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Managing Big Data in the Bedrock Data Lake Management Platform

In this webinar, Adam Diaz, Director of Field Engineering at Zaloni, will demonstrate how the Bedrock platform can run as a data federation layer that makes it easy to organize and manage data, regardless of volume, across your enterprise data architecture.

Data Federation describes any approach to data management that allows an application to retrieve and manipulate data because it understands the metadata associated. To do this and obtain business value, an enterprise­-grade data lake management and governance platform like Bedrock is required. The use of data across multiple clusters, databases and streams of data is enabled via Bedrock workflows.

In this context, topics covered will include:

- Classic Enterprise Architectures and Data Siloing

- Data Lake 360 Solution: a Holistic Approach to Modern Data Management

- Industry Trends - Movement to the Cloud and Hybrid Environments

- Metadata Management - and Handling Non-Persistent Environments

- Introduction to Bedrock

- Demonstration of Bedrock - How do I manage multiple systems?
Recorded Jan 18 2017 43 mins
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Adam Diaz, Director of Field Engineering
Presentation preview: Managing Big Data in the Bedrock Data Lake Management Platform

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  • Technical Deep Dive: GDPR Compliance via a Governed Data Lake Recorded: Aug 3 2017 44 mins
    Ben Sharma, CEO & Co-Founder at Zaloni
    GDPR is quickly becoming a global data privacy crisis. With the May 2018 deadline looming, businesses in every industry are taking a fresh look at governing personal information. They’re finding out what’s needed to ensure compliance - and it’s not going to be easy.

    Big data thought leader, Ben Sharma, has years of experience in data management and governance. He will discuss the impact GDPR has on big data management and explain how data lakes can set you up for success, both for GDPR compliance and future governance endeavors. This webinar will discuss specific technical solutions. If you are concerned about your GDPR compliance initiative, or just interested in verifying your current path, then this is a must-attend webinar.

    Topics covered:
    - Data lineage
    - Masking of PII
    - Leveraging custom metadata
    - Data lifecycle management
    - Building a next-generation data architecture for compliance
    - Your GDPR preparation checklist

    In preparation for this deep dive into GDPR, we suggest you view our previous webinar on the basics of GDPR.
  • GDPR Compliance: Data Management Practices for Success Recorded: Jun 22 2017 34 mins
    Kelly Schupp, Vice President of Marketing
    You know GDPR is coming. And with it are substantial penalties for noncompliance. What do you need to do to ensure that you are ready?

    The General Data Protection Regulation (GDPR) is a European Union regulation set to go into effect May 25, 2018. This regulation requires that you strengthen data protection and management technologies and practices if you do business in the EU, have employees or customers that are EU citizens, or otherwise store or access data about European Union citizens. Among other things, GDPR addresses how personal data can be exported, the right for a citizen to control and delete their own personal data, data protection requirements and how data breaches are to be treated and a variety of other data and process-related rules and standards.

    In this webinar, Kelly Schupp, Vice President of Marketing at Zaloni, will discuss where GDPR sits in the world of big data, overall data lake strategies that help with compliance, and how metadata management is key to that strategy.

    Topics covered:
    - Metadata management
    - GDPR compliance and best practices
    - GDPR technologies
    - Data lake governance
  • Governed & Self-Service Data - Better Together Recorded: May 25 2017 27 mins
    Scott Gidley, Vice President of Product Development at Zaloni
    Today’s companies need actionable insights that are immediate. It is no longer feasible to wait weeks, even months, on IT to prepare business-critical data. Data lakes done right can enable you to view your entire data catalog at a moment’s notice and apply self-service transformations to that data. These interactions are key to providing a quick, clear understanding of business needs. But enterprises have a legitimate concern regarding data lake governance issues such as data privacy, data quality, security, and lineage. How do you marry both - how do you provide governed self-service to data in the data lake?

