Featured Gartner predicts exponential growth of graph technology

Published on October 6th, 2021 📆 | 8370 Views ⚑

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Gartner predicts exponential growth of graph technology

As the size and complexity of data continues to escalate, organizations will increasingly turn to graph technology as a means of harnessing their data to drive decision-making.

During the keynote address on Oct. 5 of Graph + AI Summit Fall 2021, a hybrid in-person and virtual conference hosted by graph database vendor TigerGraph, Gartner analyst Rita Sallam said the research and advisory firm forecasts that 80% of data and analytics innovations will be made using graph technology by 2025.

Currently in 2021, just 10% of data and analytics innovations are made with graph technology.

At the core of graph technology are relationships between data points.

Multiple data points

Data points stored in graph databases are able to connect with multiple other data points at any given time while those stored in traditional relational databases are able to connect with only one other data point at any time. That ability to connect to multiple other data points, meanwhile, enables deeper, faster and more accurate data exploration.

In addition, as the amount of data being created and collected increases exponentially, traditional tools are getting overwhelmed and their performance is no longer meeting the needs of many organizations, according to Sallam.

Graph technology, however, is able to handle the increasing demands of organizations.

“As the size and the complexity and the distributed nature of data needed to contextualize complex decisions accelerates, rigid architectures and tools are breaking down,” Sallam said. “Agility and resilience are key, and the complexity is pushing the limits of current approaches, but [complexity] is also leading to unprecedented cycles of rapid innovation in data and analytics.”

She added that the way to respond to the breakdown of rigid architectures and tools is to adopt graph technology — and maximize its effectiveness by combining it with augmented intelligence and the cloud.

“We believe there will be rapid adoption,” Sallam said.

Graph in the real world

To illustrate the capabilities of graph technology, Sallam discussed several seemingly unrelated real-world examples of organizations using graph to solve problems.

First, she spoke about the importance and unpredictability of supply chain management during the COVID-19 pandemic. The balance between supply and demand of certain products has been in constant flux over the past 18 months, and manufacturers have had to react quickly in order to avoid too much or too little of a given product in a given region at a given time.

Next, Sallam noted that municipalities have had to deliver food to elderly citizens unable to leave their homes during the pandemic. Cities have had to determine the best routes to optimize delivery speed and transportation resources.

Finally, she mentioned tracking the impact of climate change on penguins to determine intervention strategies. Environmentalists need to know the movement of individual penguins, migratory and mating patterns, and how it all relates to weather patterns and changes in their ecosystem.

“They all are exploiting very complex and varied data combinations, including video, text, audio and transactions as well as the micro-behavior of employees, customers and, in one case, penguins,” Sallam said. “All need to make connections quickly across these new and complex combinations of data to solve an urgent problem. And all, in fact, are innovating using graph technology and AI.”

The need to quickly make connections between data points and make data-driven decisions, meanwhile, has never been more important than it has been over the past 18 months.

Graph technology and the pandemic

The COVID-19 pandemic obliterated what was considered normal before March 2020. Organizations of all kinds needed to react quickly.

Healthcare organizations needed to prepare for and deal with surges in COVID-19 infections. Governments needed to take measures such as issuing stay-at-home mandates and then manage the re-opening of local economies. And enterprises had to find ways to survive amid potentially sharp drops in revenue.

Among businesses, many of those that have managed to survive are still dealing with the effects of the pandemic. Some industries have normalized to a degree and certain organizations have thrived, but as cases continue to ebb and flow and new variants of the coronavirus emerge, others such as hospitality and travel continue to deal with significant declines in demand from pre-pandemic levels.

While only a small percentage of organizations used graph technology at the start of the pandemic, and those now using graph technology to inform the decision-making process remain a small minority, the speed-to-insight enabled by graph technology will lead to a significant increase in graph adoption, according to Sallam.

Graph surging for innovation and decisions

In fact, beyond the 70% increase in data and analytics innovations fueled by graph technology Gartner predicts will take place by 2025, Sallam added that Gartner predicts that by 2023 graph technology will play a role in the decision-making process for 30% of organizations worldwide.

“Data, analytics and AI have never been more critical,” she said. “While taking ever-more factors, stakeholders and data sources into account, decisions are just more complex, and we have to [take those into account] faster than ever before. What’s required to succeed in the face of this unimaginable set of markets shifts is the ability to leverage increasing velocity and scale of analysis.”

Already, organizations are using graph technology in a variety of ways, according to Sallam.

Beyond fostering a better understanding of customers and helping uncover fraud, it’s now being used in such varied industries as agriculture to optimize crop yield, law enforcement and the Department of Homeland Security to track suspects, and healthcare to track and mitigate COVID-19.

“Most of the business questions we have and decisions we need to make require an understanding of the relationships between objects — people, places, behaviors — and graphs help highlight those important relationships,” Sallam said. “Graph plus data and analytics and AI in the cloud are making innovative use cases possible at scale.”

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