Usually when we talk about big data, the focus is firmly on volume. Large businesses generate huge amounts of data; big data and cloud technologies are focused on empowering businesses to extract actionable insights from that data using a combination of structured and unstructured storage, on-demand processing power, and distributed access.
However, in the modern online ecosystem, velocity is equally important. There is significant advantage to be gained from gleaning historical insights from data, but the real explosion of value comes with the ability to leverage data for real time responses to the needs of particular customers.
Take the case of marketing automation. Data analysis and cloud computing power gives us the ability to construct highly personalized marketing campaigns that can exert precisely calibrated influence on potential customers. But, the opportunity to influence hinges crucially on timeliness. For example, imagine an eCommerce user is browsing a number of online stores in search of the best price for a gift item. They make a selection and add it to their cart, but immediately spot a better price elsewhere and delete the item. If the retailer can react quickly enough, they can present the user with relevant offers and promotions in an attempt to retain the sale. In this scenario, sending them an email the next day is worthless, the sale is already lost. To be effective, retailers would have to process the data and react immediately.
The same basic use-case for real time insights applies to almost all large businesses. Banks, retailers, realtors, logistics companies, manufacturing companies,the tourism industry, and many others could leverage real time data to their advantage. Or, at least they could if their information technology wasn’t geared towards batch processing of data rather than fluid real time analytics.
Consider the banking industry. Financial transactions have traditionally been batch processed. The bank’s IT infrastructure would grind through data overnight, and every morning aggregate data would be available for analysis. It’s very expensive for large enterprise companies to abandon their legacy batch processing systems entirely, but they’re missing a substantial source of revenue if they don’t find some way of making use of the data generated by their operations in realtime.
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The solution lies in the hybrid cloud. Hybrid clouds are a combination of private, in-house infrastructure and the public cloud. While it’s practically impossible to immediately abandon legacy hardware and software, it’s entirely practical to leverage the strengths of the public cloud, including its scalability, flexible APIs, and on-demand pricing structure, to implement the real time analytics that truly reactive business processes require.
Businesses can have the best of both worlds. The hybrid cloud enables them to retain legacy hardware and systems so they can maintain business continuity, while implementing the real time systems that are necessary to compete in the modern business landscape.