    In this presentation, Scott Gidley, Vice President of Product Development at Zaloni, will highlight the benefits of governed self-service data and will provide a brief demo of Zaloni’s Self-service Data Platform.

    Topics covered:

    - Metadata management, the foundation for governed self service in the data lake
    - Data catalogs
    - Self-service data preparation
    - Self-service ingestion
    - Bringing it all together with Zaloni’s Self-service Data Platform
  • Data Monetization: A Telecommunications Use Case Recorded: Mar 15 2017 38 mins
    Dirk Jungnickel, Senior Vice President of Business Analytics at du
    Telco operators have worked with big data even before it had a name. By making data work for them, they have improved quality of service and customer satisfaction and have been some of the first companies to truly monetize their data.

    Leveraging massive amounts of data has been a technical and architectural challenge. Most telco operators have adopted data lakes as cost-effective, highly scalable architectures for collecting and processing massive volumes of data and data types. Emirates Integrated Telecommunications Company (du), one of the UAE’s largest telecommunications companies, is addressing this issue with a game-changing modern data lake architecture.

    Dirk Jungnickel explains how Dubai-based telco leader du leverages big data to create smart cities and enable location-based data monetization, covering business objectives and outcomes and addressing technical and analytical challenges.

    Topics include:
    Architectural considerations
    Platform requirements for the IoT
    Performing root cause analysis
    The impact of data volume on pattern recognition
  • Building a Modern Data Architecture Recorded: Mar 15 2017 34 mins
    Ben Sharma
    Learn how to build a modern, scalable data architecture to get business results.

    When building your data stack, architecture could be your biggest challenge—yet it could also be the best predictor of success. With so many elements to consider and no proven playbook, where do you begin when assembling a scalable data architecture? Ben Sharma shares real-world lessons and best practices to get you started. If you are concerned with building a data architecture that will serve you now and scale for the future, this is a must-attend session.

    Topics include:

    • A recommended data lake reference architecture
    • Considerations for data lake management and operations
    • Considerations for data lake security and governance
    • Metadata management
    • Logical data lakes to enable ground-to-cloud hybrid architectures
    • Self-service data marketplaces for more democratized data access
  • Zaloni Bedrock and Mica: 20-minute Demonstration Recorded: Mar 9 2017 19 mins
    Greg Wood, Field Engineer at Zaloni
    See what an agile, scalable data lake looks like with Zaloni’s Data Lake 360 Platform

    Register to watch this 20-minute demonstration of an end-to-end use case for data management, governance, and self-service data within Bedrock Data Lake Management & Governance and Mica Data Lake Catalog & Self-Service.

    Highlights of this demonstration include:

    - A defined use case for ingesting and transforming sales data of various types and sources.

    - The data's journey through the Bedrock platform, including ingestion, applying metadata, developing workflows, examining the data lineage, and exposing the data catalog for self-service preparation.

    - How data is presented to end users and the features in Mica that they need to export the data for business analysis.
  • Everyone is a Stakeholder in a Data-Driven Enterprise Recorded: Mar 2 2017 50 mins
    Dave Wells, Research Analyst, Eckerson Group & Kelly Schupp, VP Marketing, Zaloni
    Almost everyone is concerned with the tooling to manage the big data lifecycle. From business people engaged with self-service analytics, to data scientists, data analysts, and data professionals from BI and IT organizations, it seems that nearly everyone is both a consumer and a provider of data.

    Big data management software spans the data lifecycle supporting data profiling, transformation, enrichment, cleansing, matching and other functions. It is the glue that binds a big data environment together, fostering continuous alignment of data with dynamic and changing business needs.

