Meeting the Big Data Challenge: Get Close, Get Connected

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1 CITO Research Advancing the craft of technology leadership Meeting the Big Data Challenge: Get Close, Get Connected Sponsored by

2 Contents Executive Summary 1 Introduction 1 The Untold Story of Big Data 2 Use Cases for Big Data Analytics Your Network Matters 3 Use Case 1: Moving the Data to the Best Architecture 3 Use Case 2: Collecting Data Across the Internet 4 Use Case 3: Bursting Into the Public Cloud When Data Gets Too Big 5 Use Case 4: Time-Sensitive Big Data Applications 6 Conclusion 7

3 Executive Summary In boardrooms around the world, C-suite executives are clamoring to join the big data party. And for good reason: the value that can be derived from analyzing big data is well known. Cost savings, productivity gains and compelling customer insights are but a few of the benefits of big data in the enterprise. There is a hidden challenge to analyzing big data, one that is often ignored: the fluid movement of data from one place to another. In order to collect, store and analyze big data, it has move, and it has to move fast. The value of using big data cannot be overstated When it comes to the movement of big data, there is an important component that can make or break success: the network. This CITO Research white paper explains the big data network challenge and offers solutions to overcome it so that you can derive value faster. Introduction Big data is changing everything. What is big data? It s data so big that your current infrastructure and tools can t handle it. Excel breaks down. Databases break down. Data warehouses can t handle the volume. That s big data. It s no secret that companies around the world are doing big data deep dives to find out more about their customers and to drive sales. Facebook is now matching its advertising partners loyalty card data with individual Facebook profiles using addresses and phone numbers. Considering that there are close to 900 million monthly active users on the social network, that s a lot of data to crunch. The value of learning how to use big data for competitive advantage cannot be overstated. Companies that leverage big data to better understand and target their customers and transform their business processes have or will quickly outpace those who don t. If you are in the process of determining how you plan to use big data in your company, this is an important paper to read. This paper provides information about some practical aspects of working with big data that you probably haven t considered. 1

4 The Untold Story of Big Data CITO Research has found an important big data story that is not being reported. If you think of an overall architectural solution for computing as a three-legged stool, what you find is that two of the three legs are solid. The first leg, hardware, has advanced over the last 10 years. So has the second leg, software, with software as a service, apps, and big data toolsets such as Hadoop and Amazon RedShift crunching data at scale. There s one area where advances are conspicuously absent and that is the network. We are more reliant on networks than ever, and variations in network performance across the Internet are extreme and our three-legged stool is lopsided as a result. To illustrate, Figure 1 shows the variability in moving a mere 12 TB of data from one cloud provider to another, hardly big data. It took one provider 4 hours and another a full 7 days. Estimated Minimum Hours to Transfer 12 TB To be successful with big data, barriers within infrastructure must be overcome Number of Hours Cloud Transmission Scenarios 1 2 Figure 1: Wild Variations in Moving Data from Cloud to Cloud (Data source: Nasuni, Bulk Data Migration in the Cloud, 2012) 2

5 If you want to gain competitive advantage in using big data, you need to consider where big data is coming from, where it will go, and how you plan to analyze it. To be successful with big data, barriers within the infrastructure must be overcome to achieve high throughput and lower latency. Big data analytics projects have different network requirements, which vary based on use case. Use Cases for Big Data Analytics Your Network Matters There are many use cases for big data analytics; this paper addresses four of them: 1. Moving big data to the most effective architecture to process it 2. Collecting big data from multiple sources (i.e., social networks) across the Internet for analysis 3. Using the cloud s elastic capability when data is too big for your infrastructure, requiring you to move the data to the public cloud 4. Offering a big data application that depends on (or is differentiated by) speed Use Case 1: Moving the Data to the Best Architecture The choice of provider can mean the difference between seeing results in a day or in two weeks Big data comes with a build or buy decision, and the cloud makes this choice more interesting (and potentially mind boggling) than ever. Should we set up a Hadoop cluster or rent one? Whether you re working with a company such as GoodData, which offers a complete analytics infrastructure in the cloud, or moving your data into Amazon RedShift s online data warehouse to do your crunching there, or taking advantage of any number of other leading-edge services, there s one common denominator. You have to move big data. The speed with which you can move your data and get analytical results becomes a clear differentiator. Choosing a provider with highspeed direct connections to your service means that each time you move data, it s going as fast as possible. This can mean the difference between seeing results in a day or in two weeks. 3

