We have come a long way in terms of technological advancements, haven’t we? While we aren’t living in a utopia of science and technology, the many advancements that we see around us today were once considered the staple of science fiction: Automated delivery drones, smart wearables, the blockchain, driverless cars, lifelike robots, and artificial intelligence (AI). Today, they have become a stark reality and are changing the world as we know it.
None of these technologies would have been possible without the binding fabric that is data. Despite the technological advancements in the field of data analytics, data and analytics as a business practice has a long way to go. According to Impact, 63% of organizations report that the use of big data and analytics is creating a competitive advantage for their business. Based on insights from Gartner, let’s take a closer look at how the pertinent data and analytics trends shall impact your business in 2021.
Analytics has been revolutionized by AI. Given that businesses and their consumers generate a plethora of unstructured and structured data, automated manual analytics can merely scratch the surface of what’s available. AI, in layman terms, allows software, devices, and computers to learn by themselves.
According to an article by The Economic Times, agendas for digital transformation have been significantly fast tracked and speed is extremely important today. 70% of companies surveyed highlighted that re-prioritization of technology goals is likely even if the budgets themselves are not likely to change. Companies are focussing on direct to consumer via omni-channel touchpoints an digitalization so that they can connect with customers and address their needs better.
Since most businesses already have a wealth of information from various business touchpoints and market research, the challenge arises when it comes to leverage actionable insights in time. This is where AI comes in. Since it can correctly analyse, interpret, and put forth insights from varied data sets in a short span of time. It allows businesses to find solutions to key problems such as the lifetime value of a particular customer or segment of customers, pain-point of customers s, and the market appeal of a product. AI itself does not give right or wrong answers but offers a range of probabilities that companies can act upon.
Composable data and analytics
By combining components from various data, analytics, and AI technologies, composable data and analytics endeavours to build an intuitive, flexible, and usable experience that lets executives to link business actions and data insights. As per Gartner client queries, most major companies have myriad ‘enterprise standard’ business intelligence and analytics tools.
Creating new applications using each company’s packaged business skills boosts productivity and agility. Composable data and analytics will not only stimulate cooperation and expand the organization’s analytics skills, but it will also enhance access to analytics.
According to an article, initiatives that leverage composable data and analytics could lead to the discovery of new ways to package data as part of a service or product. These could be built with no-code and low-code tools through the cloud or new types of data service intermediates.
With data becoming complex and the acceleration of digital business approaches, data and analytics is increasingly becoming the core business function. Increased customer segmentation is giving rise to more competition and niches. Automation and analytics are helping companies address key customer pain points better and even offer highly customized solutions in certain instances. In terms of uncertainty, data analytics is helping organizations predict future uncertainties and changing consumer demand patterns and take action accordingly.