    During this webinar, Dave Wells, Research Analyst at Eckerson Group, and Kelly Schupp, VP of Data-driven Marketing at Zaloni, will discuss the tools, and how to leverage them for high-impact analytics, leveraging research from Dave’s recent industry report titled “Big Data Management Software for the Data-Driven Enterprise”. Topics addressed:

    - The kinds of tools that are needed to meet the challenges of big data
    - The purpose, functions, and characteristics of data preparation tools
    - The purpose, functions, and characteristics of pipeline management tools
    - The purpose, functions, and characteristics of data cataloging tools
    - The role of big data management tools for high-impact analytics

    Speaker Bios:

    Dave Wells is an advisory consultant, educator, and industry analyst at Eckerson Group. He is dedicated to building meaningful connections throughout the path from data to business value. He works at the intersection of information management and business management, driving business impact through analytics, business intelligence, and active data management.

    Kelly Schupp is Vice President of Marketing for Zaloni. Kelly has 20 years of experience in the enterprise software and technology industry. She has held a variety of global marketing leadership roles, and previously worked at IBM, Micromuse and Porter Novelli.
  • Techniques to Establish Your Data Lake: How to Achieve Data Quality and Security Recorded: Feb 16 2017 63 mins
    Ben Sharma, CEO and Co-Founder, Zaloni
    The growing volume and variety of data makes it imperative for organizations to manage and govern their data in a way that's scalable and cost-effective. The data lake – once considered just a relatively inexpensive storage solution – can now be a tool for deriving true business value. By implementing a set of best practices for establishing and managing your data lake, you can achieve 360-degree control and visibility of your data.

    In this webcast, Ben Sharma, Zaloni's co-founder and CEO discusses techniques to balancing the flexibility a data lake can provide with the requirements for privacy and security that are critical for enterprise data.

    Topics covered include:

    - How to establish a managed data ingestion process - that includes metadata management - in order to create a solid foundation for your data lake

    - Techniques for establishing data lineage and provenance

    - Tips for achieving data quality

    - Key considerations for data privacy and security

    - Unique stages along the data lake lifecycle and management concepts for each stage

    - Why a data catalog is important

    - Considerations for self-service data preparation

    About the speaker:

    Ben Sharma is CEO and co-founder of Zaloni. He is a passionate technologist and thought leader in big data, analytics and enterprise infrastructure solutions. Having previously worked in technology leadership at NetApp, Fujitsu and others, Ben's expertise ranges from business development to production deployment in a wide array of technologies including Hadoop, HBase, databases, virtualization and storage. Ben is co-author of Architecting Data Lakes and Java in Telecommunications. He holds two patents.
  • Data Warehouse Augmentation: Cut Costs, Increase Power Recorded: Jan 26 2017 46 mins
    Pradeep Varadan and Scott Gidley
    The data warehouse (DW) is one of the most effective tools for complex data analytics. But the downside is… it can drain your budget. How do you maximize the value of your DW and save on storage costs?

    Don't clog your DW's analytics bandwidth with less valuable storage and ETL processing. Those in the know are migrating storage and large-scale or batch processing to data lakes built on scale-out architectures such as Hadoop and the Cloud to save on costs and get increased processing power for the DW.

    Pradeep Varadan, Verizon's Wireline OSS Data Science Lead and Scott Gidley, Zaloni's VP, Product Management, discuss the benefits of augmenting your DW with a data lake. They also address how migrating to a data lake allows you to efficiently exploit original raw data of all types for data exploration and new use cases.

    Topics covered include:

    - Reducing storage costs
    - Increasing process speeds
    - Maximizing EDW for business intelligence
    - Extending data retention and extracting more value from all data

    About the Speaker:

    Pradeep Varadan is a data scientist and enterprise architect who specializes in data challenges within telecommunications. As the Wireline OSS Data Science Lead at Verizon Data Services, Pradeep is tasked with providing a competitive edge focused on utilizing data analytics to drive effective decision-making. He is skilled in creating systems that can be used to understand and make better decisions involving rapid technology shifts, customer lifestyle and behavior trends and relevant changes that impact the Verizon Network.
  • Managing Big Data in the Bedrock Data Lake Management Platform Recorded: Jan 18 2017 43 mins
    Adam Diaz, Director of Field Engineering
    In this webinar, Adam Diaz, Director of Field Engineering at Zaloni, will demonstrate how the Bedrock platform can run as a data federation layer that makes it easy to organize and manage data, regardless of volume, across your enterprise data architecture.

