Welcome!

Government Cloud Authors: Don MacVittie, Elizabeth White, Liz McMillan, Gopala Krishna Behara, Raju Myadam

Related Topics: @CloudExpo, Microservices Expo, Containers Expo Blog, Agile Computing, Apache

@CloudExpo: Article

The Big Data Revolution

The problem with the term Big Data is that it’s used in a lot of different ways

For many years, companies collected data from various sources that often found its way into relational databases like Oracle and MySQL. However, the rise of the Internet, Web 2.0, and recently social media began an enormous increase in the amount of data created as well as in the type of data. No longer was data relegated to types that easily fit into standard data fields. Instead, it now came in the form of photos, geographic information, chats, Twitter feeds, and emails. The age of Big Data is upon us.

Big Data Beginnings
A study by IDC titled "The Digital Universe Decade" projects a 45-fold increase in annual data by 2020. In 2010, the amount of digital information was 1.2 zettabytes (1 zettabyte equals 1 trillion gigabytes). To put that in perspective, the equivalent of 1.2 zettabytes is a full-length episode of "24" running continuously for 125 million years, according to IDC. That's a lot of data. More important, this data has to go somewhere, and IDC's report projects that by 2020, more than one-third of all digital information created annually will either live in or pass through the cloud. With all this data being created, the challenge will be how to collect, store, and analyze what it means.

Business intelligence (BI) systems have always had to deal with large data sets. Typically the strategy was to pull in "atomic" data at the lowest level of granularity, then aggregate the information to a consumable format for end users. In fact, it was preferable to have a lot of data because you could also drill-down from the aggregation layer to get at the more detailed information, as needed.

In other words, large data sets have been around a long time. And there have been many attempts at trying to manage, wrangle, and tame the onslaught of data being generated from everywhere. But it wasn't until Jeffrey Dean and Sanjay Ghemawat of Google Labs wrote their influential paper on MapReduce in 2003 that Big Data really started to take shape. Google has had to deal with large amounts of raw data (such as crawled documents and web request logs) that needed to be analyzed in a timely manner. Creating MapReduce was their way of being able to abstract the compute parallelization, distribution of data, fault tolerance, and load balancing from developers so they could focus on expressing the computations necessary to analyze the data. This seminal paper reportedly inspired Doug Cutting to develop an open-source implementation of the MapReduce framework called "Hadoop," which was named after his son's toy elephant. Yahoo famously embraced this implementation after hiring Cutting in 2004. Yahoo continued to build upon this technology and first used Hadoop in production in 2008 for its search "webmap," which was an index of all known webpages and all the metadata needed to search them.

One of the key characteristics of Hadoop was that it could run on commodity hardware and automatically distribute jobs. By its nature, it is designed to be fault tolerant so jobs aren't impacted by the failure of a single node. According to an article in Wired magazine about Yahoo's use of Hadoop, "Hadoop could ‘map' tasks across a cluster of machines, splitting them into tiny sub-tasks, before ‘reducing' the results into one master calculation." Soon after, companies like eBay and Facebook were adopting the technology and implementing it internally. Reportedly, Facebook has the largest Hadoop cluster in the world, currently at 30 petabytes (PB).

Although early adopters of Hadoop and other Big Data technologies tended to form around the Internet, social media, and ad networks, Big Data solutions are intended to be general-purpose tools. With most companies now integrating social media into their offerings, the amount of data created internally combined with those extracted externally will only increase. This is an indication that companies from all industries will need to start investigating how to implement Big Data technologies to make use of all this data they're collecting and creating.

Making Sense of Big Data
The problem with the term Big Data is that it's used in a lot of different ways. One definition is that Big Data is any data set that is too large for on-hand data management tools. According to Martin Wattenberg, a scientist at IBM, "The real yardstick ... is how it [Big Data] compares with a natural human limit, like the sum total of all the words that you'll hear in your lifetime." Essentially, what makes something Big Data is that it:

  • Is at a large scale (petabytes, not gigabytes)
  • Has high velocity (frequently polled, generated, or collected)
  • Is unstructured (not only from a relational database)

Collecting that data is a solvable problem, but making sense of it, (particularly in real time), is the challenge that technology tries to solve. This new type of technology is often listed under the title of NoSQL (or Not Only SQL) and includes distributed databases that are a departure from relational databases like Oracle and MySQL. These systems are specifically designed to be able to parallelize compute, distribute data, and create fault tolerance on a large cluster of servers. Some examples of NoSQL projects and software are Cassandra, Hadoop, Membase, MongoDB, and Riak.

The techniques vary, but there is a definite distinction between SQL relational databases and their NoSQL brethren. Most notably, NoSQL systems share the following characteristics:

  • Do not use SQL as their primary query language
  • May not require fixed table schemas
  • May not give full ACID guarantees (Atomicity, Consistency, Isolation, Durability)
  • Scale horizontally

Because of the lack of ACID, NoSQL is used when performance and real-time results are more important than consistency. For example, if a company wants to update its website in real time based on an analysis of the behaviors of a particular user interaction with the site, it will most likely turn to NoSQL technologies to solve this use case.

However, this shortcoming doesn't mean relational databases are going away. In fact, it's likely that in larger implementations, NoSQL and SQL will function together. Just as NoSQL was designed to solve a particular use case, so do relational databases solve theirs. Relational databases excel at organizing structured data and are the standard for serving up ad-hoc analytics and BI reporting. In fact, Apache Hadoop even has a separate project called Sqoop that is designed to link Hadoop with structured data stores. Most likely, those who implement NoSQL will maintain their relational databases for legacy systems and for reporting off their NoSQL clusters.

