Hi [[ session.user.profile.firstName ]]

Big Data & the Analysis Conundrum

This talk will cover several current topics in big data and specific analytic use cases, outlining the challenges and opportunities in the field, as well as the ethics of big data analytics. The use of Hadoop and associated toolsets, along with optimal HDFS architecture for analysis problems at scale, will be discussed and best practices outlined.
Recorded Jun 13 2013 47 mins
Your place is confirmed,
we'll send you email reminders
Presented by
Rob Peglar, CTO Americas, EMC Isilon
Presentation preview: Big Data & the Analysis Conundrum

Network with like-minded attendees

  • [[ session.user.profile.displayName ]]
    Add a photo
    • [[ session.user.profile.displayName ]]
    • [[ session.user.profile.jobTitle ]]
    • [[ session.user.profile.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(session.user.profile) ]]
  • [[ card.displayName ]]
    • [[ card.displayName ]]
    • [[ card.jobTitle ]]
    • [[ card.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(card) ]]
  • Channel
  • Channel profile
  • Introduction to Neural Networks Apr 11 2017 9:00 am UTC 45 mins
    Ganesh Raskar, Cloud Consultant at RapidCircle India
    Join this 6-module session which will take an insightful approach for anyone who wants to get started with deep learning and give intuition to explore the areas of DNN(Deep Neural Networks).

    The outline of this session is as follows:
    -Module 1: What is a neural network? Building blocks of neural networks, biological and artificial neurons
    -Module 2: Architecture of Neural Networks
    -Module 3: The Learning Process -- The Back-Propagation Algorithm
    -Module 4: Anatomy of Neural Networks -- What is tensor? What is a computation graph? Auto-differentiation tools
    -Module 5: Building a simple neural network
    -Module 6: Resources and Next Steps
  • 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
  • Simplify how your app gets the edge with Text, Video, and Speech Analytics Apr 6 2017 3:00 pm UTC 30 mins
    Joe Leung, Product Marketing Manager, HPE
    IDG estimates that unstructured data is growing at 62% per year and that 93% of all data in the digital universe will be unstructured. This is not surprising considering that there are over 600 million Instagrammers with over 100 million of them joining during the 2nd half of 2016 alone!

    Does your app need to connect to unstructured data sources, process and analyze massive amount of such data fast? Do you need to accelerate the release of a competitive and reliable app by embedding proven analytics from an established technology vendor? Trying to control R&D expenses? Wondering how to evaluate an OEM option? Please join us in this webinar to learn about:

    · The key criteria for evaluating an OEM partner
    · How HPE IDOL addresses those criteria
    · Resources for developers

    Joe Leung has over 13 years of experience in technology marketing and is currently focused on the analytics solution portfolio. Prior to this role, he was responsible for product marketing of the enterprise application data management solution.
  • GDPR: How to Manage Risks and Reputation within Any Data-Driven Company Apr 3 2017 2:00 pm UTC 45 mins
    Ronald van Loon, Director Business Development, Adversitement
    With the new GDPR taking effect in 2018 in the European Union, clients and consumers will have more control over their data, allowing them to decide which companies can use and store their information, which will have a substantial impact on data driven businesses. This includes all data analytics, and all applications, including Big data, Business Intelligence, data warehouses, data lakes, analytics, marketing applications, and all other applications where data is used. Client consent will be at the forefront of a business’s concerns, and organizations must manage this process to be compliant.

    Data-driven companies need to apply proactive measures that will help in effectively managing their risks and reputation when client trust is at stake.

    In this webinar, speaker Ronald van Loon will discuss the following:

    •Maintain client trust with appropriate data management
    •Taking steps to reduce risks and protect your reputation
    •Adopting a Protection by Design approach to data
    •How to implement technical infrastructures to protect and govern client data
    •Utilizing a Data Protection Officer to define how data is collected and stored
    •How to handle the various data streams

    Stay Tuned for a Q&A at the conclusion of the webinar with speaker Ronald van Loon
  • IT Relevance in the Self-Service Analytics Era Recorded: Mar 28 2017 60 mins
    Kevin McFaul and Roberta Wakerell (IBM Cognos Analytics)
    There’s no denying the impact of self-service. IT professionals must cope with the explosive demand for analytics while ensuring a trusted data foundation for their organization. Business users want freedom to blend data, and create their own dashboards and stories with complete confidence. Join IBM in this session and see how IT can lead the creation of an analytics environment where everyone is empowered and equipped to use data more effectively.

    Join this webinar to learn how to:


    · Support the analytic requirements of all types of users from casual users to power users
    · Deliver visual data discovery and managed reporting in one unified environment
    · Operationalize insights and share them instantly across your team, department or entire organization
    · Ensure the delivery of insights that are based on trusted data
    · Provide a range of deployment options on cloud or on premises while maintaining data security
  • Analyse, Visualize, Share Social Network Interactions w Apache Spark & Zeppelin Recorded: Mar 13 2017 49 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.
  • Systems of Insight - The Next Generation of Business Intelligence Recorded: Feb 21 2017 59 mins
    Boris Evelson - Forrester Principal Analyst
    Business intelligence has gone through multiple iterations in the past few decades. While BI's evolution has addressed some of the technology and process shortcomings of the earlier management information systems, BI teams still have a ways to go.

