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Demo Video: SAP Document Access by OpenText and SAP Archiving by OpenText

It's easy to ensure compliance and boost efficiency with SAP data and document archiving. Regardless if paper, email or office document, all business documents are securely archived and attached to SAP transactions and processes. Your business content can be stored in any format, guaranteeing long-term access and full readability. Together, OpenText and SAP allow users to access all business documents regardless of time or where they are in the world.
Recorded Jul 2 2015 5 mins
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Presentation preview: Demo Video: SAP Document Access by OpenText and SAP Archiving by OpenText

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  • Visualizing Smart Cities: How Data Visualization can help shape our communities Jun 23 2017 12:00 pm UTC 60 mins
    Andy Kriebel, Head Coach at The Data School, Tableau Zen Master & Eva Murray, Tableau Evangelist at EXASOL, Tableau Trainer
    Whenever there is data, there is the chance to visualize it and gain valuable insights that can drive change and improvements. Governments have realized the potential that data holds for transforming our towns, cities, living spaces and communities to better address the needs of our modern society.

    Governments may want to change public transport services to suit commuters who move away from city centers due to increasing living costs, or develop programs that deliver more support services to areas showing high incidences of mental illnesses, or simply monitor bike traffic to assess the necessity of additional cycle lanes and bike share programs in our capitals. Data and data visualization can help us identify the needs of our communities and can support us in addressing them effectively.

    In this webinar Andy and Eva will present examples of Government using data visualization to improve services for communities and will share how you can get involved through analyzing open data and becoming part of the wider 'dataviz' community.
  • How to get data moving: Impact of big data on transportation Jun 23 2017 10:00 am UTC 45 mins
    Arwen Smit, Head of Marketing, dovu
    Moving from A-B is slowly being revolutionised through data. Car-sharing and ride-hailing are just the beginning. Thousands of connected devices are currently monitoring data points, and although stand-alone analysis can be useful, true innovation occurs when these data sets are combined to transform into something new.

    In the near future, IoT data explosion and the API revolution will collide to change city planning, urban movement and the role of the car in the 21st century.

    First off, we set out to understand what big data means in the context of transportation, answering questions such as what is it, where is it coming from, and what can you do with it.
    - Next, we'll zoom out and apply these learning to transport innovation in a wider context, considering how it will influence concepts such as urban movement, social mobility, and quality of life.
    - Finally, we'll discuss the relationship between open data and innovation.
  • Interpreting IoT Data: Context is Everything Jun 23 2017 8:00 am UTC 45 mins
    Dr. Boris Adryan, Head of IoT & Data Analytics, Zühlke Engineering GmbH
    For decades “things” have been connected to the Internet. Embedded in carefully planned end-to-end solutions, the what and why of the data arising from these devices has often been hard-coded. In other words, in the M2M world, it is usually clear from the outset what is going to happen with the data. In a future IoT, this won’t necessarily be the case. In a world full of connected devices, the meaning and the potential of the device data is only going to become clear in the context where it is needed in.

    But how can software tell that your connected thermometer is useful for a medical application, or that a car in the drive way is likely an indicator of your partner’s presence? This is where device catalogues, information models and ontologies come in handy.

    While the talk is not specifically tailored towards a smart city focus, it should become clear how these technologies can be useful in such environment.
  • Tableau in the Cloud: A Netflix Original Jun 22 2017 1:00 pm UTC 75 mins
    Albert Wong - Reporting Platform Manager, Netflix
    See how Netflix built its analytics in the cloud with Tableau and Amazon Web Services

    Building out a data platform doesn't have to be like building a House of Cards, and our friends at Netflix know this better than anyone else. With 86 million members and counting, and more than 700 billion events per day, Netflix has had to expand their data capabilities by developing a scalable and flexible analytics platform built on Tableau and AWS.

    Attend this webinar to hear from Albert Wong, analytics expert at Netflix, to see how they simplified their data stack by building a data lake/data warehouse strategy which allows Netflix to collect and store massive amounts of data, supporting thousands of Tableau users with managed data.

