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    • 5 Traps to Avoid and 5 Ways to Succeed with Big Data Analytics
      5 Traps to Avoid and 5 Ways to Succeed with Big Data Analytics Hal Lavender, Chief Architect, Cognizant, Thomas Dinsmore, BI & Big Data Expert, Josh Klahr, VP Product Management, AtScale D Recorded: Dec 20 2017 6:00 pm UTC 59 mins
    • When it comes to Big Data Analytics, do you know if you are on the right track to succeed in 2017?

      Is Hadoop where you should place your bet? Is Big Data in the Cloud a viable choice? Can you leverage your traditional Big Data investment, and dip your toe in modern Data Lakes too? How are peer and competitor enterprises thinking about BI on Big Data?

      Come learn 5 traps to avoid and 5 best practices to adopt, that leading enterprises use for their Big Data strategy that drive real, measurable business value.

      In this session you’ll hear from Hal Lavender, Chief Architetect of Cognizant Technologies, Thomas Dinsmore, Big Data Analytics expert and author of ‘Disruptive Analytics: Charting Your Strategy for Next-Generation Business Analytics, along with Josh Klahr, VP of Product, as they share real world approaches and achievements from innovative enterprises across the globe.

      Join this session to learn…

      - Why leading enterprises are choosing Cloud for Big Data in 2017
      - What 75% of enterprises plan to drive value out of their Big Data
      - How you can deliver business user access along with security and governance controls

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    • The Ideal Architecture for BI on Big Data
      The Ideal Architecture for BI on Big Data Scott Gidley Zaloni - VP of Product Management, Josh Klahr AtScale - VP of Product Recorded: Dec 14 2017 4:00 pm UTC 46 mins
    • Watch this online session and learn how to reconcile the changing analytic needs of your business with the explosive pressures of modern big data.

      Leading enterprises are taking a "BI with Big Data" approach, architecting data lakes to act as analytics data warehouses. In this session Scott Gidley, Head of Product at Zaloni is joined by Josh Klahr, Head of Product at AtScale. They share proven insights and action plans on how to define the ideal architecture for BI on Big Data.

      In this webinar you will learn how to

      - Make data consumption-ready and take advantage of a schema-on-read approach
      - Leverage data warehouse and ETL investments and skillsets for BI on Big Data
      - Deliver rapid-fire access to data in Hadoop, with governance and control

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    • Informatica Big Data Management Deep Dive and Demo
      Informatica Big Data Management Deep Dive and Demo Amit Kara, Big Data Technical Marketing, Informatica Recorded: Jan 28 2016 5:00 pm UTC 62 mins
    • Hadoop is not just for play anymore. Companies that are turning petabytes into profit have realized that Big Data Management is the foundation for successful Big Data projects.

      Informatica Big Data Management delivers the industry’s first and most comprehensive solution to natively ingest, integrate, clean, govern, and secure big data workloads in Hadoop.

      In this webinar you’ll learn through in depth product demos about new features that help you increase productivity, scale and optimize performance, and manage metadata such as:

      • Dynamic Mappings – enables mass ingestion & agile data integration with mapping templates, parameters and rules
      • Smarter Execution Optimization – higher performance with pushdown to DB, auto-partitioning and runtime job execution optimization
      • Blaze – high performance execution engine on YARN for complex batch processing
      • Live Data Map – Universal metadata catalog for users to easily search and discover data properties, patterns, domain, lineage and relationships

      Register today for this deep dive and demo.

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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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    • Tame the Complexity of Big Data Infrastructure
      Tame the Complexity of Big Data Infrastructure Tony Baer, Big Data Analyst, Ovum; Anant Chintamaneni, VP of Products, BlueData Recorded: Aug 12 2015 5:00 pm UTC 58 mins
    • Implementing Hadoop can be complex, costly, and time-consuming. It can take months to get up and running, and each new user group typically requires their own infrastructure.

      This webinar will explain how to tame the complexity of on-premises Big Data infrastructure. Tony Baer, Big Data analyst at Ovum, and BlueData will provide an in-depth look at Hadoop multi-tenancy and other key challenges.

      Join us to learn:

      - The pitfalls to avoid when deploying Big Data infrastructure
      - Real-world examples of multi-tenant Hadoop implementations
      - How to achieve the simplicity and agility of Hadoop-as-a-Service – but on-premises

      Gain insights and best practices for your Big Data deployment. Find out why data locality is no longer required for Hadoop; discover the benefits of scaling compute and storage independently. And more.

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    • Intelligent Data Lake : Valorisez les données issues du Big Data
      Intelligent Data Lake : Valorisez les données issues du Big Data Edouard Guérin - Spécialiste Big Data, Informatica Recorded: Dec 13 2016 10:00 am UTC 47 mins
    • La digitalisation du marketing et l’émergence de nouvelles applications génèrent un flux toujours plus important de données, de toutes formes et tailles. L’exploitation de ces informations permet de mieux cibler, acquérir et satisfaire la clientèle, cependant, trop peu de directions marketing parviennent à en tirer parti.

      Le 13 décembre à 11 heures, participez à notre webinaire Intelligent Data Lake et découvrez grâce à des exemples concrets de mise en œuvre comment :
      - Visualiser le parcours client global pour identifier les programmes les plus efficaces et optimiser le mix marketing ;
      - Développer des stratégies efficaces pour mieux cibler et acquérir de nouveaux clients ;
      - Tirer profit des données issues du Big Data à travers tous les points de contact pour créer de la valeur métier.

      Informatica Intelligent Data Lake
      La solution Intelligent Data Lake d’Informatica offre la data préparation en libre-service, en combinant l’automatisation, l’intégration et la gestion de la qualité des données, aux capacités de gestion de la gouvernance et de la sécurité requises pour tirer la véritable valeur métier de tous types de données, tout en rationalisant les risques.

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    • What's Ahead in Big Data and Analytics
      What's Ahead in Big Data and Analytics Paul Nelson, Leena Joshi, and Balaji Mohanam Recorded: Dec 12 2017 11:20 pm UTC 61 mins
    • We have come a long way since the term "Big Data" swept the business world off its feet as the next frontier for innovation, competition and productivity. Hadoop, NoSQL and Spark have become members of the enterprise IT landscape, data lakes have evolved as a real strategy and migration to the cloud has accelerated across service and deployment models.

      On the road ahead, the demand for real-time analytics will continue to skyrocket alongside growth in IoT, machine learning, and cognitive applications. Meeting the speed and scalability requirements of these types of workloads requires more flexible and efficient data management processes – both on-premises and in the cloud. Flexible deployment and integration options will become a must-have for projects.

      Finally, the need for data governance and security is intensifying as businesses adopt new approaches to expand their data storage and access via data lakes and self-service analytics programs. As data, along with its sources and users, continues to proliferate, so do the risks and responsibilities of ensuring its quality and protection.

      Join us to watch the replay of "What's Ahead in Big Data and Analytics" to get real direction and practical advice on the challenges and opportunities to tackle in 2018.

      Read more >