ESG Infographic: The Path to Data Leadership: Embracing Business Intelligence to Achieve Data-driven Success

Abstract:

Business intelligence is the key to data-driven success according to new ESG research—with organizations on the leading-edge of data analytics usage revealing they enjoy a variety of competitive advantages.

Topics: Data Platforms, Analytics, & AI

ESG Brief: The Rise of the All-flash Data Lake

Abstract:

Data is the fuel of the business, creating new value and offering greater insights. A data lake environment plays a foundational role in helping extract value from data, and artificial intelligence initiatives are no exception. As the demand for faster access to data increases, massive scalability is no longer enough for modern data lake environments, so these environments increasingly leverage flash-level performance as well.

Topics: Storage Data Platforms, Analytics, & AI

ESG Brief: AI and the Massive Success Problem

Abstract:

The recent and massive uptick in AI investments has been driven by the fact that these projects are, by and large, successful. This success often fuels an increase in the number of AI objectives, which places greater demands on IT and the underlying infrastructure. To ensure continued success with AI, the right infrastructure must be in place to consolidate data storage and accelerate its usage across the entire data pipeline.

Topics: Storage Data Platforms, Analytics, & AI

ESG Research Report: The Path to Data Leadership

Abstract:

Data teams and developers continue to serve as the lynchpin to businesses, overcoming shortcomings associated with more rapidly and reliably gaining insight from growing data sets. With improving data analytics for real-time business intelligence (BI) and customer insight consistently ranking as one of the business priorities driving significant technology spending, how are organizations enabling more end-users to actually leverage data? Skills gaps, collaboration, and accessibility have created several barriers for democratizing analytics across organizations, and pressure is being placed on data and software teams to make business intelligence easier to leverage and consume. But with the dynamic nature of the business being what it is today and the constant shifting of priorities, timeliness of delivery and accessibility of simplified analytics are being scrutinized. Embedded analytics is increasingly becoming the answer.

Topics: Data Platforms, Analytics, & AI

ESG Brief: AI Adoption Trends

Abstract:

While AI is still considered nascent, the impact it is having on organizations that are embracing it early and often is profound. This serves as a key component to why organizations continue placing bets on AI. Even as skills gaps remain when it comes to incorporating AI into the business, organizations simply cannot afford to wait in adopting the technology as they risk being disrupted by the competition using AI today. With the rise of AI tools that simplify and automate several, if not all aspects of the AI lifecycle, expect adoption of AI to continue exploding for years to come.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Gaining Value from AI

Abstract:

Organizations continue to prioritize AI investments with a goal of achieving a more data-centric future. While business objectives point to several areas where AI can help improve businesses both internally and externally, time to value continues to be scrutinized as organizations make massive investments in people, processes, and technology in support of AI initiatives. Opportunities to reduce time to value continue to pave the way for AI technology vendors that can help simplify the adoption and use of AI technology to support a growing number of use cases throughout the business.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Operationalizing AI: Time, Infrastructure Considerations, and Data Drift

Abstract:

Though the cyclical AI lifecycle is riddled with complexity, the last mile of AI is proving to be the greatest challenge for organizations in their quest to leverage AI. Between diverse and distributed application environments, the rate at which growing data sets change and create data drift, and the dynamic needs of the business, several contributing factors lead to organizations suffering from AI deployment challenges. Both new and mature businesses leveraging AI continue to prioritize opportunities to simplify the last mile of AI—deploying AI into production—with a goal of reducing the amount of time it takes to get from trained model to production. This has paved the way for the emergence of technology to better enable businesses to deploy, track, manage, and iterate on a growing number of ML models in production environments.

Topics: Data Platforms, Analytics, & AI

ESG Brief: The State of Data Lakes

Abstract:

As organizations strive to utilize more data, data lakes are increasingly becoming an attractive option with limitless potential. Data lakes enable organizations to unite disparate data silos and make data more accessible across the business by serving as a centralized repository or collection of data, regardless of shape, speed, or size. Organizations can then leverage a data lake to feed other data-centric tools or utilize tools that sit on top of a data lake to work with the data in-place, such as query optimization solutions that can minimize data movement while enabling improved processing and analysis. And the economic advantages cannot be understated as organizations increasingly leverage cost-effective cloud storage and minimize operating costs through the consolidation of infrastructures silos.

Topics: Data Platforms, Analytics, & AI

ESG Master Survey Results: Supporting AI/ML Initiatives with a Modern Infrastructure Stack

Abstract:

This Master Survey Results presentation focuses on organizations in the process of transforming their businesses with artificial intelligence to understand the evolving data storage requirements of the next-generation applications and workloads supporting AI initiatives.

ESG conducted a comprehensive online survey of IT operations professionals from private- and public-sector organizations in North America (United States and Canada) between September 17, 2020 and September 26, 2020. To qualify for this survey, respondents were required to be IT professionals familiar and involved with evaluating, purchasing, and managing storage associated with AI initiatives for their organizations.

Topics: Storage Data Platforms, Analytics, & AI Cloud Services & Orchestration

ESG Brief: Juniper Enters 2021 Focused on Client-to-cloud Vision: Delivering Superior User Experiences for the AI-driven Enterprise

Abstract:

The global pandemic significantly impacted organizations last year in many different ways. The biggest was undoubtedly the swift transition to work-from-home programs and the need to stand up technology to enable this shift. As a result, many organizations reported that these efforts had dramatically accelerated their company’s digital transformation efforts. ESG research validates this acceleration and highlights that some of the top goals of organizations’ digital transformation initiatives are to drive greater operational efficiencies and deliver differentiated customer experiences. Therefore, it shouldn’t be a surprise that technology vendors are also accelerating their efforts to deliver solutions to enable greater operational efficiency to address the increasing complexity arising from a highly distributed IT environment. A great example of this vendor transformation can be seen in the steps taken by Juniper Networks.

Topics: Networking Data Platforms, Analytics, & AI