Welcome!

WebRTC Summit Authors: Pat Romanski, Liz McMillan, Elizabeth White, Roger Strukhoff, Yeshim Deniz

Related Topics: @CloudExpo, Artificial Intelligence, @DXWorldExpo, @ThingsExpo

@CloudExpo: Blog Feed Post

“Unlearn” to Unleash Your #DataLake | @CloudExpo @Schmarzo #BigData #AI #DX

The Data Science Process is about exploring, experimenting, and testing new data sources and analytic tools quickly

It takes years – sometimes a lifetime – to perfect certain skills in life: hitting a jump shot off the dribble, nailing that double high C on the trumpet, parallel parking a Ford Expedition. Malcolm Gladwell wrote a book, “Outliers,” discussing the amount of work – 10,000 hours – required to perfect a skill (while the exactness of 10,000 hours has come under debate, it is still a useful point that people need to invest considerable time and effort to master a skill). But once we get comfortable with something that we feel that we have mastered, we become reluctant to change. We are reluctant to unlearn what we’ve taken so long to master.

Changing your point of release on a jump shot or your embouchure for playing lead trumpet is dang hard! Why? Because it is harder to unlearn that it is to learn. It is harder to un-wire all those synoptic nerve endings and deep memories than it was to wire them in the first place. It’s not just a case of thinking faster, smaller or cheaper; it necessitates thinking differently.

For example, why did it take professional basketball so long to understand the game changing potential of the 3-point shot? The 3-point shot was added to the NBA during the 1979-1980 season, but for decades the 3-point shot was more a novelty then a serious game strategy. Pat Riley, the legendary coach of the 3-pointer’s first decade in the league (won NBA Championships in 1982, 1985, 1987 and 1988), called it a “gimmick.” Larry Bird, one of that era’s top players said: “I really don’t like it.”

It’s only been within the past 3 years where the “economics of the 3-point shot” have changed the fundamentals of how to win an NBA Championship (see Figure 1).

Figure 1: NBA 3-point Baskets per Season

NBA Coaches and General Managers just didn’t comprehend the “economics of the 3-point shot” and how the 3-point shot could turn a good shooter into a dominant player; that a 40% 3-point shooting percentage is equivalent to a 60% 2-point shooting percentage from a points / productivity perspective. The economics of the 3-point shot (coupled with rapid ball movement to create uncontested 3-point shots) wasn’t full exploited until the 2015-2016 season by the Golden State Warriors. Their success over the past 3 seasons (3 trips to the NBA finals with 2 championships) shows how much the game of basketball has been changed.

Sometimes it’s necessary to unlearn long held beliefs (i.e. 2-point shooting in a predominately isolation offense game) in order to learn new, more powerful, game changing beliefs (i.e., 3-point shooting in a rapid ball movement offense).

Sticking with our NBA example, Phil Jackson is considered one of the greatest NBA coaches, with 11 NBA World Championships coaching the Chicago Bulls and the Los Angeles Lakers. Phil Jackson mastered the “Triangle Offense” that played to the strengths of the then dominant players Michael Jordan (Chicago Bulls) and Kobe Bryant (Los Angeles Lakers) to win those 11 titles.

However, the game passed Phil Jackson as the economics of the 3-point shot changed how to win. Jackson’s tried-and-true “Triangle Offense” failed with the New York Knicks leading to the team’s dramatic under-performance and ultimately his firing. It serves as a stark reminder of how important it is to be ready to unlearn old skills in order to move forward.

And what holds true for sports, holds even more so for technology and business.

The Challenge of Unlearning
For the first two decades of my career, I worked to perfect the art of data warehousing. I was fortunate to be at Metaphor Computers in the 1980’s where we refined the art of dimensional modeling and star schemas. I had many years working to perfect my star schema and dimensional modeling skills with data warehouse luminaries like Ralph Kimball, Margy Ross, Warren Thornthwaite, and Bob Becker. It became engrained in every customer conversation; I’d built a star schema and the conformed dimensions in my head as the client explained their data analysis requirements.

Then Yahoo happened to me and soon everything that I held as absolute truth was turned upside down. I was thrown into a brave new world of analytics based upon petabytes of semi-structured and unstructured data, hundreds of millions of customers with 70 to 80 dimensions and hundreds of metrics, and the need to make campaign decisions in fractions of a second. There was no way that my batch “slice and dice” business intelligence and highly structured data warehouse approach was going to work in this brave new world of real-time, predictive and prescriptive analytics.

