Not being ‘genuinely’ real time could mean missing out on some of the action

The future of business lies in real-time and businesses that are able to close the time gap between customer demands and fulfilment can expect to flourish. Real-time tools are changing business forever and set to become ever more important in an increasingly complex-data-intensive world. IDC estimates that by 2020, business transactions on the Internet will reach £310 billion per day.

Today, real-time is becoming ‘genuinely’ real-time but within the context of its environment. It used to be that when a customer or prospect asked you for real-time, what they really wanted was something faster than their apps and systems were performing at the time - so maybe this meant on the same day (instead of overnight) or maybe within an hour (instead of hours later).  In a sale’s situation you may want to know about an abandoned shopping cart within minutes to understand the reasons why it never completed - real-time should therefore be as fast as it needs to be and appropriate to the contextual environment.

A real-time data processing system has to be able handle data of any type and from any source, in other words: Big Data.  Different data sources need to be aggregated in real-time for analysis to feed action systems instantly making demands of data ingestion, data storage and data query.

Rapid ingestion of data is crucial for any streaming pipeline to be as efficient as possible and the problem with many of today’s analytics solutions is that they rely on batch processing to provide what are purported to be real-time reports for business intelligence.

Poor data storage also holds us back.  A data lake is increasingly one of the most common approaches for storing large amounts of data in one place; a vast reservoir of all your data that can be accessed equally by everyone in the business, without any need to specially prepare it.  There should be no limits to what can be collected and stored and you should be able to inspect and ask questions of your historical data using any set of measures, date ranges and event details at any time.

The final piece of the jigsaw is an ability to ask and query data across any timeframe without the need for predefined measures or time buckets.  Ideally, if you could preserve each data point to enable unlimited segmentation and inspection so any event detail is never lost in processing or reporting.  When analysis happens on the fly we don’t need to know the questions in advance.

Real-time, all of the time, requires a new way of collecting, storing and interrogating data to enable marketers to both monitor campaigns and make ‘live’ adjustments to meet demand.  Ultimately real-time is relative in context to the user.  While blistering speeds are bewitching don’t fall foul of that ‘need for speed’.  Yes, there’s an allure to instantaneous information but the reality is that real-time data is only ever beneficial if you can actually do something with it, regardless of whether it took milliseconds or minutes to arrive.

Not being ‘genuinely’ real-time could mean missing out on some of the action but having ‘appropriate’ real-time is likely to win you more of the business and for much less.