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    • Building a multi-purpose Data Lake for Increased Business Agility.
      Building a multi-purpose Data Lake for Increased Business Agility. Pablo Alvarez, Director of Product Management at Denodo. Upcoming: Mar 27 2018 9:00 am UTC 60 mins
    • The data contained in the data lake is too valuable to restrict its use to just data scientists. It would make the investment in a data lake more worthwhile if the target audience can be enlarged without hindering the original users. However, this is not the case today, most data lakes are single-purpose. Also, the physical nature of data lakes have potential disadvantages and limitations weakening the benefits and possibly even killing a data lake project entirely.

      A multi-purpose data lake allows a broader and greater use of the data lake investment without minimizing the potential value for data science or for making it a less flexible environment. Multi-purpose data lakes are data delivery environments architected to support a broad range of users, from traditional self-service BI users to sophisticated data scientists.

      Attend this session to learn:

      * The challenges of a physical data lake
      * How to create an architecture that makes a physical data lake more flexible
      * How to drive the adoption of the data lake by a larger audience

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    • Make Sure You Pack Data Management for Your Journey to Cloud
      Make Sure You Pack Data Management for Your Journey to Cloud Philip Russom, Ph.D., Sr. Research Director, Data Management Recorded: Mar 20 2017 5:05 pm UTC 19 mins
    • Your journey to cloud can take many forms. For example, you may move your whole data center or just single applications and databases. You may move existing solutions or build new green-field ones on the cloud, such as Hadoop implementations and data lakes. And you may evolve into a cloud-only architecture or one that’s a hybrid mix of multiple platforms on clouds and on premises. All of these journeys involve a migration of massive amounts of diverse data, and so require substantial data management infrastructure, tools, and best practices, during both development and production. TDWI’s Philip Russom will tell you what data management best practices to pack for success in your journey to cloud, regardless of the path you take.

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    • Data Preparation Done Right
      Data Preparation Done Right Davinder Mundy, Specialist Big Data Technologies, Informatica Upcoming: May 9 2018 9:00 am UTC 45 mins
    • How do you avoid your enterprise data lake turning into a so-called data swamp? The explosion of structured, unstructured and streaming data can be overwhelming for data lake users, and make it unmanageable for IT. Without scalable, repeatable, and intelligent mechanisms for cataloguing and curating data, the advantages of data lakes diminish. The key to solving the problem of data swamps is Informatica’s metadata driven approach which leverages intelligent methods to automatically discover, profile and infer relationships about data assets. Enabling business analysts and citizen integrators to quickly find, understand and prepare the data they are looking for.

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    • Deep Dive and Demo on Informatica 10.2: Data Management Reimagined with AI
      Deep Dive and Demo on Informatica 10.2: Data Management Reimagined with AI 1. Awez Syed, VP, Product Management, 2. Amit Kara, Product Marketing, Informatica Recorded: Nov 15 2017 5:00 pm UTC 64 mins
    • The need for businesses to become more agile and lead intelligent disruptions using data has never been stronger. To help you unleash the disruptive power of data, Informatica reimagines data management with its latest release of 10.2, powered by the CLAIRE™ engine using metadata-driven Artificial Intelligence (AI). Informatica Release 10.2, provides an intelligent, scalable and integrated platform for managing any data across your enterprise to accelerate data-driven digital transformation.

      Discover how AI enhances the intelligent capabilities of key products and solutions in 10.2 and deep dive into these offerings:
      -Industry leading enterprise data catalog
      -Out-of-the-box, end-to-end data governance and compliance
      -Cloud data lake management and real-time intelligent streaming
      -Detect and protect critical data with intelligent data security
      -Enterprise-scalable hybrid and multi-cloud deployments

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    • Great Data for Great Analytics: Best Practices for Data Management
      Great Data for Great Analytics: Best Practices for Data Management Philip Russom, Research Director for Data Management, TDWI & David Lyle, VP Product Strategy, Informatica, Recorded: Jan 27 2015 7:00 pm UTC 59 mins
    • The verdict is in. Data is now broadly perceived as a source of competitive advantage. No wonder many organizations view their Analytics initiative as highly strategic. Yet, many Analytics initiatives fail to deliver their promised value. Pretty visualizations and dashboards are only as good as their underlying unrefined data. Simply put: ‘garbage in-garbage out’. What is needed is great data.