6 What s a direct connection? A direct connection bypasses the Internet entirely. Instead of having your data routed across the Internet (with the variation and unpredictability of that besteffort routing), a direct connection is a shortcut from one well-connected provider to another. It s up to 80% faster than sending data over the Internet. Use Case 2: Collecting Data Across the Internet Information can flow in different ways, but if your big data use case depends on collecting data from multiple sources in a time-sensitive fashion, having fast connections to those sources makes a big difference. Let s say you re pulling data from your own point-of-sale systems, from Facebook, Foursquare, and Twitter. Whether you re monitoring your brand or offering targeted promotions to customers via mobile, there s a great deal of value in being able to pull data from all these sources. To collect that much data and then crunch it in time to matter, you need to be able to access it fast. As another example, say Coca-Cola decided to advertise to people who have bought Pepsi in the last month. In order to do that, data from hundreds, possibly thousands, of retailers would have to be quickly collected so the ad opportunity isn t lost. Choosing a provider that has direct connections to the vast majority of these data sources means that you can collect big data fast. Once you have the data, whether you re gauging reaction to your new product initiative or a new marketing campaign or making real-time offers to customers, you can analyze it and use it effectively. For these applications, stale data is next to worthless. Your offers need to keep pace with what s happening. Direct connections to data sources is differentiating and gives you a competitive edge. 4

7 Use Case 3: Bursting Into the Public Cloud When Data Gets Too Big Stale data is worthless; offers need to keep pace with what s happening Some companies have huge batch jobs for big data. When you are looking at billions of transactions, it s impossible to crunch those kinds of numbers in a traditional infrastructure. Doing the monthly or quarterly reports on numbers like those requires additional infrastructure. This is when it s time to burst into the Amazon public cloud. Having a direct connect into the public cloud provides elasticity to handle large jobs as needed. This use case can occur at the beginning of a company s exploration with big data, where the public cloud is an attractive option, as well as later in the lifecycle, when a company has used the public cloud intensively enough and needs a more cost effective private cloud infrastructure. Periodically you need to go beyond the capabilities of your private infrastructure. When this happens, bursting into the public cloud securely and easily makes good sense (this is referred to as a hybrid cloud). Private Analyze Big Data with Hybrid Cloud Hybrid Public Amazon Public Cloud Your Company Manage your regulatory constraints Use hybrid cloud to connect private and public Retain access during demand spikes Figure 2: Using a Hybrid Cloud Solution to Increase Big Data Efficiency Selecting a provider that offers a direct connection into the Amazon public cloud enables cost effective scaling whenever it becomes necessary. This strategy also works for companies that need to handle usage spikes. Public cloud elasticity provides support to scale under heavy loads. 5

8 Use Case 4: Time-Sensitive Big Data Applications The fourth and most latency-sensitive use case involves an application that depends on bringing in big data, crunching it, and fueling an application s response with the results. Performance depends on having a provider with fast global points of presence One of the most difficult cases is advertising exchanges. According to Forrester Research, successful real-time bidding (RTB) for advertising requires companies to receive, analyze, and bid on individual ad impressions within 100 milliseconds. The faster bidding happens, the higher the likelihood of completed transactions and larger transaction volumes create more revenue for all participants. Looking to boost the execution speed of its video ads, which would give digital video advertising buyers precious additional milliseconds of decision-making time to improve audience targeting and increase ROI for their ad buys, BrightRoll needed high-speed connectivity. By choosing a provider that offers direct connections, BrightRoll increased performance by 80% compared with going over the Internet and boosted transaction volume by 10%. There s another key aspect of this use case. Applications have users all over the world. Performance depends on having a provider with fast global points of presence. Direct connections bypass the Internet where needed; global data centers provide fast access into the largest regional providers. For example, content sharing platform Box turned to a well-connected provider to add capacity to Box Accelerator, its global data transfer network. These upgraded connections augmented the speed of the Box service for enterprise users by 60 percent. Similarly, gamification and behavior management platform Badgeville leveraged direct connections to improve latency between its database and the public cloud. Partially as a result, overall response time from the Badgeville application APIs improved 15 percent, so customers experience overall better performance. Badgeville has cut approximately 40 percent of its monthly operational costs for cloud services. 6

9 Conclusion The Internet is a network of networks. From the beginning of the Internet, there have been carrier-neutral interconnection points where all the major providers positioned their data centers. This has never been more important than today, when applications depend on using, moving, and pivoting in response to crunching big data. What is less well-known is that you can enjoy the same benefits as these major players. By choosing to partner with Equinix, you tap into this network of networks; upwards of 80% of all connections over the Internet traverse Equinix data centers. By locating your big data where all the major players are, Platform Equinix offers: Direct connections to the public cloud Interconnects to all the major social networks High speed global access Connections to market-leading and up and coming big data partners That last point deserves special attention. The face of big data is constantly changing as new products and services come on the market. What you use for big data today and what you ll use a year from now are unlikely to be the same. By positioning yourself at Equinix, you can take advantages of the latest technology for big data with minimal business impact. The latest technology is just a cross-connect away. About Equinix Equinix, Inc. One Lagoon Drive 4th Floor Redwood City, CA Main: Fax: This paper was created by CITO Research and sponsored by Equinix. Whether you re building a big data cluster or seeking help to do so, Equinix is strategically positioned to help you move faster than the competition and make the most of your big data initiative. CITO Research CITO Research is a source of news, analysis, research, and knowledge for CIOs, CTOs, and other IT and business professionals. CITO Research engages in a dialogue with its audience to capture technology trends that are harvested, analyzed, and communicated in a sophisticated way to help practitioners solve difficult business problems. Visit us at 7

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