Mike Leone

Mike Leone

ESG Senior Analyst Mike Leone covers converged and hyperconverged infrastructure, data platforms, data management, data analytics, and the emerging blockchain segment. Mike joined ESG as part of the validation team, where he provided third-party validation of claims made by vendors. In his analyst role, Mike draws upon his enthusiasm for bleeding edge technology as well as his engineering and marketing backgrounds to help IT vendors improve everything from product development and marketing to go-to-market strategies and roadmap adjustments.

Recent Posts by Mike Leone:

ESG Infographic: Cloud Analytics Trends

Abstract:

Discover why IT organizations consider the cloud critical to fueling data-driven success with this ESG Infographic, Cloud Analytics Trends.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Data Initiatives Spending Trends for 2022

Abstract:

As organizations increasingly turn to data to enable rapid business innovation, it’s no surprise that a majority of them are spending more on analytics-related data initiatives. Such organizations are looking to empower more decision makers and democratize the use of data, analytics, and AI, but many still need to invest in the technologies and processes necessary to enable the execution and ongoing support of these data priorities.

Topics: Data Platforms, Analytics, & AI IT Spending Intentions

ESG Research Report: Cloud Analytics Trends

Abstract:

In order to gain insight into how public cloud computing services are impacting data analytics strategies, ESG surveyed 338 IT and data-centric decision makers at organizations in North America (US and Canada) with knowledge of or responsibility for their organization’s analytics initiatives and goals, including how these activities intersect with public cloud computing services.

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

ESG Brief: Fueling Data Innovation with Self-service

Abstract:

As organizations look to make data and analytics capabilities available to more stakeholders, providing the right tools, technology, and training for all employees rooted in self-service is proving valuable. A key benefit of self-service is productivity. Experts and generalists alike benefit from self-service technology to ensure faster ramp-up, fewer interruptions, and ongoing improvements in day-to-day tasks.

Topics: Data Platforms, Analytics, & AI Business intelligence

ESG Brief: Business Intelligence Pervasiveness Fueling Adoption of Advanced Capabilities

Abstract:

With a goal of broadening BI usage throughout the business, organizations are turning to advanced BI capabilities. Embedded analytics, mobile application delivery and support, augmented analytics, self-service enablement, low-code/no-code, and natural language querying are expected to rapidly grow in adoption to enable the business to better leverage data and empower more end-users to gain access to actionable insight.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Business Intelligence Adoption Trends: Business Objectives and Challenges

Abstract:

Business intelligence has long served as a technology-driven process for analyzing data and delivering actionable information that helps a variety of roles—from executives and managers to business analysts and data scientists—make more informed business decisions. With the understanding that the goal of BI initiatives is to drive better business decisions that enable organizations to increase revenue, improve operational efficiency, and gain competitive advantages over business rivals, it is no surprise that organizations continue to prioritize BI, as can be seen through larger investments and more end-user exposure throughout the business.

Topics: Data Platforms, Analytics, & AI

ESG Complete Survey Results: Cloud Analytics Survey

Abstract:

ESG conducted a comprehensive online survey of IT decision makers and data architects from private- and public-sector organizations in North America (United States and Canada) between May 3, 2021 and May 15, 2021. To qualify for this survey, respondents were required to be IT decision makers and data architects with knowledge of/responsibility for their organization’s analytics initiatives and goals.

This Complete Survey Results presentation focuses on the impact of public cloud services on data analytics initiatives, including benefits and challenges, as well as what matters most to organizations when evaluating these technology solutions.

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

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 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