      However, business leaders often fail to recognize the inherent complexities in building and maintaining a great data foundation for Analytics. Oversimplification leads to disappointing Analytics initiatives, and hence bad decision making.

      In order to deliver great data you need to:
      •Integrate data from many different systems, on-premise, in Hadoop, or in the cloud
      •Combine data from all the different data sources
      •Ensure the data is of the highest quality
      •Operationalize a repeatable process for generating and modifying reusable reports at the speed of business.

      In this webinar, hosted by David Lyle of Informatica, Philip Russom of TDWI will walk us through the potential data pitfalls, which a corporation should consider when designing a successful Analytics effort. Philip will share best practices for managing data, in order to promote an Analytics initiative that is truly based on great data. And David will discuss how Informatica can help you make better decisions with great data that’s refined, so you spend more time analyzing and less time finding and fixing data errors.

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    • Answering your research data management needs: Mendeley Data Launch
      Answering your research data management needs: Mendeley Data Launch Wouter Haak, VP, Research Data Management Solutions Upcoming: Apr 5 2018 2:00 pm UTC 60 mins
    • Ready access to research data is a cornerstone for success in science. Researchers need to keep track of their data & improve its impact through increased re-use. Universities want to eliminate re-work, showcase research outputs & improve collaboration inside and outside to drive research performance. These needs become more urgent as international funding bodies revise their policies to encourage, or even mandate, institutions and their researchers to make research data available.

      In this webinar we will introduce Mendeley Data, a platform designed to facilitate the comprehensive utilization of data. Consisting of five modules, this open, cloud-based platform helps research institutions to manage the entire life-cycle of research data, and enables researchers to safely access and share information wherever they are.

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    • Master-Data Fueled Supplier Management with MDM – Supplier 360
      Master-Data Fueled Supplier Management with MDM – Supplier 360 Barry Wildhagen, Senior MDM Specialist, Informatica Recorded: Dec 12 2017 10:00 am UTC 46 mins
    • If you are in supply chain management, procurement, or supplier relationship management, you are shifting from playing a tactical role to a strategic one. As trusted advisors to internal business partners, you need to fundamentally support the success of your organization’s innovation and digital transformation.

      However, quite often, supply chain, buying and sourcing teams struggle to access a single view of all supplier data so they can understand the total supplier relationship across the business.
      Does this sound familiar to you?
      Join this webinar and learn how leverage MDM – Supplier 360 to:
      - Have quick access to trusted, governed and relevant supplier data in order to make the right decisions, respond quickly, monitor supplier performance and detect anomalies, i.e. related to supplier risk and compliance
      - Standardize and automate operational processes and workflows, like supplier onboarding, reducing manual and redundant workloads
      - Accelerate time-to-market
      - Improve supplier collaboration and supplier relationship management
      - Quickly react to changing market requirements and deal with demand volatility
      - Evaluate supplier spend management

      Barry Wildhagen is a Senior MDM Specialist with strong background in master-data fueled supplier management solutions. Working closely with global enterprise customers, he understands the trends, challenges and needs of supply chain organizations and how to address them.

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    • Transform Big Data Management into a Big Advantage
      Transform Big Data Management into a Big Advantage Mark Beyer, VP & Distinguished Analyst, Gartner & Awez Syed, VP Product Management, Informatica Recorded: Mar 17 2016 7:55 pm UTC 27 mins
    • Watch Gartner VP and Distinguished Analyst, Mark Beyer, along with Informatica VP of Product Marketing, Awez Syed, as they discuss big data management.

      Big data offers new opportunities and new challenges. Gartner has stated, “Through 2018, 70% of Hadoop deployments will fail to meet cost savings and revenue generation objectives due to skills and integration challenges.” But a new class of big data management solutions is enabling organizations to consistently and reliably meet business demands and deliver business value. Capabilities like self-service data preparation combined with common sense approaches to data security, data governance, and metadata management can enable organizations to turn big data into big value.

      Join this webinar to learn some of the opportunities of big data management with Gartner’s Mark Beyer and learn how Informatica’s Big Data Management solution can help your organizations turn more data into business value without more risk from Informatica's Awez Syed.