    You'll learn about:

    How to set up effective analytics on top of enormous data sets
    How Netflix serves large groups of people with governed data
    The details of Netflix's data lake/data warehouse strategy
    How Netflix manages Hadoop with Tableau
  • Fog Computing in Mobile Network Jun 22 2017 8:00 am UTC 45 mins
    Adnyesh Dalpati, Director Solutions Architect at Alef Mobitech
    Fog computing has the potential to resolve the issues with network latency since the media rich content can be delivered through such nodes directly.

    Fog Computing inside the mobile network providers opens up a window of revenue opportunities for MNO's and creates a innovative space in content & application delivery platform.

    Join this webinar to learn how to tackle the different challenges with fog computing and its role in the IoT cycle.
  • Toward Internet of Everything: Architectures, Standards, & Interoperability Jun 21 2017 3:00 pm UTC 60 mins
    Ram D. Sriram, Chief of the Software and Systems Division, IT Lab at National Institute of Standards and Technology
    In this talk, Ram will provide a unified framework for Internet of Things, Cyber-Physical Systems, and Smart Networked Systems and Societies, and then discuss the role of ontologies for interoperability.

    The Internet, which has spanned several networks in a wide variety of domains, is having a significant impact on every aspect of our lives. These networks are currently being extended to have significant sensing capabilities, with the evolution of the Internet of Things (IoT). With additional control, we are entering the era of Cyber-physical Systems (CPS). In the near future, the networks will go beyond physically linked computers to include multimodal-information from biological, cognitive, semantic, and social networks.

    This paradigm shift will involve symbiotic networks of people (social networks), smart devices, and smartphones or mobile personal computing and communication devices that will form smart net-centric systems and societies (SNSS) or Internet of Everything. These devices – and the network -- will be constantly sensing, monitoring, interpreting, and controlling the environment.

    A key technical challenge for realizing SNSS/IoE is that the network consists of things (both devices & humans) which are heterogeneous, yet need to be interoperable. In other words, devices and people need to interoperate in a seamless manner. This requires the development of standard terminologies (or ontologies) which capture the meaning and relations of objects and events. Creating and testing such terminologies will aid in effective recognition and reaction in a network-centric situation awareness environment.

    Before joining the Software and Systems Division (his current position), Ram was the leader of the Design and Process group in the Manufacturing Systems Integration Division, Manufacturing Engineering Lab, where he conducted research on standards for interoperability of computer-aided design systems.
  • Computational Behaviour Modelling for the Internet of Things Jun 21 2017 12:00 pm UTC 45 mins
    Dr. Fahim Kawsar, Director of IoT Research at Nokia Bell Labs
    We are observing a monumental effort from the industry and academia to make everything connected. Naturally, to understand the needs of these connected things, we need a better understanding of humans and where, when, and how they interact. This behavioural understanding would help us to create digital services and capabilities that fundamentally change the way we experience our lives.

    In this talk, I will explore the system and algorithmic challenges in modelling human behaviour. I will discuss how mobile and wearable devices together with the wireless network can be used as a multi-sensory computational platform to learn and infer human behaviour and to design user-centred connected services across Enterprise, Urban City and Lifestyle.

    Dr Fahim Kawsar leads the Internet of Things research at Bell Labs and holds a Design United Professorship at TU Delft. His current research explores novel algorithms and system design techniques to build transformative multi-sensory systems for disruptive mobile, wearable and IoT services. He borrows tenets from Social Psychology, learns from Behavioural Economics and applies Computer Science methods to drive his research. He is a frequent keynote, panel and tutorial speaker, hold 15+ patents, organised and chaired numerous conferences, (co-)authored 100+ publications and had projects commissioned. He is a former Microsoft Research Fellow and has worked before at Nokia Research, and Lancaster University. His work and publications can be viewed at http://www.fahim-kawsar.net.
  • SAP Cloud Analytics - get control on BigData Jun 21 2017 10:00 am UTC 60 mins
    Iver van de Zand
    BigData requires processing performance but even more it requires agility of your cloud analytics. Iver will demonstrate how today's SAP BusinessObjects Cloud has leading capabilities when used in a highly complex and dynamic environment accessing extreme data volumes.
  • Big Data and real time analytics in the IoT: From measurement to knowledge Jun 21 2017 9:00 am UTC 45 mins
    Raquel López Alarcón, Sofia2 Platform Architect
    Do you want to get actual knowledge from your data, to understand it and to predict what will happen next? We will see what it takes from the device to the dashboard.

