Real-Time Data Analytics: On Demand vs. Continuous

Jen Cohen Crompton

Real-Time Data Analytics touches almost every part of a business – from the data managers and enterprise architects, to marketing and sales managers – they all need to collect, use, and analyze data to shape their roles and strategies. Now, more than ever, businesses are focused on the immediate implications of data and monitoring it often to stay abreast of what is happening. We are in the Digital Age, which is fast-moving and requires a sense of immediacy.

In general, real-time analytics can be defined as the use of, or the capacity to use, available enterprise data and resources when needed. It consists of dynamic analysis and reporting, based on data entered into a system less than 60 seconds ago. In other words, this is viewing and using data as wanted, needed, and requested.

There are two specific and useful types of real-time data analysis – On-Demand and Continuous, which are differentiated by the reactive and proactive approaches – or pull and push.

On-Demand Real-Time Analytics is reactive because it waits for users to request a query and then delivers the analytics. This is used when someone within a company needs to take a pulse on what is happening right this minute. This data might be pulled during a marketing campaign to find out what is happening from a sales perspective, or from a web analyst who wants to monitor site traffic to avoid a potential crash.

Continuous Real-Time Analytics is more proactive and alerts users with continuous updates in real-time. Think of this as analytics running in the background and being pushed through on a predetermined basis. This type of data can provide a changing visualization of action on a website – maybe a line graph of site activity so analysts can monitor changing patterns. Continuous Real-Time Analytics can be considered business intelligence in action.

Both On-Demand and Continue Real-Time Analytics have their time and place within a business strategy and each can be used to help build effective strategies.

So here’s just a little more on why and type of Real-Time Analytics matter…
Real-Time Analytics can be fed through dashboards to update team members in real-time on what is going on within or outside of the business – factors that can have an instant effect. An example is how we view the stock market. We watch the stock market in real-time to see what is happening and we often view it through a continuously updated visual representation on a wesbite, TV or mobile device. We use the data to drive our actions – trades, investments, etc. All of those actions are deeply dependent upon time and understanding what is happening right this very minute.

Another important result is monitoring customer behaviors. When focusing on CRM, real-time analytics provide data about customer behavior at this very moment, which can foster quicker decision making and immediate changes or potentially “fixes” when necessary. This, in turn, can strengthen customer relationships and increase the value of engagements.


About Jen Cohen Crompton

Jen Cohen Crompton is a SAP Blogging Correspondent reporting on big data, cloud computing, enterprise mobility, analytics, sports and tech, and anything else innovation-related. When she's not blogging, she can be caught marketing, using social media and/or presenting at conferences around the world. Disclosure: Jen is being compensated by SAP to produce a series of articles on the innovation topics covered on this site. The opinions reflected here are her own.