Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Dell EMC’s Big Data Practice. As a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He’s written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organization’s key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill also just completed a research paper on “Determining The Economic Value of Data”. Onalytica recently ranked Bill as #4 Big Data Influencer worldwide.
Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored the Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements. Bill serves on the City of San Jose’s Technology Innovation Board, and on the faculties of The Data Warehouse Institute and Strata.
Previously, Bill was vice president of Analytics at Yahoo where he was responsible for the development of Yahoo’s Advertiser and Website analytics products, including the delivery of “actionable insights” through a holistic user experience. Before that, Bill oversaw the Analytic Applications business unit at Business Objects, including the development, marketing and sales of their industry-defining analytic applications.
Bill holds a Masters Business Administration from University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.
Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) are at the heart of digital transformation by enabling organizations to exploit their growing wealth of big data to optimize key business and operational use cases.
• AI is the theory and development of computer systems able to perform tasks normally requiring human intelligence (e.g. visual perception, speech recognition, translation between languages, etc.).
• ML is a sub-field of AI that provides systems the ability to learn and improve by itself from experience without being explicitly programmed.
• DL is a type of ML built on a deep hierarchy of layers, with each layer solving different pieces of a complex problem. These layers are interconnected into a “neural network.” A DL framework is SW that accelerates the development and deployment of these models.
Director, Data Analytics Portfolio Messaging and Strategy at Dell EMC
Jean Marie Martini is a Director of messaging and strategy across the data analytics portfolio at Dell EMC. Martini has been involved in data analytics for over ten years. Today the focus is on communicating the value of the Dell EMC solutions to enable customers to begin and advance their data analytics journeys to transform their organizations into data-driven businesses. You can follow Martini on Twitter @martinij.
Originally posted on CIO.com by Patricia Florissi, Ph.D.
What is a World Wide Herd (WWH)?
What does it mean to have “Distributed analytics meet distributed data?” In short, it means having a group of industry experts, in this case a group given the title of World Wide Herd, to form a global virtual computing cluster. The WWH concept creates a global network of distributed Apache™ Hadoop® instances to form a single virtual computing cluster that brings analytics capabilities to the data. In a recent CIO.com blog, Patricia Florissi, Ph.D., vice president and global CTO for sales and a distinguished engineer for Dell EMC, details how this approach enables analysis of geographically dispersed data, without requiring the data to be moved to a single location before analysis. (more…)
Brett is the Technical Lead for Dell EMC’s Data Analytics Technology Alliances, focused on developing solutions that help customers solve their data challenges. You can find him on social media at @Broberts2261
Operational Intelligence and machine generated data have been very hot topics lately as organizations are beginning to realize how valuable this data is for the business. For the last few years, Splunk has been the leader in this space with their all-encompassing platform that enables the ability to collect, search and analyze machine generated data. (Not up to speed on this yet? Check out my other blog on getting started with machine generated data) Dell EMC and Splunk have had a tremendous partnership over the past couple years that is based on the premise that we offer market leading infrastructure that is optimal for Splunk’s world class analytics platform for machine generated data. A couple weeks ago, we took this one step further… I’m excited to announce the release of the Solution Guide for Machine Analytics with Splunk Enterprise on VxRack Flex 1000! With this, Dell EMC now has a validated rack scale, hyper-converged infrastructure solution for Splunk that has been jointly validated by Splunk & Dell EMC.
Why is this important?
Having this solution that has been jointly validated by both Splunk and Dell EMC to “meet or exceed Splunk’s performance benchmarks” gives users a higher degree of confidence in the environment. With this solution the performance needed to run Splunk effectively and gain the valuable insights to make critical IT and business decisions will be there. Our solutions engineering team along with Splunk put hundreds of engineering hours into designing specific configurations based on a variety of different deployment scenarios and rigorously tested them to ensure performance. The solutions guide gives you not only those configurations but also implementation guidelines and deployment practices. All of this equals lower risk, quicker time to value and validated for performance…can’t ask for anything better.
How is VxRack Optimal for Splunk?
VxRack provides flexible, rack scale, hyper-converged infrastructure that allows you to use the hypervisor of your choice or bare metal as well as the ability to start small but scale-out to thousands of nodes. With VxRack you are given the flexibility to optimize your tiering for Splunk by putting Hot and Warm buckets in SSD while using HHD or even Isilon scale-out NAS for your cold bucket needs (Solution guide shows how to use Isilon for cold tiering). You also get to enjoy the benefits of Software Defined Storage and data services that are essential in today’s data center. The best part is that VxRack gives a turnkey experience that is engineered and designed to be ready to run, giving you a quicker time to insight and value. Additionally, with single support and life-cycle management for your infrastructure you lower complexity and reduce risk and costs. All of this equals great performance, economical tiering structure & easy to deploy and manage infrastructure that is validated to run Splunk.
Erin K. Banks has been in the IT industry for almost 20 years. She is the Portfolio Marketing Director for Big Data and Data Analytics at Dell EMC. Previously she worked at Juniper Networks in Technical Marketing for the Security Business Unit. She has also worked at VMware and EMC as an SE in the Federal Division, focused on Virtualization and Security. She holds both CISSP and CISA accreditations. Erin has a BS in Electrical Engineering and is an author, blogger, and avid runner. You can find her on social media at @banksek
I spoke with Eliot Van Buskirk ( @listeningpost ), Data Storyteller at Spotify, as part of my Big Data Conversations series for Dell EMC. Note that this is not a product or technology blog and certainly there are no endorsements implied from either side but, in all fairness, I am a paying Spotify user and I am in love with what they do to bring music to the masses.
Erin K. Banks: How do you utilize big data at Spotify? (more…)
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