Big Data Moves to the Cloud
The early adopters of Big Data tended to be companies with capital budgets that could be invested into dedicated data centers. However, with the incredible increase in the amount of data generated, collected, and analyzed, smaller companies can take advantage of the cloud and off-load the hardware management to those vendors. Two traits that many of these NoSQL solutions have in common make them a seemingly natural fit for the cloud: One is that the nodes are distributed, and the second is that they run on commodity hardware. The cloud is designed for horizontal scaling and often built on low-cost, commodity hardware, especially at the infrastructure-as-service (IaaS) layer, where customers simply need infrastructure and have the application expertise to build and configure their own Big Data application (whether it is with Hadoop, Cassandra, or any number of products).

Not all clouds are built the same, however. One of the design elements you should look for is the ability for each virtual server in the Big Data cluster to be deployed on different nodes. Although the servers are all on the same private VLAN, ensuring that each server is on different hardware solves for two problems: (1) all the traffic and processing aren't hitting the same hardware, and (2) the cluster is protected against hardware failure because all the servers are distributed. Whether or not the architecture is assuming a name node and data node construct or a Ring design, this setup ensures performance and reliability. In addition, the option of using local storage on the virtual machine and a high-performance network will reduce latency and improve performance.

Given what most users are trying to achieve with Big Data applications-large-scale data sets, large-scale analysis, often in real time-performance is a key factor. Depending on the problem to be solved, users can also leverage a hybrid implementation that combines both virtual and dedicated servers. This setup offers maximum flexibility that balances the elastic, scalable nature of virtual machines with the single-tenancy of dedicated servers. Big Data projects don't happen in a vacuum: Although a NoSQL database can leverage dedicated servers, the app or web servers that present the results of the analysis to end users or that are used to add additional functionality like log file processing can easily be added to as many virtual machines as needed to meet demand. In addition, using the cloud means that users won't need to invest in expensive equipment, pay for power and connectivity, or hire additional resources to maintain hardware. Users simply pay for the infrastructure they need and can scale it as desired over time. The ability to scale up or down to match demand (and to pay only for the infrastructure you actually use) is one of the values of using the cloud for Big Data.

Conclusion: Succeeding with Big Data
With whatever solution you select, you should also take into account the nature of the application and where you'll want to house the processing and the output. The amount of data you collect, analyze, and present will only increase over time. The advantage will go to companies that can collect and analyze this data quickly and efficiently, allowing them to react instantly to customer sentiment and to changing trends in the ever-quickening pace of business. Make sure to select the right infrastructure vendor who can match your performance criteria and has the capacity to grow with you as your data and application needs increase to match the changing demands of your business.

More Stories By Rupert Tagnipes

Rupert Tagnipes is Senior Product Manager at GoGrid, with responsibility for managing and expanding the company's multiple product lines. His focus is on leveraging his technical background and industry knowledge to drive product innovation and increase adoption of the cloud.

He has extensive software product experience at Silicon Valley technology companies solving data analytics and cloud infrastructure problems for customers across a range of industries. Before joining GoGrid, he was a solutions architect at DASHbay, solving complex data analytics and business intelligence problems that leveraged cloud technologies for Internet companies. At Telephia / Nielsen, he was responsible for the technical development of its flagship wireless share measurement product. This product measures the market share of each carrier on a monthly basis and is an innovation in telecommunications data collection, analysis, and delivery. He earned his data chops at Informatica, developing a supply chain business analytics product that leveraged the company’s world-class ETL platform and next-generation business intelligence tools.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@ThingsExpo Stories
Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration an...
Recently, REAN Cloud built a digital concierge for a North Carolina hospital that had observed that most patient call button questions were repetitive. In addition, the paper-based process used to measure patient health metrics was laborious, not in real-time and sometimes error-prone. In their session at 21st Cloud Expo, Sean Finnerty, Executive Director, Practice Lead, Health Care & Life Science at REAN Cloud, and Dr. S.P.T. Krishnan, Principal Architect at REAN Cloud, discussed how they built...
In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, provided a fun and simple way to introduce Machine Leaning to anyone and everyone. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and B...
In his Opening Keynote at 21st Cloud Expo, John Considine, General Manager of IBM Cloud Infrastructure, led attendees through the exciting evolution of the cloud. He looked at this major disruption from the perspective of technology, business models, and what this means for enterprises of all sizes. John Considine is General Manager of Cloud Infrastructure Services at IBM. In that role he is responsible for leading IBM’s public cloud infrastructure including strategy, development, and offering m...
With tough new regulations coming to Europe on data privacy in May 2018, Calligo will explain why in reality the effect is global and transforms how you consider critical data. EU GDPR fundamentally rewrites the rules for cloud, Big Data and IoT. In his session at 21st Cloud Expo, Adam Ryan, Vice President and General Manager EMEA at Calligo, examined the regulations and provided insight on how it affects technology, challenges the established rules and will usher in new levels of diligence arou...
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 busin...
Smart cities have the potential to change our lives at so many levels for citizens: less pollution, reduced parking obstacles, better health, education and more energy savings. Real-time data streaming and the Internet of Things (IoT) possess the power to turn this vision into a reality. However, most organizations today are building their data infrastructure to focus solely on addressing immediate business needs vs. a platform capable of quickly adapting emerging technologies to address future ...
No hype cycles or predictions of a gazillion things here. IoT is here. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen. In his session at @ThingsExpo, Jay Mason, an Associate Partner of Analytics, IoT & Cybersecurity at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He also discussed the evaluation of communication standards and IoT messaging protocols, data...
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 ...
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 ...
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,...
@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...
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 ov...
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 qua...
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 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.
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 sav...
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 ...
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...