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    • Succeeding with Big Data Analytics and Machine Learning in The Cloud
      Succeeding with Big Data Analytics and Machine Learning in The Cloud James E. Curtis Senior Analyst, Data Platforms & Analytics, 451 Research Recorded: Oct 10 2018 5:00 pm UTC 49 mins
    • The cloud has the potential to deliver on the promise of big data processing for machine learning and analytics to help organizations become more data-driven, however, it presents its own set of challenges.

      This webinar covers best practices in areas such as.

      - Using automation in the cloud to derive more value from big data by delivering self-service access to data lakes for machine learning and analytics
      - Enabling collaboration among data engineers, data scientists, and analysts for end-to-end data processing
      - Implementing financial governance to ensure a sustainable program
      - Managing security and compliance
      - Realizing business value through more users and use cases

      In addition, this webinar provides an overview of Qubole’s cloud-native data platform’s capabilities in areas described above.

      About Our Speaker:

      James Curtis is a Senior Analyst for the Data, AI & Analytics Channel at 451 Research. He has had experience covering the BI reporting and analytics sector and currently covers Hadoop, NoSQL and related analytic and operational database technologies.

      James has over 20 years' experience in the IT and technology industry, serving in a number of senior roles in marketing and communications, touching a broad range of technologies. At iQor, he served as a VP for an upstart analytics group, overseeing marketing for custom, advanced analytic solutions. He also worked at Netezza and later at IBM, where he was a senior product marketing manager with responsibility for Hadoop and big data products. In addition, James has worked at Hewlett-Packard managing global programs and as a case editor at Harvard Business School.

      James holds a bachelor's degree in English from Utah State University, a master's degree in writing from Northeastern University in Boston, and an MBA from Texas A&M University.

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    • Data Platforms 2018: Opening Keynote - Big Data Activation
      Data Platforms 2018: Opening Keynote - Big Data Activation Ashish Thusoo, CEO, Qubole Recorded: Apr 27 2018 5:05 pm UTC 38 mins
    • In this keynote Ashish Thusoo, CEO of Qubole, discusses the gap that enterprises face today when activating their big data. He makes a case for the shift that organizations need to make towards a big data activation strategy in order to put their data assets to use for differentiating and achieving business objectives. The session also covers key elements of big data activation supported by usage trends of Qubole's cloud-native big data activation platform. He presents various ways that enterprises can use to measure their own activation readiness, and demonstrate why Qubole provides the right approach to big data activation.

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    • Best Practices: Implementing DataOps with a Data Science Platform
      Best Practices: Implementing DataOps with a Data Science Platform Crystal Valentine, MapR Technologies & William Merchan, DataScience.com Recorded: Nov 7 2017 2:55 pm UTC 66 mins
    • With the growing number of data-driven organizations new approaches are needed to drive innovation in scaling and implementing data science. We will discuss how data and data science platforms take advantage of what we are calling DataOps. We will share background on this approach and how it supports putting data science models into production. We will provide best practices and a roadmap on how to implement these techniques to become a leader in machine learning and data science.

      Watch the recording of this complimentary webinar with experts from DataScience.com & MapR to:

      - Learn about the benefits of applying a DataOps approach to your data science workflow
      - Review best practices for how IT teams can support their data science teams
      - Hear how customers of MapR and DataScience.com have reaped the benefits of this new approach.

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    • Next-Level Data Lake Management with the Zaloni Data Platform
      Next-Level Data Lake Management with the Zaloni Data Platform Scott Gidley, VP of Product at Zaloni Recorded: Jun 26 2018 6:00 pm UTC 52 mins
    • The modern, data-rich enterprise demands access to data at a pace that has outclassed traditional data management platforms. Whether they are utilizing a cloud, hybrid, or on-prem solution, these organizations require capabilities that are vendor-neutral and often implemented with microservices to ensure an agile environment at scale.

      In this webinar, Scott Gidley, Zaloni’s Vice President of Product, will showcase the latest version of the Zaloni Data Platform. This version provides exciting new features to address the growing demands of data-driven companies, including:
      - Managing hybrid and multi-cloud environments
      - Managing your data with zones
      - Cloud-native support
      - Ingestion wizard
      - Platform global search
      - Persona-driven homepage

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    • Is the Traditional Data Warehouse Dead?
      Is the Traditional Data Warehouse Dead? James Serra, Data Platform Solution Architect, Microsoft Recorded: Mar 27 2018 3:00 pm UTC 61 mins
    • With new technologies such as Hive LLAP or Spark SQL, do you still need a data warehouse or can you just put everything in a data lake and report off of that? No! In the presentation, James will discuss why you still need a relational data warehouse and how to use a data lake and an RDBMS data warehouse to get the best of both worlds.

      James will go into detail on the characteristics of a data lake and its benefits and why you still need data governance tasks in a data lake. He'll also discuss using Hadoop as the data lake, data virtualization, and the need for OLAP in a big data solution, and he will put it all together by showing common big data architectures.

