Technical

Big Data Technical Breakout Sessions and Related Events at VMworld 2017

There are many interesting technical breakout sessions and other discussions on virtualizing big data being given at the VMworld events this year. To give you a time-ordered roadmap to all of these sessions, here is the list we have built along with their times and dates of delivery. Check in at the event itself for the rooms in which these will be held We will look forward to seeing you there!

VMworld USA – Mandalay Bay – Las Vegas

Sunday, 27th August 2017

[VIRT1971QU] Virtualizing Big Data: Quick Talk:  2:00-2:30pm

This short session gives an overview of the other technical sessions that will be held in the main conference on the following days.

Monday, 28th August 2017

[SER3052BU] How VMware vSphere and NVIDIA GPUs Accelerate Your Organization: 1:00-2:00pm

Big data analytics and machine learning are shown here as two workloads that can exploit the power of GPUs in the datacenter as they emerge into popular use.

[MMC3164BU] How Data Science is Transforming Operations: Introduction to Wavefront by VMware: 2:00-3:00pm

Companies are re-thinking how they monitor and manage their systems, The data science techniques that WaveFront customers like Box, Lyft, Workday and Groupon use will be explored in this talk.

[VIRT1400BU] Real-World Customer Architecture for Big Data on VMware: 2:30-3:30pm

A VMware customer speaks about the technical details of the company’s deployment of Hadoop on vSphere

[FUT2634PU] Big Data for the 99% (of Enterprises): 3:30–4:30pm

A team from VMware’s Office of the CTO shows their work in providing a “spreadsheet for big data” that gives convenience at scale, contrasting with the infrastructures that many companies look to first

[STO3192BU] Deploying Big Data on HCI Powered by VSAN : 4:00-5:00pm

Deployment scenarios, best practices and results from various tests using VSAN as the basis for big data deployments are described in this very interesting talk.

[VIRT1351BU] New Architectures for Virtualizing Spark and Big Data Workloads : 5:30-6:30pm

This talk looks into the viability of using different file systems to the Hadoop Distributed File System (HDFS) and explores a set of alternative storage mechanisms for that data. These are becoming more common as big data matures on virtualization technology.

Tuesday, 29th August 2017

Lenovo Theater Presentation: 12:00 -12:15pm – at the Lenovo booth on Exhibitor Floor

[FUT2020BU] Wringing Maximum Performance from vSphere for Extremely Demanding Workloads and Customers: 12:30-1:30pm

In this Office of the CTO (VMware) session, the speakers will share details of work they have done in three extremely performance-critical situations. They will talk about tuning and configuring VMWare ESXi to run a very latency-sensitive financial application, for example.

[VIRT1997BU] Machine Learning and Deep Learning on VMware vSphere: GPUs are Invading the Software-Defined Data Center: 5:30 -6:30pm

As Graphical Processing Units spread further inside the data center, this talk examines their use for virtualizing workloads other than VDI, such as for big data and analytics – and shows how best to make your decisions about using the technologies together.

[VIRT2274GU] Group Discussion on Virtualizing Big Data and Machine Learning : 5:30-6:30pm

This session is a chance for you to bring up your hot topics, opinions and questions about big data and machine learning in a virtualization context.

Wednesday, 30th August 2017

[LDT2800PU] Harnessing the Power of Data in a Virtual World: 9:30 – 10:30am

A group of VMware’s own experts in processing data to get business value from it will speak about their experiences and lessons learned in doing so here.

[MTE4789VIRT] Meet the Experts Session : 11:15am-12:00pm – Table 7

This is an opportunity to meet with VMware’s big data people in a small group context. Booking your time-slot ahead of the meeting is advised here.

Thursday, 31st  August 2017

[VIRT1445BU] Extreme Performance Series: Fast Virtualized Hadoop and Spark on All-Flash Disks : 10:30-11:30am

Using vSphere 6.5 and the latest Intel hardware, VMware’s performance engineering lead on big data shows further evidence of the high performance and flexibility you can achieve by virtualizing your big data deployments. This is always a very popular talk at VMworld, so come early!

VMworld Europe – Gran Fira – Barcelona

Monday, 11th September 2017

[VIRT1971QE] Virtualizing Big Data: Quick Talk:  1:00-1:30pm

Gives an overview of other technical sessions that will be held in the main conference breakout sessions.

Tuesday, 12th September 2017

[VIRT1351BE] New Architectures for Virtualizing Spark and Big Data Workloads : 2:00-3:00pm

This talk looks into the viability of using different file systems to the Hadoop Distributed File System (HDFS) and explores a set of alternative storage mechanisms for that data. These are becoming more common as big data matures on virtualization technology.

[MMC3164BE] How Data Science is Transforming Operations: Introduction to Wavefront by VMware: 2:00-3:00pm

Companies are re-thinking how they monitor and manage their systems, The data science techniques that WaveFront customers like Box, Lyft, Workday and Groupon use will be explored in this talk.

Wednesday, 13th September 2017

[VIRT1445BE] Extreme Performance Series: Fast Virtualized Hadoop and Spark on All-Flash Disks: 5:00-6:00pm

Using vSphere 6.5 and the latest Intel hardware, VMware’s performance engineering lead on big data shows further evidence of the high performance and flexibility you can achieve by virtualizing your big data deployments. This is always a very popular talk at VMworld, so do sign up early for it!

Thursday, 14th September 2017

[FUT2020BE] Wringing Maximum Performance from vSphere for Extremely Demanding Workloads and Customers: 10:30-11:30am

In this Office of the CTO (VMware) session, the speakers will share details of work they have done in three extremely performance-critical situations. They will talk about tuning and configuring VMWare ESXi to run a very latency-sensitive financial application, for example.