Welcome!

Apache Authors: Pat Romanski, Liz McMillan, Elizabeth White, Christopher Harrold, Janakiram MSV

Related Topics: Apache, Java IoT, Microservices Expo, Microsoft Cloud, Containers Expo Blog, Agile Computing, @CloudExpo

Apache: Article

Data Centers: Where Big Data Will Be Exploited

First things first: powering Big Data

On any given day, it's not uncommon for a company to generate 2.5 quintillion bytes of data, pushing the amount of data that must be processed and managed to unimaginable levels. Because of the requirements for power and low-latency connections that such data growth entails, many companies have become more inclined to outsource their Big Data needs to colocation data center facilities. In turn, this has created a huge demand for colocation space as additional processing grounds for Big Data. According to analyst firm Nemertes, colocation providers will not have the available space to capitalize on approximately $869 million of market demand by 2015. This is with good reason, though, as colocation data centers offer huge benefits for Big Data, including high-density power, opportunities to decrease latency and a community of like-minded companies with which to cross-connect.

First Things First: Powering Big Data
A lot has been made of Big Data analytics and the tools most capable of cataloging and valuing Big Data. However, before analyzing data, companies must first ensure that they are able to meet the power demands of such in-depth data analysis. With growing levels of data that must be processed, compute speeds must similarly increase to keep up. As a result, a higher level of power is required. Traditionally, power demands for data computation have been well below 1 kilo Volt Ampere (kVA) per square meter; with the rise of Big Data, however, this is now pushing power levels greater than 15 kVA per square meter. Without the ability to meet these power demands, it doesn't quite matter which analytics tool a company uses, as they won't have the resources to make it effective.

Colocation data centers are invaluable in this regard, as they typically purchase bundles of power, giving them the ability to offer power to customers at a much lower cost than customers would be charged in a private data center. In addition, data center facilities are required to provide backup power supplies, so that if they were to incur a power outage or electric shortage, there would still be enough power on reserve to negate any impact on Big Data value or performance for companies hosted in the facility. Finally, colocation data centers charge only for the power used by each customer, so companies can extract significant energy savings rather than miscalculating power usage and consistently overpaying for such an expensive resource.

Slow and Steady Doesn't Always Win the Race
Beyond the immense power requirements, Big Data requires faster compute speeds than the historic norm. This is not easily achieved, but without it, companies may face significant latency for Big Data. This likely won't make a difference in some industries, such as scientific research, where quality is prioritized over speed, but for many other industries, including online and mobile advertising, even a few seconds of latency has the potential to prohibit good service or remove value from Big Data.

For example, a mobile advertising company that targets consumers based on their location will need to process GPS data, consumer demographics and preferences, and advertising platform data - all within the time it takes for a consumer to walk by a store front. Clearly, time is of the essence when the window of opportunity for a sale is just a few seconds long.

The time between the GPS data noting that a customer is approaching a storefront to the end result of an advertisement popping up on his phone will inevitably have a lag - something I like to call the "virtual hop." Simply put, the virtual hop is the time that is required to mine and manipulate data to create an end result. This is a widely known concept when it comes to website impressions, which require a virtual hop of less than two seconds. Currently, a virtual hop for the mobile advertising scenario described above is much longer than this, though it is expected to develop into a much quicker process, similar to the evolution of website response times. Rather than wait, though, companies are looking for solutions to implement today to reduce their virtual hop time - and are finding their concerns answered in colocation data center facilities.

Connect With the Server Next Door
Colocating infrastructure in a data center has the potential to remove a layer of latency and reduce virtual hop times dramatically by providing a common ground for companies that often work together to collaborate and exchange information. The ability to directly connect to the servers of two different companies housed within the same data center, a concept known as cross-connecting, has huge potential to expedite compute times and eliminate a significant portion of latency.

Cross connecting has already been used in many colocation facilities to provide near instantaneous collaboration results between data center tenants. Common examples of this include a speedy deployment to a cloud environment or seamless content aggregation across digital media platforms.

The communities of like-minded companies that are often developed within data centers offer an ideal environment for decreased latency and improved Big Data analysis. Communities typically cater to specific verticals, including cloud, financial services and digital media. For example, going back to the mobile advertising example, a cross-connect between the mobile provider's database of customer demographics and the advertiser's data would greatly improve this process, as the two servers would be able to work congruently and seamlessly from within the same digital media facility.

Despite their enormous benefits to customers, these communities are not yet a common feature across colocation facilities. A recent study from Infineta Systems found that data center-to-data center connectivity, as opposed to cross connecting, is a "silent killer" for Big Data deployments, as many data centers do not prioritize the development of communities within their facilities. Therefore, this is a distinguishing feature that companies must seek when profiling data centers to house their Big Data.

Back to Basics
Without the high-density power required to process data, or the ability to improve Big Data analysis through connectivity and cross-connections, companies are essentially collecting data for fun.

More Stories By Ian McVey

As Director of Marketing and Business Development for the enterprise and systems integrator segment, Ian McVey is responsible for developing and driving Interxion’s go-to-market proposition for the enterprise and systems integrator segments, including all aspects of sales and marketing. He has over 15 years of industry experience in a variety of strategy, sales and marketing roles at Microsoft, Cable & Wireless and LEK Consulting. Before joining Interxion in 2011 he was Director of Sales and Business Development for the Microsoft Practice at CSC. He holds an MBA from London Business School and a Masters in Engineering from the University of Oxford.

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.


IoT & Smart Cities Stories
Dion Hinchcliffe is an internationally recognized digital expert, bestselling book author, frequent keynote speaker, analyst, futurist, and transformation expert based in Washington, DC. He is currently Chief Strategy Officer at the industry-leading digital strategy and online community solutions firm, 7Summits.
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
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 the strategy and defining the Big Data service offerings and capabilities for EMC Global Services Big Data Practice. As the CTO for the Big Data Practice, 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, is an avid blogge...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Business professionals no longer wonder if they'll migrate to the cloud; it's now a matter of when. The cloud environment has proved to be a major force in transitioning to an agile business model that enables quick decisions and fast implementation that solidify customer relationships. And when the cloud is combined with the power of cognitive computing, it drives innovation and transformation that achieves astounding competitive advantage.
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
In his keynote at 19th Cloud Expo, Sheng Liang, co-founder and CEO of Rancher Labs, discussed the technological advances and new business opportunities created by the rapid adoption of containers. With the success of Amazon Web Services (AWS) and various open source technologies used to build private clouds, cloud computing has become an essential component of IT strategy. However, users continue to face challenges in implementing clouds, as older technologies evolve and newer ones like Docker c...
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...