I struggled to unlearn engrained data warehousing concepts in order to embrace this new real-time, predictive and prescriptive world. And this is one of the biggest challenge facing IT leaders today – how to unlearn what they’ve held as gospel and embrace what is new and different. And nowhere do I see that challenge more evident then when I’m discussing Data Science and the Data Lake.

Embracing The “Art of Failure” and The Data Science Process
Nowadays, Chief Information Officers (CIOs) are being asked to lead the digital transformation from a batch world that uses data and analytics to monitor the business to a real-time world that exploits internal and external, structured and unstructured data, to predict what is likely to happen and prescribe recommendations. To power this transition, CIO’s must embrace a new approach for deriving customer, product, and operational insights – the Data Science Process (see Figure 2).

Figure 2:  Data Science Engagement Process

The Data Science Process is about exploring, experimenting, and testing new data sources and analytic tools quickly, failing fast but learning faster. The Data Science process requires business leaders to get comfortable with “good enough” and failing enough times before one becomes comfortable with the analytic results. Predictions are not a perfect world with 100% accuracy. As Yogi Berra famously stated:

“It’s tough to make predictions, especially about the future.”

This highly iterative, fail-fast-but-learn-faster process is the heart of digital transformation – to uncover new customer, product, and operational insights that can optimize key business and operational processes, mitigate regulatory and compliance risks, uncover new revenue streams and create a more compelling, more prescriptive customer engagement. And the platform that is enabling digital transformation is the Data Lake.

The Power of the Data Lake
The data lake exploits the economics of big data; coupling commodity, low-cost servers and storage with open source tools and technologies, is 50x to 100x cheaper to store, manage and analyze data then using traditional, proprietary data warehousing technologies. However, it’s not just cost that makes the data lake a more compelling platform than the data warehouse. The data lake also provides a new way to power the business, based upon new data and analytics capabilities, agility, speed, and flexibility (see Table 1).

Data Warehouse Data Lake
Data structured in heavily-engineered structured dimensional schemas Data structured as-is (structured, semi-structured, and unstructured formats)
Heavily-engineered, pre-processed data ingestion Rapid as-is data ingestion
Generates retrospective reports from historical, operational data sources Generates predictions and prescriptions from a wide variety of internal and external data sources
100% accurate results of past events and performance “Good enough” predictions of future events and performance
Schema-on-load to support the historical reporting on what the business did Schema-on-query to support the rapid data exploration and hypothesis testing
Extremely difficult to ingest and explore new data sources (measured in weeks or months) Easy and fast to ingest and explore new data sources (measured in hours or days)
Monolithic design and implementation (water fall) Natively parallel scale out design and implementation (scrum)
Expensive and proprietary Cheap and open source
Widespread data proliferation (data warehouses and data marts) Single managed source of organizational data
Rigid; hard to change Agile; relatively ease to change

Table 1:  Data Warehouse versus Data Lake

The data lake supports the unique requirements of the data science team to:

  • Rapidly explore and vet new structured and unstructured data sources
  • Experiment with new analytics algorithms and techniques
  • Quantify cause and effect
  • Measure goodness of fit

The data science team needs to be able perform this cycle in hours or days, not weeks or months. The data warehouse cannot support these data science requirements. The data warehouse cannot rapidly exploration the internal and external structured and unstructured data sources. The data warehouse cannot leverage the growing field of deep learning/machine learning/artificial intelligence tools to quantify cause-and-effect. Thinking that the data lake is “cold storage for our data warehouse” – as one data warehouse expert told me – misses the bigger opportunity. That’s yesterday’s “triangle offense” thinking. The world has changed, and just like how the game of basketball is being changed by the “economics of the 3-point shot,” business models are being changed by the “economics of big data.”

But a data lake is more than just a technology stack. To truly exploit the economic potential of the organization’s data, the data lake must come with data management services covering data accuracy, quality, security, completeness and governance. See “Data Lake Plumbers: Operationalizing the Data Lake” for more details (see Figure 3).

Figure 3:  Components of a Data Lake

If the data lake is only going to be used another data repository, then go ahead and toss your data into your unmanageable gaggle of data warehouses and data marts.

BUT if you are looking to exploit the unique characteristics of data and analytics –assets that never deplete, never wear out and can be used across an infinite number of use cases at zero marginal cost – then the data lake is your “collaborative value creation” platform. The data lake becomes that platform that supports the capture, refinement, protection and re-use of your data and analytic assets across the organization.

But one must be ready to unlearn what they held as the gospel truth with respect to data and analytics; to be ready to throw away what they have mastered to embrace new concepts, technologies, and approaches. It’s challenging, but the economics of big data are too compelling to ignore. In the end, the transition will be enlightening and rewarding. I know, because I have made that journey.

