Overview

If the pace of the pre-coronavirus world seemed fast, then time, in an evolutionary sense, post the pandemic seems to have transgressed further. Businesses that once mapped digital strategy in one- to three-year phases must now scale their initiatives in a matter of weeks.

The coronavirus pandemic has accelerated the move to digital transformation as customers reacted swiftly to the lockdown and the shift by their staff to home working. There has been plenty of anecdotal evidence of rapid shifts across most verticals as the world has changed over the past six months. Some of these examples include banks going digital almost completely, automobile manufacturers selling cars online to more accelerated widespread penetration and adoption of e-commerce across sectors.

However, with changing market conditions and economies still in flux along with the threat of the pandemic extending for many more months, organisations and leaders must reassess their digital initiatives in order to prepare them for both the short-term as well as the post-crisis world. Key business decisions such as hitting the market faster, customising for demand and knowing the customer including expanding to other markets or segments will play a very important role in ascertaining if businesses stay afloat in the long run. And we have seen that organisations have resorted to big data and analytics to find more business intelligence to find answers to the changing market conditions. But have they been successful?

Researchers still believe that the answer to that question is a “no’. According to a report from Forrester, while 74% of businesses want to be data-driven, only 29% are good at connecting analytics to action. Another report from Gartner found that more than 60% of models are developed with the intention of operationalizing them but were never operationalized.

While algorithm-driven businesses will become the new leaders, augmenting traditional analytics with more data, faster ingestion, and analysis, new expectations, while reducing costs seems to be only option to be future-ready.

Getting more out of analytics

Analysts believe that it has taken 15 years or so for companies to harness about 50% of the productivity potential of the Internet, and the next 50% of productivity gains likely require connecting things. The Internet of Things (IoT) is causing an interconnected world where “smart” devices allow things and people to be connected from anyplace, anytime, with anything and anyone. However, the IoT data loses its value if it is not detected and acted upon immediately. That is where real- time streaming analytics can help.

Organizations in every industry have data streaming available from applications, social media, sensors, devices, websites, and more. Analysing this data in real-time, rather than storing it and analysing it later, can provide critical, actionable insights in many operational and functional areas.

Essentially, streaming analytics is all about extracting business value from data in motion in the same way traditional analytics tools make use of data at rest. Real-time streaming analytics helps companies of all sizes by issuing alerts instantly when a customer’s experience is degraded, or fraud is detected.

Additionally, information derived from real-time analytics can be used to identify anomalies and business changes (a sudden spike in demand for a product or service, or a defect in manufacturing) as they occur. Such information allows companies to take instant action and seize an opportunity that they otherwise might miss.

Use cases of real-time analytics performed on streaming data can be found in cybersecurity, financial services, retail, manufacturing, the energy industry, healthcare, and many more.

Introducing ET’s The Dataversity webinar

As businesses realise that questions around digital transformation are changing from “if” anymore; to “how fast can we can pivot?” to  “what are the costs involved?”, the Economic Times The Dataversity webinar, powered by Cloudera, is an effort to understand how enterprises and IoT applications can benefit immensely from real-time streaming analytics by visualizing the business in real-time, cutting preventable losses, detecting urgent situations and automating immediate actions.