The benefits of turning big data into fast data

Big data is the new technology darling. There are several big data players emerging every day, each with their own unique angle on solving a specific gap, and some of the tech giants are honing their database platforms as well. The old question used to be one of scalability. How do we make big data work efficiently over terabytes of information and multiple data centers?

Big data allows companies to produce stronger, more relevant insights than ever before. But having vast quantities of data can be a double-edged sword. If queries run slower because of the database size, and if reporting takes longer because of slower queries, then big data almost becomes unusable. There still remains the problem of harnessing the power of big data, in real-time.

So what exactly are the benefits of real-time big data (“fast data”)? How do we generate actionable results in real-time, before the data gets “old” – which only takes a few seconds? To achieve this, organizations must be able to react to changes in data patterns in real-time. But what is real-time? And how does fast data translate to better business practices, stronger customer loyalty and, ultimately, reduced costs?

Fast data means customer loyalty

E-merchants say, “Sure, we do real-time campaigns, our customers can click on ads when they’re online.” However, what they fail to realize is that those real-time campaigns are running on old data, which results in losing out on significant business. What if a customer just bought a dress, and instead of showing her accessories, you’re still showing her more dresses?

If the data had been analyzed and reported in real-time, and was adapted to the customer’s dynamic clickstream, then the e-merchant would be able to serve ads for shoes, belts or other complementary products while the customer is still browsing the site. Fast big data helps e-commerce companies target their customers more effectively. Better targeting improves the customer shopping experience by allowing e-merchants to deliver personalized shopping experiences. Personalized shopping experiences create an atmosphere that is more likely to retain customer loyalty, and entice additional purchases.

As a second example, consider a customer browsing a travel website for vacation deals. If the results take even a few hundred milliseconds to load, the customer will likely leave the site to find other sources for travel deals. A travel website focusing on fast data, rather than just large quantities of big data, and delivering real-time page loads will enjoy a much better customer retention rate because customers will be more apt to stay and browse longer.

Fast big data will lead to more efficient, real-time report generation and analytics queries. Fast data allows organizations improve their response times to customers, which answers the ultimate question of improving the customer experience.

Reduce infrastructure, operating costs

Fast data can provide a telco operator OTT (Over The Top) revenues, through premium analytical services for business partners. For example, operators collect vast amounts of data at base stations. However, they currently pass it on to the central data warehouse. If operators turned this data into analytical insights faster, they could generate significant premium revenues. Analyzing data at each cell tower, or radio access controller, rather than sending it all to one data warehouse, will save operators time and generate additional incremental revenue.

In addition, many operators choose to analyze network data, such as performance and capacity. But focusing on customer data, correlated with network data, can enable imperative insights. Fast customer data also lets operators provide customer service in real-time. An operator that uses fast data to analyze customer behavior will have instantaneous information about network bandwidth spikes, downtime and dropped call information. If an operator receives and analyzes this data in real-time, it can also address these problems in real-time. Customers demand instant satisfaction; fast customer data can give operators the means to provide it.

What’s next?

Big data is beginning to become overhyped, if it is not already. The idea that having vast quantities of data is the only prerequisite for a strong data-driven infrastructure is inaccurate. Decision-makers must be able to see instantaneous reporting and query responses in order to address customer needs and infrastructure maintenance. It is clear that big data is not all that is necessary to maintain competitive advantages. Now, organizations must evolve, and to do so, they must turn their attention to fast data.