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Gartner looks at 2019’s data and analytics technology trends

When it comes to business and creating competitive advantages, data and analytics thereof hold many of the keys. So much so that research firm Gartner routinely looks at the top technology trends that will drive the data and analytics industry each year, and 2019 is no different.

In particular the firm has identified 10 trends in this space that businesses and IT decision makers should be cognisant of for the coming year.

“The story of data and analytics keeps evolving, from supporting internal decision making to continuous intelligence, information products and appointing chief data officers,” says Rita Sallam, research vice president at Gartner.

“It’s critical to gain a deeper understanding of the technology trends fuelling that evolving story and prioritise them based on business value,” she adds.

New possibilities

Diving deeper into the technology trends, Gartner notes that the vast amounts of data that has been generated over the past decade, and will continue to created, also presents a significant opportunity for many businesses. This is driven by the fact that cloud-enabled processing capabilities, coupled with the potential of AI to learn and compute, to glean more insight than ever before.

“The size, complexity, distributed nature of data, speed of action and the continuous intelligence required by digital business means that rigid and centralised architectures and tools break down,” says David Feinberg, VP and distinguished research analyst at Gartner.

“The continued survival of any business will depend upon an agile, data-centric architecture that responds to the constant rate of change,” he continues.

So what are the 10 technology trends that Gartner has identified?

The first is referred to by Gartner as Augmented Analytics, and is described as the next wave of disruption for the industry. It utilises machine learning to transform the way analytics content is developed, shared and consumed.

In fact by 2020 Gartner predicts that it will be the key driver for business intelligence for the data and analytics industry.

Next is Augmented Data Management, and it touches on metadata in particular.

This as metadata is shifting from a passive to an active state in the view of Gartner, and as such will prove a significant input when it comes to artificial intelligence and machine learning.

The firm then followed that trend up by mentioning Continuous Intelligence, which is anticipated to be adopted by half of businesses by 2022, according to Gartner.

For those unfamiliar with the term, it’s a design pattern in which real-time analytics are integrated within a business operation, and allows for processing current and historical data to list actions in response to events. As such it will be a boon when it comes to critical decision making.

The fourth trend is Explainable AI, which refers to how an AI model comes to the decision that it does. This is particularly important as AI is often used to augment or replace human decision making, and therefore requires a higher level of trust to be in place in order to justify high level actions being taken by a business.

Number five is Graph Analytics. Graph analytics is a set of analytic techniques that allows for the exploration of relationships between entities of interest such as organisations, people and transactions.

Gartner says the application of graph processing and graph database management systems will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.

The sixth technology trend identified for 2019 is Data Fabric, and in particular how it enables the sharing of data within a distributed data environment.

Through 2022, bespoke data fabric designs will be deployed primarily as a static infrastructure, forcing organisations into a new wave of cost to completely re-design for more dynamic data mesh approaches, says Gartner.

Up next is Natural Language Processing. This as the research firm predicts that 50 percent of analytical queries will be garnered by search, voice or automatically generated.

Added to this will be the need to analyse complex combinations of data and make it accessible to everyone in an organisation.

The eighth trend is Commercial AI and ML. Gartner predicts that by 2022, 75 percent of new end-user solutions leveraging AI and ML techniques will be built with commercial solutions rather than open source platforms, hence its rise to prominence this year.

The penultimate trend is one that has been touched on in previous years – Blockchain.

According to Gartner it will be several years before four or five major blockchain technologies become dominant. Until that happens, technology end users will be forced to integrate with the blockchain technologies and standards dictated by their dominant customers or networks.

The final trend is Persistent Memory Servers. New persistent-memory technologies will help reduce costs and complexity of adopting in-memory computing (IMC)-enabled architectures, notes Gartner.

The research firm says this persistent memory represents a new memory tier between DRAM and NAND flash memory, which can provide cost-effective mass memory for high-performance workloads. Adding that it has the potential to improve application performance, availability, boot times, clustering methods and security practices, while keeping costs under control.

[Image – CC 0 Pixabay]

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