    Data Federation describes any approach to data management that allows an application to retrieve and manipulate data because it understands the metadata associated. To do this and obtain business value, an enterprise­-grade data lake management and governance platform like Bedrock is required. The use of data across multiple clusters, databases and streams of data is enabled via Bedrock workflows.

    In this context, topics covered will include:

    - Classic Enterprise Architectures and Data Siloing

    - Data Lake 360 Solution: a Holistic Approach to Modern Data Management

    - Industry Trends - Movement to the Cloud and Hybrid Environments

    - Metadata Management - and Handling Non-Persistent Environments

    - Introduction to Bedrock

    - Demonstration of Bedrock - How do I manage multiple systems?
  • Data Lake 360: Extending Storage and Lifecycle of Data Recorded: Oct 5 2016 40 mins
    Gus Horn and Scott Gidley
    Highly competitive enterprises are continually looking for ways to maximize and accelerate value that can be derived from their data. The influx of diverse data is causing data lakes to emerge as a powerful architectural approach. Data lakes allow you to analyze the most relevant and valuable data stored in the most efficient and high performing way possible. The question is: Are you managing the life of your data in your data lake correctly?

    Gus Horn, NetApp’s Senior Global Consulting Engineer and Scott Gidley, Zaloni’s VP, Product Management, discuss effective data lake lifecycle management and data architecture modernization. This webinar addresses the best ways to achieve new levels of data insight and how to get superior value from your data.

    Topics covered include:

    - Improving infrastructure efficiency
    - Building smaller, more efficient analytics platforms
    - Capabilities of Zaloni's Bedrock Data Lake Management Platform
    - Defining logical data lakes on and off the premises or a combination of both with NetApp E-Series and NetApp StorageGRID® Webscale
    - Extending storage and lifecycle of the data

    About the Speaker:

    Gus Horn has over 25 years experience of product and software development with a proven track record in quality product delivery. Horn has been immersed in the Big Data Analytic World, designing and building for some of the largest enterprise class analytic platforms in the world. Horn is currently Senior Global Consulting Engineer at NetApp. He is responsible for both strategic and tactical advancement of analytics, data management and integration solutions.
  • The Four Zones of Data Lake Architecture Recorded: Sep 27 2016 28 mins
    Ben Sharma, Founder & CEO of Zaloni
    Data lakes make more sense when you think about the architecture in zones. Don’t miss this encore lecture from Ben Sharma, CEO and Co-Founder of Zaloni. Ben uses illustrations of a reference architecture to describe the concept of 4 zones for envisioning the data lake:

    Transient landing zone
    Raw zone
    Trusted zone
    Refined zone

    By understanding the inputs, outputs, processes, and policies within each zone, you can take your implementation further, evaluating a holistic approach and rethinking the possibilities when it comes to build vs buy for the future of your data lake management.
  • The 360-Degree Approach to Managing a Data Lake Recorded: Aug 31 2016 54 mins
    Adam Diaz and Kelly Schupp
    In order to achieve the agility, shorter time-to-insight, and scalability that a big data lake promises today’s enterprise, customers need a unified, holistic approach that addresses data visibility, reliability, security and privacy and provides democratized access to useful data. Zaloni’s Data Lake 360° solution addresses the need for this holistic approach, giving complete control and full visibility into data lakes by providing a 360-degree view.

    Join Adam Diaz, Director of Field Engineering, for a discussion about how Zaloni's Data Lake 360° Solution reduces the complexity of creating a modern, integrated big data architecture for advanced analytics and data science. A demo of the latest versions of Bedrock and Mica is provided.

