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Database Management

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  • Logistics Analytics: Predicting Supply-Chain Disruptions Logistics Analytics: Predicting Supply-Chain Disruptions Dmitri Adler, Chief Data Scientist, Data Society Recorded: Feb 16 2017 47 mins
    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 Unlock real-time predictive insights from the Internet of Things Sam Chandrashekar, Program Manager, Microsoft Recorded: Feb 16 2017 60 mins
    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.
  • Bridging the Data Silos Bridging the Data Silos Merav Yuravlivker, Chief Executive Officer, Data Society Recorded: Feb 15 2017 48 mins
    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.
  • Strategies for Successful Data Preparation Strategies for Successful Data Preparation Raymond Rashid, Senior Consultant Business Intelligence, Unilytics Corporation Recorded: Feb 14 2017 33 mins
    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 Virtualization: An Introduction (Packed Lunch Webinars) Data Virtualization: An Introduction (Packed Lunch Webinars) Paul Moxon, VP Data Architectures & Chief Evangelist, Denodo Recorded: Feb 10 2017 56 mins
    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
  • Building Enterprise Scale Solutions for Healthcare with Modern Data Architecture Building Enterprise Scale Solutions for Healthcare with Modern Data Architecture Ramu Kalvakuntla, Sr. Principal, Big Data Practice, Clarity Solution Group Recorded: Nov 10 2016 47 mins
    We all are aware of the challenges enterprises are having with growing data and silo’d data stores. Businesses are not able to make reliable decisions with un-trusted data and on top of that, they don’t have access to all data within and outside their enterprise to stay ahead of the competition and make key decisions for their business.

    This session will take a deep dive into current Healthcare challenges businesses are having today, as well as, how to build a Modern Data Architecture using emerging technologies such as Hadoop, Spark, NoSQL datastores, MPP Data stores and scalable and cost effective cloud solutions such as AWS, Azure and BigStep.
  • Data at the corner of SAP and AWS Data at the corner of SAP and AWS Frank Stienhans, CTO, Ocean9 Recorded: Nov 9 2016 48 mins
    Past infrastructures provided compute, storage and network enabling static enterprise deployments which changed every few years. This talk will analyze the consequences of a world where production SAP and Spark clusters including data can be provisioned in minutes with the push of a button.

    What does it mean for the IT architecture of an enterprise? How to stay in control in a super agile world?
  • 3 Critical Data Preparation Mistakes and How-to Avoid them 3 Critical Data Preparation Mistakes and How-to Avoid them Mark Vivien, Business Development, Big Data Recorded: Oct 20 2016 32 mins
    Whether you're just starting out or a seasoned solution architect, developer, or data scientist, there are most likely key mistakes that you've probably made in the past, may be making now, or will most likely make in the future. In fact, these same mistakes are most likely impacting your company's overall success with their analytics program.

    Join us for our upcoming webinar, 3 Critical Data Preparation Mistakes and How to avoid them, as we discuss 3 of the most critical, fundamental pitfalls and more!

    • Importance of early and effective business partner engagement
    • Importance of business context to governance
    • Importance of change and learning to your development methodology
  • Practical Data Cleaning Practical Data Cleaning Lee Baker, CEO, Chi-Squared Innovations Recorded: Oct 13 2016 38 mins
    The basics of data cleaning are remarkably simple, yet few take the time to get organized from the start.

    If you want to get the most out of your data, you're going to need to treat it with respect, and by getting prepared and following a few simple rules your data cleaning processes can be simple, fast and effective.

    The Practical Data Cleaning webinar is a thorough introduction to the basics of data cleaning and takes you through:

    • Data Collection
    • Data Cleaning
    • Data Classification
    • Data Integrity
    • Working Smarter, Not Harder
  • Self-service BI for SAP and HANA – Dream or Reality? Self-service BI for SAP and HANA – Dream or Reality? Swen Conrad, CEO, Ocean9 Recorded: Sep 14 2016 48 mins
    Gartner predicts that “analytics will be pervasive … for decisions and actions across the business.” Sounds like analytics nirvana with instant access for any analysis you want to do, in other words self-service BI. Is this dream or reality?

    Join this webinar to find out how clouds like AWS or Azure are moving the industry close to this nirvana today through simple assembly of cloud services combined with the appropriate consumption model of these services.

    We will demonstrate how easy it is to provision your high end SAP HANA Database right next to your BI Analytics tier.

    Maybe we are closer to this nirvana than you think?

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