to print for management meetings.
    But what happens if you have another question?


    We argue that there is a better way to approach financial data and to unlock more of the collective brain power of your analysts. We will show you a number of options for visualizing financial results, highlighting trends and developing KPI dashboards that provide real insights quickly. Because there are more valuable things your staff could be doing than wrangling with spreadsheets
  • Radiant, a powerful open source Shiny application for business analytics Recorded: Jul 11 2017 58 mins
    Ali Marami Chief Data Scientist
    Radiant is a robust tool for business analytics and running sophisticated models without any need for code development. It leverages the functions and tools in R and at the same time provides a user-friendly interface. With Radiant, you can manipulate and visualize your data, run different models from simple OLS to decision trees (CART) and neural networks, and evaluate your results.

    The application is based on the Shiny package and can be run locally or on a server. Radiant was developed by Vicent Nijs. In this webinar, we review the tools available in Radiant and explain how easily you can use this tool without any setup or installation on your system.

    Radiant key features:

    • Explore: Quickly and easily summarize, visualize, and analyze your data
    • Run different models: OLS, GLM, Neural Networks, Naïve Bayes and CART.
    • Cross-platform: It runs in a browser on Windows, Mac, and Linux
    • Reproducible: Recreate results and share work with others as a state-file or an Rmarkdown report
    • Programming: Integrate Radiant's analysis functions with your own R-code
    • Context: Data and examples focus on business applications

    After this webinar you will learn:

    • Data manipulation and running different models
    • How to run advanced analytics in a browser on any device even in your tablet or iPad.


    Presenter bio:

    Ali has a Ph.D. in Finance from the University of Neuchatel in Switzerland and a BS in Electrical Engineering. He has extensive experience in financial modeling, quantitative modeling, and financial risk management in several US banks.
  • Binomial and Multinomial Logistic Regressions in R Recorded: Jun 29 2017 49 mins
    Ali Marami Chief Data Scientist
    Logistic regressions are the basic of machine learning. In this webinar, we discuss binomial and multinomial logistic regressions, how we implement them in R and test their performance. We will also review few examples of their usage in industry. In addition, you will learn how to use R-Brain advanced IDE when implementing the model.

    - Logistic regressions fundamentals and how to interpret estimates
    - Binomial and Multinomial logistic regressions
    - Implement logistic regressions in R
    - Performance measurement in logistic regressions
    - Generating and understanding ROC curve
    - Building confusion metrics and understanding its elements
    - Examples of model application in industry
    - Learn about new advanced IDE

    Presenter bio:

    Ali has a Ph.D. in Finance from the University of Neuchatel in Switzerland and a BS in Electrical Engineering. He has extensive experience in financial modeling, quantitative modeling, and financial risk management in several US banks.
  • Death to Traffic: How Smart Cities are Changing Transportation Recorded: Jun 23 2017 45 mins
    Laura Schewel, CEO, StreetLight Data
    From automated vehicles to ride hailing apps, transportation as we know it is changing - and fast. But new technologies alone won't help communities build the efficient, equitable, and sustainable transportation networks communities want. In fact, these innovative technologies could do just the opposite, especially if they are not deployed wisely. Cities must collect the right data and enact the right policies to ensure they do not exacerbate problems like inequity and traffic, and to hold themselves accountable to the promise of new mobility technologies.

    In this webinar, you will find out why - and how - the smartest cities of tomorrow will be those that adopt data-driven transportation strategies today. Join for Laura Schewel's presentation to gain insights into:

    • Why the status quo for transportation data collection is no longer good enough
    • The types of Massive Mobile Data that are useful for transportation and urban planning
    • Algorithmic processing techniques that are critical for making this data useful
    • Case studies from California and Virginia that demonstrate why Massive Mobile Data drives more effective transportation planning
    • A forward-looking blueprint for using Massive Mobile Data to maximize the potential benefits of new transportation technologies - and minimize negative impacts

    Laura Schewel founded StreetLight Data, a mobility analytics provider, after spending more than a decade as an advanced transportation researcher and statistician at the Rocky Mountain Institute and FERC. She has particular expertise in transportation systems, sustainability and safety, and vehicle/system modeling and analysis.
  • How IoT Will Make Healthcare Healthy, Wealthy, & Wise Recorded: Jun 23 2017 46 mins
    Jarie Bolander, COO, Lab Sensor Solutions
    IoT is a technology that has the potential to make us healthy, wealthy, and wise especially in healthcare. Healthcare is just now adopting IoT to improve patient outcomes and decrease the cost of care.

    In this webinar, you’ll learn:

    - How to identify if an IoT solution will work for your use case.
    - What others in healthcare are using IoT for.
    - The challenges of IoT in healthcare
Big Data, Big Challenges, Big Gains
Everyone is talking about big data. But what is it? How do you use it? How will it affect your organization?

Subscribe to this channel to hear best practices and practical information on everything big data from infrastructure requirements to analysis and use cases.

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  • Presented by: Rob Symes, CEO, The Outside View
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