    From the laggards failing to transform enough of their structured and data into information and business insights, to the old guard of spreadsheet-based applications for key business decisions, companies have hit a rut. How do we solve this? With Systems of Insight.


    In this webinar, guest speaker, Boris Evelson, Vice President and Principal Analyst at Forrester, will show you how to get with the BI program by creating systems of insight. Doing so will allow you to:


    - Merge existing IT capabilities with demanding business requirements

    - Harness valuable customer and company data

    - Make decisions faster, and more pointed, to serve customers in the Age of the Customer
  • How to apply real-time Cloud analytics in just an hour Recorded: Feb 17 2017 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
  • Logistics Analytics: Predicting Supply-Chain Disruptions Recorded: Feb 16 2017 47 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.
  • Unlock real-time predictive insights from the Internet of Things Recorded: Feb 16 2017 60 mins
    Sam Chandrashekar, Program Manager, Microsoft
    Continuous streams of data are generated in every industry from sensors, IoT devices, business transactions, social media, network devices, clickstream logs etc. Within these streams of data lie insights that are waiting to be unlocked.

    This session with several live demonstrations will detail the build out of an end-to-end solution for the Internet of Things to transform data into insight, prediction, and action using cloud services. These cloud services enable you to quickly and easily build solutions to unlock insights, predict future trends, and take actions in near real-time.

    Samartha (Sam) Chandrashekar is a Program Manager at Microsoft. He works on cloud services to enable machine learning and advanced analytics on streaming data.
  • Machine Learning towards Precision Medicine Recorded: Feb 16 2017 47 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 Recorded: Feb 15 2017 48 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.
  • Data Visualization IS NOT Self Service BI - The Case for IoT in BI Recorded: Feb 15 2017 27 mins
    Lee Hermon, Sisense Engagement Manager and Adi Azaria, Sisense Chief Evangelist
    Businesses today already know that visualization in business intelligence is an essential part of competitive success. Yet, too many organizations are falling behind because of the inability to keep up with demand for information. One mistake is thinking that self-serve data visualization is all they need when setting up a self-service BI environment.

    Debunking the common myth, we will explore why data visualization IS NOT self-service BI. The only way for Information workers to become more self-sufficient is by having a BI environment that is more usable but also more consumable. It is these two themes—usability and consumability - that play crucial roles in a fully functioning self-service BI environment. Using modern IoT technologies, the modern business can expand access and consumability of data by engaging the human senses of sight, sound, and touch.

    Join Lee Hermon, Sisense Engagement Manager, as he explores the limitations of current Self Service Visualization models and Adi Azaria, Sisense co-founder & Chief Evangelist as he introduces how IoT in Business Intelligence is changing the game.
  • Hype vs. reality: the truth of self-service BI Recorded: Feb 15 2017 41 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
  • Comparison of ETL v Streaming Ingestion,Data Wrangling in Machine/Deep Learning Recorded: Feb 15 2017 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
  • Strategies for Successful Data Preparation Recorded: Feb 14 2017 33 mins
    Raymond Rashid, Senior Consultant Business Intelligence, Unilytics Corporation
    Data scientists know, the visualization of data doesn't materialize out of thin air, unfortunately. One of the most vital preparation tactics and dangerous moments happens in the ETL process.

    Join Ray to learn the best strategies that lead to successful ETL and data visualization. He'll cover the following and what it means for visualization:

    1. Data at Different Levels of Detail
    2. Dirty Data
    3. Restartability
    4. Processing Considerations
    5. Incremental Loading

    Ray Rashid is a Senior Business Intelligence Consultant at Unilytics, specializing in ETL, data warehousing, data optimization, and data visualization. He has expertise in the financial, manufacturing and pharmaceutical industries.
  • Data Science Apps: Beyond Notebooks with Apache Toree, Spark and Jupyter Gateway Recorded: Feb 14 2017 48 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 Recorded: Feb 14 2017 49 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 Recorded: Feb 14 2017 48 mins
    Ronald van Loon, Top Big Data and IoT influencer 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.
  • Data Virtualization: An Introduction (Packed Lunch Webinars) Recorded: Feb 10 2017 56 mins
    Paul Moxon, VP Data Architectures & Chief Evangelist, Denodo
    According to Gartner, “By 2018, organizations with data virtualization capabilities will spend 40% less on building and managing data integration processes for connecting distributed data assets.” This solidifies Data Virtualization as a critical piece of technology for any flexible and agile modern data architecture.

    This session will:

    Introduce data virtualization and explain how it differs from traditional data integration approaches
    Discuss key patterns and use cases of Data Virtualization
    Set the scene for subsequent sessions in the Packed Lunch Webinar Series, which will take a deeper dive into various challenges solved by data virtualization.
    Agenda:

    Introduction & benefits of DV
    Summary & Next Steps
    Q&A
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.

Embed in website or blog

Successfully added emails: 0
Remove all
  • Title: Big Data & the Analysis Conundrum
  • Live at: Jun 13 2013 4:00 pm
  • Presented by: Rob Peglar, CTO Americas, EMC Isilon
  • From:
Your email has been sent.
or close