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AtScale

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  • Harnessing the Power of BI on the Google Cloud
    Harnessing the Power of BI on the Google Cloud Lucio Daza, Director Technical Product Marketing at AtScale Recorded: Jun 7 2018 35 mins
    If you're trying to deliver performant, scalable business intelligence on big data and the capability to handle large number of queries is a key issue for you, Google BigQuery is a choice well-worth considering. It is no surprise that more and more data workloads are moving to the cloud. The question is, how can you be successful at it?

    Join this session to learn:
    - How to support BI on the cloud regardless of the data size.
    - How to analyze all your data without breaking the bank.
    - What are the key factors for a successful BI on the cloud implementation.
  • Revolutionizing The Cloud with AtScale and Amazon RedShift
    Revolutionizing The Cloud with AtScale and Amazon RedShift Denis Dubeau, Director Product Management, Platforms Recorded: Jun 7 2018 30 mins
    Data engineers, data analysts, developers and pretty much anyone involved in the data stewarding process is looking to migrate their data to the cloud, mainly to increase performance and lower costs.

    Join this session to learn:
    - How to reduce query cost
    - Key factors to succeed with BI on the cloud.
    - How to get more from your existing data cluster.
  • Accelerate Business Analytics with AtScale 6.5
    Accelerate Business Analytics with AtScale 6.5 Daren Drummond: Dir-Product, Wendy Gradek: Dir-Product; Lucio Daza, Dir Tech Marketing Recorded: Apr 11 2018 57 mins
    The new AtScale 6.5 product release offers significant new features to sharpen analytics insight, improve end-user productivity, and strengthen data governance in democratized analytics environments. In AtScale 6.5, users may:

    *Calculate quantiles on all of your data without requiring data movement or losing analysis accuracy.

    *Re-use existing dimensions within a cube without creating extra dimensions

    *Govern access to cube objects to manage complexity

    With AtScale 6.5, BI leaders and enterprise data architects alike will see a new way to gain access to and report on all your organization’s data.

    Join Josh Klahr, VP-Product at AtScale and Lucio Daza, Director Technical Marketing at AtScale for this deep dive into AtScale 6.5 and learn how to:

    *Optimize business analytics by supporting consistent models across data platforms and BI tools

    *Run sophisticated multi-dimensional analytics on all your enterprise data using the tools your business users know well

    *Secure data access governed by policy without needing to replicate data no matter the BI tool desired for use

    The webinar will run live at Wednesday, April 11, 11:00 AM Pacific Time.
  • The Definitive Big Data Maturity Survey - 2018 Edition
    The Definitive Big Data Maturity Survey - 2018 Edition John Mertic, Director, ODPi (a Linux Foundation project); Bruno Aziza, Chief Marketing Officer, AtScale Recorded: Mar 27 2018 58 mins
    Big data is here to stay, and enterprises are determined to transform their data into strategic assets to inform operations and planning. Yet despite years of focus, investment, and effort, CDOs haven't reached a transformational level of maturity in data and analytics. What's holding us back?

    Leveraging data from multiple years of results spanning over 5,500 survey responses from 429 companies, the Definitive Big Data Maturity Survey provides the industry's only comprehensive look at where big data and analytics are heading. Join this webinar as AtScale explains the six trends driving enterprise transformation in big data. The webinar will cover:

    *The future of the cloud in big data
    *BI tools winners and losers
    *Strategies enterprises use to win with big data

    You won't want to miss this in-depth examination of what's driving big data today.

    Who Should Attend:
    *Strategic Data Executives
    *Data Architects
    *Business Intelligence and Analytics Leaders
  • BI on the Data Lake Checklist: Gartner BI MQ Review
    BI on the Data Lake Checklist: Gartner BI MQ Review Jen Underwood, Founder of Impact Analytix, LLC; Bruno Aziza, CMO of AtScale Recorded: Mar 8 2018 51 mins
    Join Big Data Analytics expert Jen Underwood as she dissects the 2018 Gartner BI & Analytics Platform Magic Quadrant, and shares some of the best practices data-driven organizations use to select and deploy Big Data Analytics solutions.

    In this interactive session, you’ll learn how to:

    *Better understand key analyst reports like the 2018 Gartner BI Magic Quadrant or the Forrester Wave
    *Build a Business Case for BI-on-The-Data-Lake, based on analysts' insights
    *Create a checklist to better select the software you truly need to succeed

    Finally, Jen will give each registrant access to her latest “BI-on-The-Data-Lake” deployment guide, a must-read resource for you and your team.
  • 6 Principles of Modern Data Architecture
    6 Principles of Modern Data Architecture Josh Klahr, VP of Product at AtScale; Lucio Daza, Dir Technical Marketing at AtScale Recorded: Feb 6 2018 42 mins
    Enterprises confront myriad challenges from using their big data to deliver the insights they need to improve business performance. Josh Klahr proposes six truths that have emerged in the world of new Big Data. By following these principles, enterprises may make the most of their big data and run at an optimized level. Tune in to learn:

    *Strategies that will optimize the use of your enterprise data
    *How to best serve your data consumers for performance and security
    *Ways to improve data efficiency across departments

    No matter your role - CDO, architect, or BI leader - these six themes will guide you through the world of data and decisions.
  • What is a Universal Semantic Layer?
    What is a Universal Semantic Layer? Dave Mariani, CEO / AtScale; and Lucio Daza, Director of Technical Marketing / AtScale Recorded: Jan 30 2018 31 mins
    Semantic layers in business intelligence aren’t new. This handy concept abstracts and simplifies data into common business terms to facilitate and improve reporting. But compounding semantic layers across each BI tool isn’t a simplified solution. A new approach to semantic layers is needed - the Universal Semantic Layer.

    Join this webcast to learn how the modern approach of a single semantic layer will help you reduce data management complexities and give users timely access to the data that matters, in a secure and accurate manner no matter its source.

    Business intelligence and big data veterans Matt Baird, CTO at AtScale and Lucio Daza, Director of Technical Marketing at AtScale, will illuminate the hidden benefits of a universal semantic layer. They’ll share real stories across industries and pain points to bring to life how you can use a single semantic layer today to consume big data – quickly, simply, securely, and accurately.

    Register for this session to learn:
    -How abstractions are helpful to business intelligence
    -How a single semantic layer can improve the way big data adds value to your organization
    -How easy it is to tackle the most complex big data use cases using the modern, single semantic layer approach
  • 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 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
  • 5 Ways To Scale BI on Hadoop
    5 Ways To Scale BI on Hadoop Hal Lavender, Chief Architect, Cognizant; Nino Bice, Principal Architect, Microsoft Recorded: Dec 19 2017 48 mins
    At a recent online session Josh Klahr, VP of Product Management at AtScale discussed the top challenges of scaling BI on Hadoop with Nino Bice, Principal Product Manager at Microsoft, and Hal Lavender, AVP and Chief Architect at Cognizant Technologies. Join this session as they discuss the 5 key ways to meet those challenges head-on. They'll cover how to:

    - Address the top 5 challenges of scaling BI on Hadoop
    - Overcome obstacles and bridge the BI and big data gap
    - Achieve scale, speed and success with BI on Hadoop
  • 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 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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