    In this webinar, we will discuss:
    - Use cases of IoT Analytics in different areas.
    - Architectural components & strategy required for a complete IoT solution.
    - Application Example.
  • Big Data analytics for IoT: Making sense of data from sensors Jun 21 2017 8:00 am UTC 45 mins
    Muralidhar Somisetty, Co-founder and CTO, Innohabit
    Big data analytics is undoubtedly one of the most exciting areas in computing today, and remains an area of fast evolution. Thanks to the data deluge from millions of sensors from IoT networks, it is humanly impossible to analyse and make sense of the data from sensors without analytics tools and processes.

    In this webinar, we will go over basics of big-data analytics, how analytics is different from traditional data warehouses or business intelligence systems, different tiers of data analytics etc., We will also see different use-cases of IoT from Smart Home to Transporation to Smart City context and how analytics can be applied for various use-cases for actionable insights.

    Webinar also briefly touches upon machine learning tools / techniques that are available as-a-service on cloud today.
  • Apache Zeppelin in the Enterprise: Build, Secure & Reuse Data Pipelines w Spark Jun 16 2017 2:00 pm UTC 45 mins
    Eric Charles, Founder at Datalayer
    Apache Zeppelin is a great entry point for Data Scientist to explore and model Data.

    In an enterprise environment, this exploration tool can be used to assemble pipeline of notes and deploy them in a production system.

    In this webinar, you will learn how to:

    + Create functional notes corresponding to each step of the analysis.
    + Call a note from another note.
    + Pipe multiple notes together.
    + Create a deployable unit and run this unit on a remote cluster
  • Makeover Monday: improving the way we visualize data, one chart at a time Recorded: May 15 2017 63 mins
    Andy Kriebel, Head Coach at The Data School, Tableau Zen Master & Eva Murray Tableau Evangelist at EXASOL, Tableau Trainer
    Join Andy Kriebel and Eva Murray to hear about #MakeoverMonday, the popular social data project linking hundreds of members from the global data visualization community in an effort to create better charts and more useful data stories.

    In this webinar Andy and Eva will share how Makeover Monday not only results in thousands of better data visualizations, but also helps people find their 'voice' in the community and land their dream jobs all while becoming better analysts and story tellers.

    They will also discuss the challenge for week 20, present their own makeovers, and the design and thought process that went into them.
  • Power BI Data Analytics and Visualization Recorded: May 8 2017 47 mins
    Priyanka Mane, Technology Consultant at Saviant Consulting
    Join this webinar to learn:

    1. What is Power BI?
    a. More power to Business Inteligence

    2. Why Power BI?
    a. Analytics
    b. Visualization

    3. How?
    a. Which data sources we can connect and analyse with Power BI?
    b. How to connect those data sources to Power BI?
    c. What is the role of R as a data source?
    d. How to visualise and Analyse?
    i. Design skills
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    iii. Analytics patterns
    1. Custom visuals
    2. R Custom visuals (Predictive Analytics)

    4. What about Backend Management?
    a. Excel / Azure SQL / Azure Storage or Other
    b. Custom Tables / Columns / Measures
    i. What / Why / How?

    5. Power BI Updates
    a.Monthly Updates
    b. Power BI Community for queries and request/issues updates
    i. How to use this?
  • Tensorflow: Architecture and use case Recorded: Apr 21 2017 49 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
  • The Secrets to WINNING with Machine Learning Recorded: Apr 13 2017 39 mins
    Patrick Rice, CEO, Lumidatum
    It’s easy to get caught in the excitement of machine learning and start optimizing RMSE, AUC or recall, but machine learning success starts with aligning to the business.