    About the speaker:

    Adam Diaz is a long time technologist working in the software industry for roughly twenty years. With roots in Bioinformatics, Statistics and CAD/CAE, Adam has spent many years with both HPC and Hadoop to enable high performance and parallel computing customer data solutions at scale. His background includes companies like SAS, Teradata, Hortonworks and MapR. Adam currently works at Zaloni enabling Hadoop Data Lake solutions utilizing Bedrock as the Director of Field Engineering.
  • Risky Business: How to Balance Innovation & Risk in Big Data Recorded: Aug 25 2016 50 mins
    Nik Rouda and Scott Gidley
    Big data is a game-changer for organizations that use it right. However, a dynamic tension always exists between rapid innovation using big data and the high level of production maturity required for an enterprise implementation. Is it possible to find the right mix?

    We say yes. Nik Rouda, senior big data analyst for Enterprise Strategy Group, reveals insights from his research and best practices for success. Join Nik and Zaloni’s Vice President of Product, Scott Gidley, for a discussion on how to find that balance between the lofty promises of big data and the mundane necessities of building a data lake environment that delivers business value.

    Topics covered include:

    - Big data business priorities and real-life use cases

    - The range of people and organizations involved in big data projects

    - A look at the time-to-business value that most organizations experience

    - An overview of the qualities and capabilities desired in data lakes

    - A typical data lake adoption lifecycle

    - Zaloni’s Data lake 360 solution as a holistic approach to building and leveraging a big data lake

    About the speaker:

    ESG Senior Analyst Nik Rouda covers big data, analytics, business intelligence, databases, and data management. With 20 years of experience in IT around the world, he understands the challenges of both vendors and buyers, and how to find the true value of innovative technologies. Using the knowledge of strategic leadership that he gathered previously helping to accelerate growth for fast-paced startups and Fortune 100 enterprises, Nik’s goal is to strengthen messaging, embolden market strategy, and ultimately, maximize his client’s gain.
  • Understanding Metadata: Why it's essential to your big data solution Recorded: Jun 21 2016 63 mins
    Ben Sharma and Vikram Skreekanti
    Metadata is essential for managing, migrating, accessing, and deploying a big data solution. Without it, enterprises have limited visibility into the data itself and cannot trust in its quality—negating the value of data in the first place. Creating end-to-end data visibility allows you to keep track of data, enable search and query across big data systems, safeguards your data, and reduces risk.

    In this O'Reilly webcast replay, Ben Sharma (co-founder and CEO of Zaloni) and Vikram Sreekanti (software engineer in the AMPLab at UC Berkeley) discuss the value of collecting and analyzing metadata, and its potential to impact your big data solution and your business.

    Learning how to access to your data's lineage allows you to know where data has come from, where it is, and how it is being used. This webinar takes a deep dive into a new open-source project under development at UC Berkeley — Ground. Ground is a data context system that enables users to uncover what data they have, where the data is flowing to and from, who is using the data, and when and how it changes. We explore how data context stretches the bounds of what we have traditionally considered metadata.

    Topics covered include:

    - The role of metadata in data analysis

    - Key considerations for managing metadata

    - How to establish data lineage and provenance, in order to create a repeatable process

    - How Ground is making an impact on a wide range of data tasks, including data inventory, usage tracking, model-specific interpretation, reproducibility, interoperability, and collective governance

