Proximity Colocation: A Data Management Strategy Enabling Data analytics

South Bend, IND. (August 28, 2014) − As data becomes more of an asset in the eyes of business owners, the "IT" team leaders are moving from the back room to the boardroom. Conversations about how to best manage valuable data are happening and people are looking to their CTO's, CIO's, and similar positions to lead the way in all things data. While some mid-sized businesses may not think they are ready for data analytics today, most admit they are planning to leverage data assets in the next three to five years. So what does this mean for today's strategy building? What can be done now to prepare for the future?

Look to the Market

Don't worry; we are not the first to ask these questions. By looking at past trends in data management we can all see where the future is going. The idea of "proximity colocation" stems from the financial trading sector, where clusters of businesses needed to locate their virtual services near the data. Think about the incentives for a high-frequency trading firm to colocate its services in the same data center where the digital exchange order book services are being housed. The location proximate to each other ensures Local Area Network (LAN) speed connectivity, resulting in the lowest competitive latency.

After the financial sector, media groups came online in a big way, requiring proximity colocation to reliably deliver large video content to subscribers. Think about the incentives for a large-content media group to locate its services in the same data center as its digital content. Just like the financial trading sector, the media delivery sector benefits from LAN speed connectivity, resulting in "happy Netflix subscribers."

The trend of proximity colocation is growing increasingly important with the emergence of data analytics, offering similar and distinct benefits for businesses. Organizations that strategically position and care for their data now, will be ideally situated to realize the promise and return from big data analytics in the future. Just like there are financial, content, music, and other digital marketplaces, data marketplaces are beginning to come online, with major opportunities specifically for mid-sized businesses.

Locate Where the Data Lives

The promise of data analytics is the freedom to ask and answer the "big questions," like: "What is the prime location for my next branch?" or "Who are my best customers and how do I get more?" Often, the answers to these questions require data from outside of one company's "four walls." Data available through Data Enrichment Services can be combined with business' own internal data. "The best answers are derived when additional, external data sources enrich a business' proprietary data," says Rich Carlton, President & COO of Data Realty; "The new, enriched data set can then be used to generate insights that have a deeper impact on business decisions."

Use proprietary data to achieve a competitive advantage. Two things that mid-sized businesses have that the enterprise players do not are: your data (it's unique, historical, transactional, and proprietary); and your professional relationships. "We believe virtual relationships should mirror the physical. If suppliers and providers have had long fruitful relationships, interconnecting key data points will also bear fruit," says Carlton, "People often associate data with a cold relationship, when the truth is, the purpose of the data is to better understand and meet the needs of your customer, patient, subscriber, etc. … and strengthen the personal relationships."

Imagine one manufacturer and one dealer who begin sharing mutually valuable insights resulting from data analytics. When the businesses interconnect data to better understand the environment around "time-to-dealer," they are both able to lower their individual inventory costs through more accurate forecasting and bulk pricing agreements. In addition, because the two businesses chose to integrate their individually-managed component / product numbering systems, they are able to proactively address warranty issues, resulting in fewer filed claims from consumers. And remember, these are a few examples from just two businesses; imagine the possibilities and benefits available to an entire supply chain if they were to interconnect select data with each other. Data Interconnection Services are a "two-way street;" both parties retain their proprietary information, while sharing agreed upon data points or algorithmic results in order to better answer questions that drive their individual businesses.

Colocating data proximate to where data enrichment and interconnection services are being offered is critical to leveraging data analytics. Because data does not exist on a single point in a network, LAN speed connectivity is crucial to access the different cloud environments where the data exists. A single algorithm may have to pull from three or more points on the network to provide the most informed insights. Even the best algorithms will only provide average results with average data. Locate where the data lives.

Data Hubs: The Key for Successful Business Analytics

A Data Hub is an infrastructure consisting of hardware and software that is optimized for data analytics. Businesses often have data on many different servers and have structured it in many ways, resulting in a lack of communication between the disparate systems and limited actionable insights for businesses. For instance, CRM systems, accounting packages, spreadsheets, and outsourced systems all tell a story about a business. Unfortunately, many businesses can only access this information in fragments. "Our solution uses Hadoop and all the benefits that come with it, with none of the hassle at a fraction of the price that it would cost businesses to build it themselves. The Hadoop Data Hub is offered as-a-service to clients, because we are the data experts," says Tom Panozzo, Chief Technology Officer of Data Realty; "We focus on managing your data, while our clients focus on their business." Once a business' data is organized on a Hadoop Data Hub, they are free to ask question knowing that "answers" will take into account data across all departments.

It is critical to colocate near data hub services, because traditional servers and legacy systems are not capable of executing algorithmic processing in an efficient manner. If your business is planning data analytics initiatives, know that it is much more reliable to connect a Hadoop Data Hub to a LAN connection with colocated servers. "Colocating in an analytics-ready data center allows businesses to transfer extremely large datasets at LAN speed, as opposed to using light bandwidth Internet connections," says Panozzo; "Essentially, if your data is here it's more quickly transformed into analytics-ready data."

What Is Next?

As businesses mature in this new world of big data and business driven analytics, real-time market data and access to historical databases will become more and more important. Today, the ideal locations for financial trading are sold out or cost prohibitive for mid-sized businesses. Just like the ‘early bird' gets the proverbial worm, the first-movers into business analytics will get the best locations. Businesses are primarily located or colocated offsite in some way, shape or form. This is something that businesses are doing already. So, why not consider strategically locating in a place that will enable your company to take full advantage of historical and predictive analytics? And remember, just because you decide to wait does not mean the competition will.

About Data Realty

Data Realty's world-class data centers are designed to enable analytic computation on data sets housed within their secure environment. Through the Hadoop Data Hub and partnership business model, Data Realty delivers mid-sized organizations unprecedented access to the advanced computing infrastructure, collaborative intellectual environment, and highly skilled technical talent that is normally reserved for large competitors. For more information and to connect, tweet and follow the team, visit Data Realty online at