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    • Citizen Data Science Series - Selecting the Right Chart for What You Are Showing
      Citizen Data Science Series - Selecting the Right Chart for What You Are Showing Britton Stamper, Sales Engineer at Periscope Data Recorded: Oct 30 2018 5:00 pm UTC 30 mins
    • Once you’ve done analysis and found insights in your data, determining the right visualization is crucial to telling the right story. Even if you’ve done the work of selecting the right dataset, asking the right initial question, following up with the right additional queries and using your personal expertise to pinpoint valuable information, all of that analytical work loses value if the charting process is not done correctly.

      Choosing the right chart doesn’t need to be intimidating. Similar to data exploration, you just need to ask a series of straightforward questions.

      Join Britton Stamper, sales engineer at Periscope Data, when he addresses:
      - The first question to ask when building a data visualization
      - The different types of data relationships
      - When to use each type of chart
      - What variables to be aware of when building your chart

      This is the third webinar in our “Citizen Data Science Empowerment” series. The first webinar “Getting Started with Citizen Data Scientists” covered the importance of citizen data scientists, how to get them enabled and how to empower them. The second webinar, “How to Do Data Right,” covered the importance of making sure that you are doing your due diligence when evaluating the data to visualize.

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    • Sink or swim? Architecting the data lake to drive, survive and thrive.
      Sink or swim? Architecting the data lake to drive, survive and thrive. Matt Aslett, Research Director of Data Platforms & Analytics at 451 Research, and Kelly Schupp, VP of Marketing at Zaloni Recorded: Oct 31 2017 3:00 pm UTC 44 mins
    • Today, big data is enabling the advanced analytics that companies have dreamed of for driving their business. And as forward-thinking companies take advantage of big data and advanced analytics to drive digital transformation initiatives, it is forcing the laggards to realize that they will have to do the same if they want to survive.

      The generally accepted architectural model for harnessing big data is a data lake. But data lakes, if leveraged simply as cheap storage within which to dump data, will inevitably disappoint. As the saying goes, garbage in, garbage out. Data lakes present unique challenges that must be dealt with if that big data set is going to be turned into actionable information.

      So what does it take to succeed with a data lake? Why do some organizations get real value out of big data, while others struggle?

      In this webinar, Matt Aslett, Research Director of Data Platform and Analytics at 451 Research and Kelly Schupp, VP of Data-driven Marketing at Zaloni, will discuss ideal data lake use cases such as Customer 360 and IoT. They will also discuss Zaloni’s data lake maturity model with which the data-eager company can chart its ideal course and roadmap.

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    • Analytical Innovation: How to Build the Next Generation Data Platform
      Analytical Innovation: How to Build the Next Generation Data Platform James Curtis, Senior Analyst, Data Platforms & Analytics, 451 Research & Jacque Istok, Head of Data, Pivotal Recorded: Sep 14 2017 6:00 pm UTC 63 mins
    • There was a time when the Enterprise Data Warehouse (EDW) was the only way to provide a 360-degree analytical view of the business. In recent years many organizations have deployed disparate analytics alternatives to the EDW, including: cloud data warehouses, machine learning frameworks, graph databases, geospatial tools, and other technologies. Often these new deployments have resulted in the creation of analytical silos that are too complex to integrate, seriously limiting global insights and innovation.

      Join guest speaker, 451 Research’s Jim Curtis and Pivotal’s Jacque Istok for an interactive discussion about some of the overarching trends affecting the data warehousing market, as well as how to build a next generation data platform to accelerate business innovation. During this webinar you will learn:

      - The significance of a multi-cloud, infrastructure-agnostic analytics
      - What is working and what isn’t, when it comes to analytics integration
      - The importance of seamlessly integrating all your analytics in one platform
      - How to innovate faster, taking advantage of open source and agile software

      We look forward to you joining us.
      The Pivotal Team

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    • Turnkey Data Lake: The Fast Path to Business Insights
      Turnkey Data Lake: The Fast Path to Business Insights Nikhil Goel, Lead Architect in Product Management Recorded: Aug 29 2018 6:00 pm UTC 37 mins
    • Data storage, data compute. Data ingestion. Metadata management. Governance. Visibility. Privacy. Transparency. These are just a few of the considerations you must plan for when modernizing your data platform with a data lake. It can be overwhelming, especially if you try to stitch specialized point products together yourself. Data lake implementations can get out of scope and out of control quickly.

      Why pull your hair out trying to do it yourself? An actionable data lake is within reach. Join us as Nikhil Goel, Zaloni’s Lead Architect in Product Management, discusses the benefits that a turnkey data lake solution can provide as your data grows to meet your organization. Some of the topics covered will be:
      • Storage and compute layers for cloud and on-premises
      • Managed ingestion
      • Zone-based data architecture
      • Self-service access to the data catalog
      • Customer success stories

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    • Best Practices: How To Build Scalable Data Pipelines for Machine Learning
      Best Practices: How To Build Scalable Data Pipelines for Machine Learning Jorge Villamariona and Holden Ackerman, Qubole Upcoming: Nov 28 2018 6:00 pm UTC 60 mins
    • Data engineers today serve a wider audience than just a few years ago. Companies now need to apply machine learning (ML) techniques on their data in order to remain relevant. Among the new challenges faced by data engineers is the need to build and fill Data Lakes as well as reliably delivering complete large-volume data sets so that data scientists can train more accurate models.

