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Gartner: 7 Dynamics Influencing the Evolution of BI and Analytics

Global revenue in the business intelligence (BI) and analytics software market is forecast to reach $18.3 billion in 2017, an increase of 7.3 percent from 2016, according to the latest forecast from Gartner, Inc. By the end of 2020, the market is forecast to grow to $22.8 billion.

According to Gartner, modern BI and analytics continues to expand more rapidly than the overall market, which is offsetting declines in traditional BI spending. The modern BI and analytics platform emerged in the last few years to meet new organizational requirements for accessibility, agility and deeper analytical insight, shifting the market from IT-led, system-of-record reporting to business-led, agile analytics including self-service.

The modern BI and analytics market is expected to decelerate, however, from 63.6 percent growth in 2015 to a projected 19 percent by 2020. Gartner believes this reflects data and analytics becoming mainstream. The market is growing in terms of seat expansion, but revenue will be dampened by pricing pressure.

"Purchasing decisions continue to be influenced heavily by business executives and users who want more agility and the option for small personal and departmental deployments to prove success," said Rita Sallam, Research VP at Gartner. "Enterprise-friendly buying models have become more critical to successful deployments."

Gartner believes the rapidly evolving modern BI and analytics market is being influenced by the following 7 dynamics:

Modern BI at scale will dominate new buying

While business users initially flocked to new modern tools because they could be used without IT assistance, the increased need for governance will serve as the catalyst for renewed IT engagement. Modern BI tools that support greater accessibility, agility and analytical insight at the enterprise level will dominate new purchases.

New innovative and established vendors will drive the next wave of market disruption

The emergence of smart data discovery capabilities, machine learning and automation of the entire analytics workflow will drive a new flurry of buying because of its potential value to reduce time to insights from advanced analytics and deliver them to a broader set of people across the enterprise. While this "smart" wave is being driven by new innovative startups, traditional BI vendors that were slow to adjust to the current "modern" wave are driving it in some cases.

Need for complex datasets drives investments in data preparation

Business users want to analyze a diverse, often large and more complex combinations of data sources and data models, faster than ever before. The ability to rapidly prepare, clean, enrich and find trusted datasets in a more automated way becomes an important enabler of expanded use.

Extensibility and embeddability will be key drivers of expanded use and value

Both internal users and customers will either use more automated tools or will embed analytics in the applications they use in their context, or a combination of both. The ability to embed and extend analytics content will be a key enabler of more pervasive adoption and value from analytics.

Support for real-time events and streaming data will expand use

Organizations will increasingly leverage streaming data generated by devices, sensors and people to make faster decisions. Vendors need to invest in similar capabilities to offer buyers a single platform that combines real-time events and streaming data with other types of source data.

Interest in cloud deployments will continue to grow

Cloud deployments of BI and analytics platforms have the potential to reduce cost of ownership and speed time to deployment. However, data gravity that still tilts to the majority of enterprise data residing on-premises continues to be a major inhibitor to adoption. That reticence is abating and Gartner expects the majority of new licensing buying likely to be for cloud deployments by 2020.

Marketplaces will create new opportunities for organizations to buy and sell analytic capabilities and speed time to insight

The availability of an active marketplace where buyers and sellers converge to exchange analytic applications, aggregated data sources, custom visualizations and algorithms is likely to generate increased interest in the BI and analytics space and fuel its future growth.

"Organizations will benefit from the many new and innovative vendors continuing to emerge, as well as significant investment in innovation from large vendors and venture capital-funded startups," said Sallam. "They do, however, need to be careful to limit their technical debt that can occur when multiple stand-alone solutions that demonstrate business value quickly, turn into production deployments without adequate attention being paid to design, implementation and support."

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Gartner: 7 Dynamics Influencing the Evolution of BI and Analytics

Global revenue in the business intelligence (BI) and analytics software market is forecast to reach $18.3 billion in 2017, an increase of 7.3 percent from 2016, according to the latest forecast from Gartner, Inc. By the end of 2020, the market is forecast to grow to $22.8 billion.

According to Gartner, modern BI and analytics continues to expand more rapidly than the overall market, which is offsetting declines in traditional BI spending. The modern BI and analytics platform emerged in the last few years to meet new organizational requirements for accessibility, agility and deeper analytical insight, shifting the market from IT-led, system-of-record reporting to business-led, agile analytics including self-service.

The modern BI and analytics market is expected to decelerate, however, from 63.6 percent growth in 2015 to a projected 19 percent by 2020. Gartner believes this reflects data and analytics becoming mainstream. The market is growing in terms of seat expansion, but revenue will be dampened by pricing pressure.

"Purchasing decisions continue to be influenced heavily by business executives and users who want more agility and the option for small personal and departmental deployments to prove success," said Rita Sallam, Research VP at Gartner. "Enterprise-friendly buying models have become more critical to successful deployments."

Gartner believes the rapidly evolving modern BI and analytics market is being influenced by the following 7 dynamics:

Modern BI at scale will dominate new buying

While business users initially flocked to new modern tools because they could be used without IT assistance, the increased need for governance will serve as the catalyst for renewed IT engagement. Modern BI tools that support greater accessibility, agility and analytical insight at the enterprise level will dominate new purchases.

New innovative and established vendors will drive the next wave of market disruption

The emergence of smart data discovery capabilities, machine learning and automation of the entire analytics workflow will drive a new flurry of buying because of its potential value to reduce time to insights from advanced analytics and deliver them to a broader set of people across the enterprise. While this "smart" wave is being driven by new innovative startups, traditional BI vendors that were slow to adjust to the current "modern" wave are driving it in some cases.

Need for complex datasets drives investments in data preparation

Business users want to analyze a diverse, often large and more complex combinations of data sources and data models, faster than ever before. The ability to rapidly prepare, clean, enrich and find trusted datasets in a more automated way becomes an important enabler of expanded use.

Extensibility and embeddability will be key drivers of expanded use and value

Both internal users and customers will either use more automated tools or will embed analytics in the applications they use in their context, or a combination of both. The ability to embed and extend analytics content will be a key enabler of more pervasive adoption and value from analytics.

Support for real-time events and streaming data will expand use

Organizations will increasingly leverage streaming data generated by devices, sensors and people to make faster decisions. Vendors need to invest in similar capabilities to offer buyers a single platform that combines real-time events and streaming data with other types of source data.

Interest in cloud deployments will continue to grow

Cloud deployments of BI and analytics platforms have the potential to reduce cost of ownership and speed time to deployment. However, data gravity that still tilts to the majority of enterprise data residing on-premises continues to be a major inhibitor to adoption. That reticence is abating and Gartner expects the majority of new licensing buying likely to be for cloud deployments by 2020.

Marketplaces will create new opportunities for organizations to buy and sell analytic capabilities and speed time to insight

The availability of an active marketplace where buyers and sellers converge to exchange analytic applications, aggregated data sources, custom visualizations and algorithms is likely to generate increased interest in the BI and analytics space and fuel its future growth.

"Organizations will benefit from the many new and innovative vendors continuing to emerge, as well as significant investment in innovation from large vendors and venture capital-funded startups," said Sallam. "They do, however, need to be careful to limit their technical debt that can occur when multiple stand-alone solutions that demonstrate business value quickly, turn into production deployments without adequate attention being paid to design, implementation and support."

Hot Topics

The Latest

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...