The post “Unlearn” to Unleash Your Data Lake appeared first on InFocus Blog | Dell EMC Services.

Read the original blog entry...

More Stories By William Schmarzo

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business”, is responsible for setting the strategy and defining the Big Data service line offerings and capabilities for the EMC Global Services organization. As part of Bill’s CTO charter, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He’s written several white papers, avid blogger and is a frequent speaker on the use of Big Data and advanced analytics to power organization’s key business initiatives. He also teaches the “Big Data MBA” at the University of San Francisco School of Management.

Bill has nearly three decades of experience in data warehousing, BI and analytics. Bill authored EMC’s Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements, and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute’s faculty as the head of the analytic applications curriculum.

Previously, Bill was the Vice President of Advertiser Analytics at Yahoo and the Vice President of Analytic Applications at Business Objects.

@WebRTCSummit Stories
It is of utmost importance for the future success of WebRTC to ensure that interoperability is operational between web browsers and any WebRTC-compliant client. To be guaranteed as operational and effective, interoperability must be tested extensively by establishing WebRTC data and media connections between different web browsers running on different devices and operating systems. In his session at WebRTC Summit at @ThingsExpo, Dr. Alex Gouaillard, CEO and Founder of CoSMo Software, presented a comprehensive view of the numerous testing challenges researchers have faced before arriving at the first release candidate of the WebRTC specifications.
SYS-CON Events announced today that CrowdReviews.com has been named “Media Sponsor” of SYS-CON's 22nd International Cloud Expo, which will take place on June 5–7, 2018, at the Javits Center in New York City, NY. CrowdReviews.com is a transparent online platform for determining which products and services are the best based on the opinion of the crowd. The crowd consists of Internet users that have experienced products and services first-hand and have an interest in letting other potential buyers learn their thoughts on their experience.
WebRTC is great technology to build your own communication tools. It will be even more exciting experience it with advanced devices, such as a 360 Camera, 360 microphone, and a depth sensor camera. In his session at @ThingsExpo, Masashi Ganeko, a manager at INFOCOM Corporation, introduced two experimental projects from his team and what they learned from them. "Shotoku Tamago" uses the robot audition software HARK to track speakers in 360 video of a remote party. "Virtual Teleport" uses a multiple Intel RealSense Depth Camera to scan 3D and build 3D models in real-time, and display as hologram in front of remote participants.
SYS-CON Events announced today that Telecom Reseller has been named “Media Sponsor” of SYS-CON's 22nd International Cloud Expo, which will take place on June 5-7, 2018, at the Javits Center in New York, NY. Telecom Reseller reports on Unified Communications, UCaaS, BPaaS for enterprise and SMBs. They report extensively on both customer premises based solutions such as IP-PBX as well as cloud based and hosted platforms.
SYS-CON Events announced today that Evatronix will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Evatronix SA offers comprehensive solutions in the design and implementation of electronic systems, in CAD / CAM deployment, and also is a designer and manufacturer of advanced 3D scanners for professional applications.
SYS-CON Events announced today that Synametrics Technologies will exhibit at SYS-CON's 22nd International Cloud Expo®, which will take place on June 5-7, 2018, at the Javits Center in New York, NY. Synametrics Technologies is a privately held company based in Plainsboro, New Jersey that has been providing solutions for the developer community since 1997. Based on the success of its initial product offerings such as WinSQL, Xeams, SynaMan and Syncrify, Synametrics continues to create and hone innovative products that help customers get more from their computer applications, databases and infrastructure. To date, over one million users around the world have chosen Synametrics solutions to help power their accelerated business and personal computing needs.
SYS-CON Events announced today that Google Cloud has been named “Keynote Sponsor” of SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Companies come to Google Cloud to transform their businesses. Google Cloud’s comprehensive portfolio – from infrastructure to apps to devices – helps enterprises innovate faster, scale smarter, stay secure, and do more with data than ever before.
Recently, WebRTC has a lot of eyes from market. The use cases of WebRTC are expanding - video chat, online education, online health care etc. Not only for human-to-human communication, but also IoT use cases such as machine to human use cases can be seen recently. One of the typical use-case is remote camera monitoring. With WebRTC, people can have interoperability and flexibility for deploying monitoring service. However, the benefit of WebRTC for IoT is not only its convenience and interoperability. It has lots of potential to address current issues around IoT - security, connectivity and so on - based on P2P technology. It will become a key-component especially in edge computing use cases, in his view.