      Aside from dealing with larger data volumes, these pipelines need to be flexible in order to accommodate the variety of data and the high processing velocity required by the new ML applications. Qubole addresses these challenges by providing an auto-scaling cloud-native platform to build and run these data pipelines.

      In this webinar we will cover:
      - Some of the typical challenges faced by data engineers when building pipelines for machine learning.
      - Typical uses of the various Qubole engines to address these challenges.
      - Real-world customer examples

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    • Adopting an Enterprise-Wide Shared Data Lake to Accelerate Business Insights
      Adopting an Enterprise-Wide Shared Data Lake to Accelerate Business Insights Ben Sharma, CEO at Zaloni; Carlos Matos, CTO Big Data at AIG Recorded: Sep 21 2017 8:50 pm UTC 68 mins
    • Today's enterprises need broader access to data for a wider array of use cases to derive more value from data and get to business insights faster. However, it is critical that companies also ensure the proper controls are in place to safeguard data privacy and comply with regulatory requirements.

      What does this look like? What are best practices to create a modern, scalable data infrastructure that can support this business challenge?

      Zaloni partnered with industry-leading insurance company AIG to implement a data lake to tackle this very problem successfully. During this webcast, AIG's VP of Global Data Platforms, Carlos Matos, and Zaloni CEO, Ben Sharma will share insights from their real-world experience and discuss:

      - Best practices for architecture, technology, data management and governance to enable centralized data services
      - How to address lineage, data quality and privacy and security, and data lifecycle management
      - Strategies for developing an enterprise-wide data lake service for advanced analytics that can bridge the gaps between different lines of business, financial systems and drive shared data insights across the organization

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    • Enterprise Data Storage, Lakes, Warehouses & More: A Crash Course
      Enterprise Data Storage, Lakes, Warehouses & More: A Crash Course Ted Sfikas, Director of Solutions Consultants, North America and LATAM, Tealium Recorded: Jul 31 2018 4:00 pm UTC 31 mins
    • Consumers are engaging with brands across multiple touchpoints, channels, and devices, generating massive amounts of valuable data. Organizations are quickly adopting a number of solutions to keep up with this explosion of customer data and better capture and correlate user behavior.

      Two common solutions brands are leveraging to house and analyze all of this customer data are Enterprise Data Warehouses (EDW) and Data Lakes. Register now for this 30-minute webinar and learn:

      - Key benefits of each and which is best for your brand

      - Why pairing your enterprise data storage solution with customer data initiatives makes your tech stack even more powerful

      - How an automated data supply chain fits in a modern EDW and data lake environment

      - And more!

      The webinar will conclude with a live Q&A Chat with questions from the audience on all things enterprise data storage.

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    • GDPR Best Practice: Using a Data Hub to Protect Personal Data
      GDPR Best Practice: Using a Data Hub to Protect Personal Data Remi Forest, MapR Technologies & Jean-Michel Franco, Talend Recorded: Jan 16 2018 1:55 pm UTC 52 mins
    • Is Your Data Ready for GDPR?

      As the deadline for GDPR approaches, it is time to get practical about protecting personal data.

      We break down the steps for turning a data lake into a data hub with appropriate data management and governance activities: from capturing and reconciling personal data to providing for consent management, data anomyzation, and the rights of the data subject.

      A smart approach to GDPR compliance lays a foundation for personalized and profitable customer and employee relations.

      Watch, as experts from MAPR and Talend show you how to:

      - Diagnose the maturity of your GDPR compliance;
      - Set up milestones and priorities to reach compliance;
      - Create a foundation to manage personal data through a data lake;
      - Master compliance operations - from data inventory to data transfers to individual rights management.

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    • Citizen Data Science Webinar Series - How To Do Data Right
      Citizen Data Science Webinar Series - How To Do Data Right Kyle Dempsey, Sr. Professional Services Engineer at Periscope Data Recorded: Sep 27 2018 5:00 pm UTC 26 mins
    • This is the second webinar in our “Citizen Data Science” series. Our first webinar, “Getting Started with Citizen Data Scientists,” covered the importance of citizen data scientists, how to get them enabled and how to empower them.

      To some citizen data scientists, data is a new language that they’re unfamiliar with translating into insights. For others, they’re eager to dive in and curious to explore, but reluctant to communicate their findings because they don’t have experience translating data into tactical operations.

      These new business-focused analysts need to be confident that they’re utilizing data properly. To empower these new data dives, Kyle Dempsey, senior professional services engineer at Periscope Data pulled together a collection of tips to make sure first-time analysts are doing data right.

      Join Kyle on September 27th, 2018 at 10 a.m. PDT as he walks through how to:
      - Define your analysis and outcomes
      - Understand what data is available and know how to ask for more
      - Ask questions in a way that allows data to answer them
      - Use data to inform decisions
      - Enable collaboration between technical and nontechnical teams

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