Analytics trends include a surge in app development
As more organizations have recognized the value of data during the pandemic, a surge in application development is among the top business intelligence trends.
Application development has surged during the pandemic and become one of the primary analytics trends, according to T.K. Anand, senior vice president of analytics at Oracle.
In addition, the move to the cloud and augmented analytics are key trends that have been accelerated by the pandemic, he said recently during the initial episode of Oracle Analytics Summit, a virtual series hosted by the tech giant.
When the pandemic struck in March 2020 and governments issued stay-at-home mandates that in effect shuttered local economies, many organizations turned to data and analytics as ways of better understanding their businesses and the overall economic climate, and figuring out ways to survive.
That meant the rapid development of new applications to enable agile data-driven decision-making, according to Anand. And that rapid development, meanwhile, was fostered by low-code and no-code development tools designed to save application developers significant time and even enable some business users to build their own applications.
Oracle Apex is a low-code application development tool the vendor's clients often use, while other vendors including Domo, Looker and Yellowfin also offer no-code and low-code tools that enable application development.
"One of the things that happened during the pandemic is organizations needed to react very quickly," Anand said. "They had to quickly build and deploy applications that track the health and whereabouts of their employees. Hospitals had to deploy their resources quickly based on rapidly changing public health situation. And all of this has required rapid application development."
The need for agile data-driven decision-making also meant more use of prebuilt programs, which are industry- or use-specific applications built by vendors that can be purchased and deployed immediately, Anand continued.
"Packaged analytics is another trend that started to grow even before the pandemic, but we've seen it accelerate through the pandemic," he said.
In particular, prebuilt applications have been beneficial for SaaS users who struggle to get value from the data stored in their SaaS applications, according to Anand.
T.K. AnandSenior vice president of analytics, Oracle
Before the pandemic, Oracle developed the Fusion Analytics Warehouse to assist SaaS application customers, including an ERP analytics system introduced in 2019 and a health care management analytics system unveiled in 2020. And as more customers request prebuilt applications, Oracle has more in the development pipeline, according to Anand.
SAS and Sisense, meanwhile, are other vendors that provide prebuilt applications.
"Both [ERP and health care management] have been growing very quickly through the pandemic as customers are choosing to go with packaged solutions as opposed to building something in-house," Anand said. "We're still in the early stages of this transformation -- we're just getting started."
Meanwhile, Anand noted that cloud adoption remains a major analytics trend.
The cloud offers speed and compute power that on-premises analytics systems lack, and that speed has been critical during the pandemic.
"A pattern that existed before the pandemic but has really accelerated has been the transition from on-premises systems to the cloud," Anand said. "Over the past 18 months, we've seen the pandemic cause some dramatic shifts in how organizations think and operate, and they're leveraging Oracle Analytics and the Oracle Cloud in ways we haven't seen before."
Among those ways, he continued, are to enable collaboration while working remotely and to undertake short-term cost-tracking projects to better oversee their spending amid uncertain economic conditions and make quick decisions related to rapid changes.
Similarly, the increased use of augmented analytics has been a trend throughout the pandemic as organizations understand the importance of reacting quickly to recent changes and anticipating coming changes, according to Anand.
"During the early days of the pandemic, especially, organizations had to understand the implications on their own business, on their sales forecast, their supply chain, their inventory, and they had to react," he said. "Augmented tools … really helped the business analysts and citizen data scientists to analyze and explore the relevant data."
In particular, he continued, augmented analytics tools enabled them to build predictive models.
Oracle customers have used the predictive modeling and machine learning capabilities of Oracle Analytics Cloud, while Alteryx and Tibco are among the other analytics vendors with popular predictive modeling tools.
"The models inform the business leaders in terms of the agile decision-making they've had to do to deal with the [pandemic]," Anand said.
As do the capabilities enabled by cloud migration and the increased development and implementation of analytics applications.