    Join Patrick Rice, CEO of Lumidatum, as he leverages his decade of experience in big data analytics including implementing machine learning solutions at Amazon to outline the secrets to winning at machine learning and delivering real ROI to the business.
  • The Ways Machine Learning and AI Can Fail Recorded: Apr 13 2017 48 mins
    Brian Lange, Partner and Data Scientist, Datascope
    Good applications of machine learning and AI can be difficult to pull off. Join Brian Lange, Partner and Data Scientist at data science firm Datascope, as he discusses a variety of ways machine learning and AI can fail (from technical to human factors) so that you can avoid repeating them yourself.
  • Different Strategies of Scaling H2O Machine Learning on Apache Spark Recorded: Apr 13 2017 46 mins
    Jakub Hava, Software Engineer at H2O.ai
    Sparkling Water integrates H2O, open source distributed machine learning platform, with the capabilities of Apache Spark. It allows users to leverage H2O’s machine learning algorithms with Apache Spark applications via Scala, Python, R or H2O’s Flow GUI which makes Sparkling Water a great enterprise solution.

    Sparkling Water 2.0 was built to coincide with the release of Apache Spark 2.0 and introduces several new features. One of the latest and largest features is the ability to configure Sparkling Water for different workloads, scale and optimize the platform according to your data and needs.

    In this talk we will introduce the basic architecture of Sparkling Water, go over different scaling strategies and explain the pros and cons of each solution. We will also compare the approaches with regards to the specific use cases and provide the rationale why or why not each solution may be a good fit for the desired use case.

    This talk will finish with a live demo demonstrating the mentioned approaches and should give you a real time experience of configuring and running Sparkling Water for your use case(s)!
  • Machine Learning Is Set To Unlock The Power of Business Intelligence Recorded: Apr 13 2017 46 mins
    Boaz Farkash - Head of Product Management, Sisense and Philip Lima - CEO, Mashey
    Machine learning can identify patterns that humans tend to overlook or can’t find easily in masses of data.

    When it comes to business intelligence, machine learning brings real opportunity to:

    - Automatically uncover business insights
    - Help make products more suggestive in nature
    - Empower users to get value faster out of their BI projects
    - Reduce implementation complexities
    - Generate predictive models

    Organizations have begun to notice that by using machine learning, they are able to make new discoveries, as well as identify and solve issues faster, gaining the competitive edge over their competition.

    Join Boaz Farkash, Sisense Head of Product Management and Philip Lima, Mashey’s CEO, as they explore how Machine Learning is unlocking the power of Business Intelligence.

    To be discussed:

    - The Rise of the All-in-One Machines
    - Machine Learning is Revolutionizing Immediate Decision Making
    - The Power of Business Intelligence Bots
    - How Smart Can One Machine Be?
    - What Lies Ahead
  • Data Science in Modern Banking Recorded: Apr 13 2017 45 mins
    Charlie Leahy, Head of Software Architecture and Data Science (Hufsy)
    Banks have a vast wealth of mineable data available to them, but traditionally have provided their customers with little feedback beyond a balance and list of transactions.

    In this talk Charles Leahy, Tech Lead at Hufsy, looks at ways in which tools such as visualisation and machine learning can be employed to give users meaningful insights, helping them make the most of their money.
  • Applied Data Science Recorded: Apr 13 2017 49 mins
    Giovanni Lanzani, Chief Science Officer at GoDataDriven
    Now that the Data Science hype is levelling out, many companies are wondering what went wrong as they could not extract values from their data science efforts.

    In this webinar we will explore what does it take to apply data science and machine learning in the real world.

    Key takeaways include:
    - How can you go beyond the traditional data warehouse when doing machine learning
    - How should you adapt your processes to keep monetizing on your data
    - How to close the feedback loop between your customers and your machine learning models
    - What kind of profiles are essential to successfully become a data driven organization
Make smarter moves with your big data management
Make smarter moves with your big data management

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