Cloud Expo | DXWorld Expo have announced the conference tracks for Cloud Expo 2018. Cloud Expo will be held June 5-7, 2018, at the Javits Center in New York City, and November 6-8, 2018, at the Santa Clara Convention Center, Santa Clara, CA. Digital Transformation (DX) is a major focus with the introduction of DX Expo within the program. Successful transformation requires a laser focus on being data-driven and on using all the tools available that enable transformation if they plan to survive over the long term. A total of 88% of Fortune 500 companies from a generation ago are now out of business. Only 12% still survive. Similar percentages are found throughout enterprises of all sizes.
The 22nd International Cloud Expo | 1st DXWorld Expo has announced that its Call for Papers is open. Cloud Expo | DXWorld Expo, to be held June 5-7, 2018, at the Javits Center in New York, NY, brings together Cloud Computing, Digital Transformation, Big Data, Internet of Things, DevOps, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal today!
22nd International Cloud Expo, taking place June 5-7, 2018, at the Javits Center in New York City, NY, and co-located with the 1st DXWorld Expo will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Meanwhile, 94% of enterprises are using some form of XaaS – software, platform, and infrastructure as a service.
22nd International Cloud Expo, taking place June 5-7, 2018, at the Javits Center in New York City, NY, and co-located with the 1st DXWorld Expo will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Meanwhile, 94% of enterprises are using some form of XaaS – software, platform, and infrastructure as a service.
DevOps at Cloud Expo – being held June 5-7, 2018, at the Javits Center in New York, NY – announces that its Call for Papers is open. Born out of proven success in agile development, cloud computing, and process automation, DevOps is a macro trend you cannot afford to miss. From showcase success stories from early adopters and web-scale businesses, DevOps is expanding to organizations of all sizes, including the world's largest enterprises – and delivering real results. Among the proven benefits, DevOps is correlated with 20% faster time-to-market, 22% improvement in quality, and 18% reduction in dev and ops costs, according to research firm Vanson-Bourne. It is changing the way IT works, how businesses interact with customers, and how organizations are buying, building, and delivering software.
@DevOpsSummit at Cloud Expo, taking place June 5-7, 2018, at the Javits Center in New York City, NY, is co-located with 22nd Cloud Expo | 1st DXWorld Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long development cycles that produce software that is obsolete at launch. DevOps may be disruptive, but it is essential.
SYS-CON Events announced today that T-Mobile exhibited at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. As America's Un-carrier, T-Mobile US, Inc., is redefining the way consumers and businesses buy wireless services through leading product and service innovation. The Company's advanced nationwide 4G LTE network delivers outstanding wireless experiences to 67.4 million customers who are unwilling to compromise on quality and value. Based in Bellevue, Washington, T-Mobile US provides services through its subsidiaries and operates its flagship brands, T-Mobile and MetroPCS. For more information, visit https://www.t-mobile.com.
SYS-CON Events announced today that Cedexis will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Cedexis is the leader in data-driven enterprise global traffic management. Whether optimizing traffic through datacenters, clouds, CDNs, or any combination, Cedexis solutions drive quality and cost-effectiveness. For more information, please visit https://www.cedexis.com.
SYS-CON Events announced today that Vivint to exhibit at SYS-CON's 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California. As a leading smart home technology provider, Vivint offers home security, energy management, home automation, local cloud storage, and high-speed Internet solutions to more than one million customers throughout the United States and Canada. The end result is a smart home solution that saves you time and money and ultimately simplifies your life.
SYS-CON Events announced today that Opsani will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Opsani is the leading provider of deployment automation systems for running and scaling traditional enterprise applications on container infrastructure.
SYS-CON Events announced today that Nirmata will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Nirmata provides a comprehensive platform, for deploying, operating, and optimizing containerized applications across clouds, powered by Kubernetes. Nirmata empowers enterprise DevOps teams by fully automating the complex operations and management of application containers and its underlying resources. Nirmata not only simplifies deployment and management of Kubernetes clusters but also facilitates delivery and operations of applications by continuously monitoring the application and infrastructure for changes, and auto-tuning the application based on pre-defined policies. Using Nirmata, enterprises can accelerate their journey towards becoming cloud-native.
SYS-CON Events announced today that Opsani to exhibit at SYS-CON's 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California. Opsani is creating the next generation of automated continuous deployment tools designed specifically for containers. How is continuous deployment different from continuous integration and continuous delivery? CI/CD tools provide build and test. Continuous Deployment is the means by which qualified changes in software code or architecture are automatically deployed to production as soon as they are ready. Adding continuous deployment to your toolchain is the final step to providing push button deployment for your developers.