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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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    • Successful Application Consolidation & Migration: Data Management Best Practices
      Successful Application Consolidation & Migration: Data Management Best Practices Philip Russom, Research Director for Data Management, TDWI & Rob Myers, Technical Delivery Manager, Informatica Recorded: Mar 10 2015 5:00 pm UTC 57 mins
    • According to Gartner, “through 2019, more than 50% of data migration projects will exceed budget and/or result in some form of business disruption due to flawed execution."(1) Furthermore, 1 in 6 large IT projects go over budget by 200%, according to a Harvard Business Review article. It is widely recognized that application migration and consolidation projects are “risky business” – high-ticket items for the corporation, with a scary chance of failing. If you are undertaking any IT modernization or rationalization project, such as consolidating applications or migrating applications to the cloud or ‘on-prem’ application, such as SAP, this webinar is a must-see.

      The webinar is going to shine the light on the critical role that data plays in the success or failure of these projects. Application data consolidation and migration is typically 30% to 40% of the application go-live effort. There is a multitude of data issues that can plague a project like this and lead to its doom, and these are not always recognized and understood early on, which is the biggest problem.

      In this webinar, Philip Russom of TDWI will walk us through the potential data pitfalls a corporation should consider when undertaking an application consolidation or migration project. Philip will share best practices for managing data in order to minimize risks and ensure on-time and on-budget delivery of these projects. Rob will discuss Informatica’s unique methodology and solution to support these best practices. Rob will also share real-life examples on how Informatica is helping customers reduce risks and complete application consolidation and migration projects on budget and on schedule.

      1)Gartner report titled "Best Practices Mitigate Data Migration Risks and Challenges" published on December 9, 2014

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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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    • Cloud Data Synergy, from Data Lakes and Data Warehouse to ML and AI
      Cloud Data Synergy, from Data Lakes and Data Warehouse to ML and AI GigaOm, Qubole & Snowflake Recorded: Mar 19 2018 10:35 pm UTC 63 mins
    • This 1-hour webinar from GigaOm Research brings together leading minds in cloud data analytics, featuring GigaOm analyst Andrew Brust, joined by guests from cloud big data platform pioneer Qubole and cloud data warehouse juggernaut Snowflake Computing. The roundtable discussion will focus on enabling Enterprise ML and AI by bringing together data from different platforms, with efficiency and common sense.

      In this 1-hour webinar, you will discover:

      - How the elasticity and storage economics of the cloud have made AI, ML and data analytics on high-volume data feasible, using a variety of technologies.
      - That the key to success in this new world of analytics is integrating platforms, so they can work together and share data
      - How this enables building accurate, business-critical machine leaning models and produces the data-driven insights that customers need and the industry has promised
      - How to make the lake, the warehouse, ML and AI technologies and the cloud work together, technically and strategically.

      Register now to join GigaOm Research, Qubole and Snowflake for this free expert webinar.

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    • Unified Data Management: The Best of Data Lakes, Data Warehouses and Streaming
      Unified Data Management: The Best of Data Lakes, Data Warehouses and Streaming Jason Pohl, Software Engineer at Databricks, and Bill Chambers, Product Manager at Databricks Recorded: Nov 16 2017 6:00 pm UTC 61 mins
    • Current data management architectures are a complex combination of siloed, single-purpose tools. There are data lakes for low cost storage, but are difficult to use for data discovery, data warehouses that are reliable and optimized for fast queries, but come at a cost when having to scale, and various streaming and batch systems to shuffle data between them, often times resulting in data integrity issues.

      Businesses have to create a patchwork of different tools, skillsets, and expertise just to solve one fundamental problem: How can I make data-driven decisions faster?

      Join this webinar to learn how Databricks Delta — a new unified data management system — takes advantage of the the scale of a data lake, the reliability and performance of a data warehouse, and the low-latency updates of a streaming system, all in a unified and fully managed fashion.

      This webinar will cover:
      -How the need to process batch and streaming data creates challenges for enterprises with complex data architectures.
      -How Databricks Delta takes the best of data warehouses, data lakes and streaming systems to provide a highly scalable, performant, and reliable data management system.
      -A live demonstration of Databricks Delta to showcase how easy it is to cost-efficiently scale without impacting query performance.

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