The analytics firm has released its top 10 data and analytics technology trends for 2020 that it says can help organisations prepare for a post-pandemic reset. "To innovate their way beyond COVID-19, data and analytics leaders require an ever-increasing speed and scale of analysis in terms of both processing and access to succeed," explains Rita Sallam, research vice president at Gartner. By the end of 2024, 75% of organisations will shift from piloting to operationalising artificial intelligence (AI), driving a 5x increase in streaming data and analytics infrastructures. "Within the current pandemic context, AI techniques such as machine learning (ML), optimisation and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures," Sallam. "Other smarter AI techniques such as reinforcement learning and distributed learning are creating more adaptable and flexible systems to handle complex business situations; for example, agent-based systems that model and stimulate complex systems."

Data and analytics leaders know that data and platform capabilities and the correct application of data and AI skills deliver successful AI applications. However, the majority of organizations miss the critical collaboration required across data management and AI disciplines when organizing these roles. Only 1 in 10 organizations are able to get 75% or more of their AI model prototypes into production, according to the Gartner AI in Organizations Survey. The survey also revealed that several barriers prevent organizations from successfully moving AI applications beyond prototypes. The survey revealed data dependency as a high barrier for operational AI. To mitigate this key dependency, data and analytics leaders must establish interdisciplinary practices across data management and AI.

The massive data sets, complex processing capabilities and advanced analytical models in the current digital business landscape create the perfect storm of opportunity for data and analytics. After languishing for decades, graph approaches are being embraced by analysts, data scientists and data management professionals. Graph technology is a sort of catch-all phrase that includes graph theory, graph analytics and graph data management. IT executives have a growing interest in graphs, as there is a basic understanding that graph technology is somehow different from existing solutions. Data and analytics leaders are being asked to provide guidance regarding how graph technology can be used, but many still don't have a complete understanding.

In today's tumultuous business-scape amid increasingly intricate, and often vexing, marketplace conditions, curating and mining data to drive analytics-based decision-making is no longer enough. For competing with maximum, sustained impact and mitigated opportunity loss, it's rapidly monetizing data that's now the name of the game--particularly when spurred by artificial intelligence (AI). Indeed, emerging AI methodologies are helping forward-thinking companies achieve and sustain true agility, fuel growth, and compete far more aggressively than ever before. AI is critical as a means toward those ends and also certainly with respect to aptly predicting, preparing, and responding to prospective crises as with the COVID-19 pandemic the globe is currently immersed in. In fact, Gartner recently cited the need for "smarter, faster, more responsible AI" as its No. 1 trend that data and analytics leaders should focus on--particularly those looking to "make essential investments to prepare for a post-pandemic reset."

In today's tumultuous business-scape amid increasingly intricate, and often vexing, marketplace conditions, curating and mining data to drive analytics-based decision making is just no longer enough. For competing with maximum, sustained impact and mitigated opportunity loss, it's rapidly monetizing data that's now the name of the game--particularly when spurred by artificial intelligence (AI). Indeed, emerging AI methodologies are helping forward-thinking companies achieve and sustain true agility, fuel growth and compete far more aggressively than ever before. AI is critical as a means toward those ends and also certainly with respect to aptly predicting, preparing and responding to prospective crises as with the COVID-19 pandemic the globe is currently immersed in. In fact, Gartner recently cited the need for "smarter, faster, more responsible AI" as its No. 1 top trend that data and analytics leaders should focus on--particularly those looking to "make essential investments to prepare for a post-pandemic reset."

In response to the COVID-19 emergency, over 500 clinical trials of potential COVID-19 treatments and interventions began worldwide. The trials use a living database that compiles and curates data from trial registries and other sources. This helps medical and public health experts predict disease spread, find new treatments and plan for clinical management of the pandemic. Data and analytics combined with artificial intelligence (AI) technologies will be paramount in the effort to predict, prepare and respond in a proactive and accelerated manner to a global crisis and its aftermath. "To innovate their way beyond the post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts," says Rita Sallam, Distinguished VP Analyst, Gartner. Here are the top 10 technology trends that data and analytics leaders should focus on as they look to make essential investments to prepare for a reset.

Gartner, Inc. identified the top 10 data and analytics (D&A) technology trends for 2020 that can help data and analytics leaders navigate their COVID-19 response and recovery and prepare for a post-pandemic reset. "To innovate their way beyond a post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts," said Rita Sallam, distinguished research vice president at Gartner. By the end of 2024, 75% of organizations will shift from piloting to operationalizing artificial intelligence (AI), driving a 5 times increase in streaming data and analytics infrastructures. Within the current pandemic context, AI techniques such as machine learning (ML), optimization and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures. Other smarter AI techniques such as reinforcement learning and distributed learning are creating more adaptable and flexible systems to handle complex business situations; for example, agent-based systems that model and simulate complex systems.

Gartner, Inc. identified the top 10 data and analytics (D&A) technology trends for 2020 that can help data and analytics leaders navigate their COVID-19 response and recovery and prepare for a post-pandemic reset. "To innovate their way beyond a post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts," said Rita Sallam, distinguished research vice president at Gartner. AIBy the end of 2024, 75% of organizations will shift from piloting to operationalizing artificial intelligence (AI), driving a 5 times increase in streaming data and analytics infrastructures. Within the current pandemic context, AI techniques such as machine learning (ML), optimization and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures.Other smarter AI techniques such as reinforcement learning and distributed learning are creating more adaptable and flexible systems to handle complex business situations; for example, agent-based systems that model and simulate complex systems. Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click authoring and exploration. As a result, the amount of time users spend using predefined dashboards will decline.

Despite the promise of artificial intelligence (AI) and machine learning (ML), the greatest challenge of all is not data or process or technology -- it is culture. Such technologies have promised automation galore and insight discovery at the flip of a switch. But culture continues to impede our ability to realize this promise. Data and analytics leaders need to put critical touchstones in place today to ensure the right decisions are taken in the right way at the right time and for the right outcome. This special report provides the insight, best practices and critical touchstones you need to set up now in order to help rewire your culture.

Augmented analytics and artificial intelligence (AI) are among the top data and analytics technology trends that have the potential to significantly change business operations in the next three to five years, according to a presentation at the Gartner Data and Analytics Summit in Sydney this week. Data and analytics leaders must examine the potential business impact of these technology trends, and adjust business models accordingly--or risk losing competitive advantage to companies that do, Rita Sallam, research vice president at Gartner, said at the event and in a press release. "The story of data and analytics keeps evolving, from supporting internal decision making to continuous intelligence, information products and appointing chief data officers," Sallam said in the release. "It's critical to gain a deeper understanding of the technology trends fueling that evolving story and prioritize them based on business value." With digital transformation efforts underway at most organizations, businesses are collecting more data than ever before, creating challenges but also major opportunities, Donald Feinberg, vice president and distinguished analyst at Gartner, said in the release.