Big Appetite for Big Data Spells Big Business for Channel
Our society is creating an unprecedented and massive data resource in cyberspace with each passing second. However, this growing mountain only turns into a resource when there is some means to mine or exploit it and that is where big data comes in. Big data is already a hot topic, and more and more organizations are looking at their mounting data and wondering if there might be gold in those hills.” Some of the biggest data mountains belong to media, manufacturing, and government. However, these massive databases are building up everywhere such as online retail giants like Amazon and the less obvious smaller retail operations, especially those with loyalty cards.
Currently all this data is not moving anywhere, and there is a growing appreciation that this massive burden might contain within it valuable insights, but if only there was some way to extract them.
A serious commitment to big data in most cases requires a rethink of the network architecture, and technology organizations will be looking for help and guidance towards agile, scalable and cost-effective solutions spelling big business for the channel. The first thing organizations looking to capitalize on this potential need to know is that big data is not a single problem needing to be solved, so it demands a strategy more than any one solution to overcome its challenges.
The Challenges of Big Data
The first challenge with big data is the growing demands for compliance making it mandatory for organizations to preserve records as proof they have conformed to financial, fiduciary, health, safety and other regulations. This data often must be stored infinitely and, whats more, stored at least twice to ensure backup for disaster recovery creating a huge burden.
The second difficulty in mining big data is managing this sheer volume of data not just the storage of it, but also the processing power needed to analyze it. An extreme example is the CERN Large Hadron Collider where physicists need to sift through 15 petabytes every year to see if the collisions have thrown up any significant results. Not even CERN has the computing power to do this, and so they rely on a worldwide grid of computers to crunch those numbers.
The third obstacle is speed. CERN cannot wait forever for those results, but a delay of days or weeks makes little difference in the progress of science. Compare that with a cybersecurity operation where an hour of delay could give the criminal a window of opportunity or a financial system where even one second could lose a fortune.
A fourth problem is diversity of data. A marketing exercise comparing consumer response to a range of packaging styles would need to integrate visual data with numerical response statistics, and so on. The more diverse the data, the longer it takes to design the analysis, and the more complex it will be.
These four issues volume, storage, speed and diversity work against each other. As organizations need to access their data continues to grow exponentially, addressing these challenges also means costs are growing out of hand for many customers.
Big Data Represents Big Business for the Channel
As the evolving big data trend gathers momentum, enterprise organizations seek intelligence and people with a broad understanding of the big data trends, the direction and, most importantly, a clear road map for agile, scalable networks required to implement the big data analytics. Those capable of integrating best-of-breed, open standard and future-proof solutions are likely to prosper from big data development.
There are four major demands fuelling this growth that collectively spell big business for the channel.
1) Meeting the challenges of big data
The necessity for network scalability, agility and reduced cost is currently driving a migration from legacy storage technology, such as Fibre Channel, to IP-based Ethernet and iSCSI. The now-proven capability of Ethernet to perform in the most demanding storage environments reduces investment costs by more than 60 percent in some cases, but this is only achievable thanks to the scalability (to 100 and 40Gbps) and performance delivered by best-of-breed solutions that have agility and performance, combined with open platforms and architectures to avoid interoperability issues. With this approach, enterprises achieve scale and are not locked into a proprietary and often expensive investment. Organizations serious about big data must rethink their network architecture and technology. They require guidance from outside sources, and this represents an excellent opportunity for the solution providers services capabilities. This demand means solution providers must address these vital factors for the customers:
- Scalability. The customers investments need protection longer than a three- to five-year write-off and refresh period.
- Agility. Customers must retain the power of choice with their investments and ensure their investments achieve a significant financial return.
- Cost. Total cost of ownership installation, maintenance, costs such as power, real estate, human capital and training must be assessed and minimized.
- Service Opportunities. Opportunities for such things as architecture development, technology and product selection, project management, implementation, risk assessments, outsourced employees and ongoing maintenance must be identified and exploited.
2) The need for sharing, integration and expansion of data uses
Integrating data spread across multiple information systems has historically been a challenge for many organizations. In some cases, channel partners have been reluctant to share data due to concerns over how this data would be used with a customer. Lack of visibility drives decreased information for decisions. Recent technology innovations are making it easier to aggregate and analyze data, and channel partners can more safely share their data knowing they can control it, understand the exact use of the data and help ensure they can place a monetary value on sharing that data and information.
3) Solutions providers growing the channel
Solution providers can lead the big data market, but many will have to invest in new skills. As businesses look to onboard these skills, there will be growing demand for high-speed, high bandwidth, low latency networking infrastructures that enable instant analysis of data from several different sources, allowing businesses to make real time decisions.
4) A shift toward real-time analysis
Big data mining stresses on the network will continue to surge in the areas of scope as well as speed as the demand for real time analysis increases. The channel must continue to surge to support this as well.
As the powerful implications and potential of big data become increasingly clear, overcoming its key challenges and maximizing its potential while meeting its ever increasing demands will continue to fuel powerful business growth for the channel well into the future.
Theresa Caragol is the vice president of global channel at Extreme Networks, where she continues her outstanding track record of building channel and distribution organizations throughout the industry. She has received numerous industry accolades, including being selected the last two years as one of the Top 100 Channel Executives in the IT Industry, as one of the Top 10 Next Generation Channel Leaders and one of the Top 100 Women in the Channel.