    - Initial work on Ground, and how this data context system is making an impact on a wide range of data tasks, including: data inventory, usage tracking, model-specific interpretation, reproducibility, interoperability, and collective governance
  • Fireside Chat with Ovum Research: Developing a Strategy for Data Lake Governance Recorded: May 18 2016 56 mins
    Tony Baer, Ovum Research & Scott Gidley, VP of Product Management
    In Ovum’s upcoming Big Data Trends to Watch 2016 report, Tony Baer forecasts that data lake management will become a front-burner issue as early Hadoop adopters get to the point of production implementation.
    During this fireside chat, Tony Baer and Scott Gidley, VP of Product Management at Zaloni assess the state of the industry regarding governance and data management tools, technologies, and practices that should fall into place as part of a data lake strategy.
  • Fireside Chat with 451 Research: The reality of an end-to-end data lake Recorded: Feb 26 2016 60 mins
    Matt Aslett, Big Data Research Director, 451 Research & Ben Sharma, CEO and co-founder, Zaloni
    The reality of building effective, scalable, big data enterprise solutions can be daunting. There are so many elements to consider, and no pre-written playbook to follow. But there are more best practices being recognized every day, and value realized by those organizations that are moving boldly ahead.
    During this fireside chat, Matt Aslett, Big Data Research Director of 451 Research and Ben Sharma, thought leader and CEO of Zaloni, engaged in a lively discussion exploring topics including:
    - The data lake as a core element of the modern big data architecture
    - Big data trends including ground-to-cloud deployments, logical data lakes, and virtualization
    - Changes in analytics that the data lake has enabled, including self-service data preparation and data marketplaces
    - The move from reporting to predictive analytics to prescriptive analytics
  • Targeted Health Informatics with Managed Data Lakes Recorded: Feb 9 2016 54 mins
    John Poonnen - Managing Principal, Nexor, Health and Life Science Informatics & Kelly Schupp - Vice President of Marketing
    Coordinating data across all points of contact – clinical, claims and pharmacy – is critical to providing coordinated care. Outcome-based reimbursement, population health management and personalized medicine all rely on accurate and actionable data intelligence. Healthcare organizations need to have a Big Data solution in place that provides actionable intelligence to those who need it, when they need it. During this webinar, we will talk about how foundational platforms, such as Bedrock, make an actionable data lake a reality for healthcare organizations.
  • Governance of the Big Data Lake with a focus on RDARR for Financial Services Recorded: Dec 1 2015 48 mins
    Sunil Soares, Founder and Managing Partner of Information Asset & Ben Sharma, CEO and Founder of Zaloni
    Discover Data Lake Governance Best Practices with experts Sunil Soares and Ben Sharma. During this webcast they will discuss a few key areas relating to Governance of the Big Data Lake with a specific focus on RDARR:

    - Identifying Critical Data Elements for RDARR
    - Establishing Data Standards for Critical Data Elements
    - Supporting data lineage for Big Data to support regulatory compliance
    - Managing Data Quality
    - Hardening Information Security

    We will explore multiple use cases and explore how organizations in the financial services industry are building Hadoop Data Lakes that deliver the necessary components for risk data aggregation and risk reporting.

    About Sunil Soares, Founder and Managing Partner, Information Asset

    Sunil Soares is the Founder and Managing Partner of Information Asset, a consulting firm focused on data governance and enterprise data management. Sunil used to be the Director of Information Governance at IBM. He is the author of several books including The IBM Data Governance Unified Process, Selling Information Governance to the Business, Big Data Governance, Data Governance Tools and The Chief Data Officer Handbook for Data Governance.

    About Ben Sharma, CEO & Co-Founder, Zaloni

    Ben Sharma, is CEO and co-founder of Zaloni. He is a passionate technologist with experience in business development, solutions architecture, and service delivery of big data, analytics and enterprise infrastructure solutions. Having previously worked in management positions for NetApp, Fujitsu and others, Ben's expertise ranges from business development to production deployment in a wide array of technologies including Hadoop, HBase, databases, virtualization and storage. Ben is an author and holds two patents. He received his MS in Computer Science from the University of Texas at Dallas.
The Data Lake Company
Zaloni, the data lake company, is an award-winning provider of enterprise data lake management solutions. Our software, Bedrock and Mica, enables customers to gain their own competitive advantage through organized, actionable big data lakes. Serving the Fortune 500, Zaloni has helped its customers build production implementations at many of the world’s leading companies.

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  • Title: Managing Big Data in the Bedrock Data Lake Management Platform
  • Live at: Jan 18 2017 6:00 pm
  • Presented by: Adam Diaz, Director of Field Engineering
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