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 Brief: The State of Open Source in Cloud Analytics

Abstract:

Many organizations use open source analytics and data management technology, which often serves as a foundation of their data-centric technology ecosystems. But deploying and managing open source tools and solutions are a challenge in many cases—a situation that calls for managed services to help ease the challenges and pave the way for increased open source adoption, especially in distributed cloud environments.

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

ESG Brief: The Argument for a Single Public Cloud Vendor to Support All Analytics Initiatives

Abstract:

Many decision makers are interested in standardizing their analytics initiatives on a single cloud provider’s infrastructure and services. A large majority think their organization would be open to considering such a move. This research highlights what they’d be looking for by doing so—easier management, simplified support, and more. But it also points to a fundamental question: Can one vendor meet all of an organization’s data needs?

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

ESG Brief: Data Integration in a Multi-cloud World

Abstract:

Data integration is proving to be more complex in the cloud for a majority of organizations, especially ones that use public cloud services in multi-cloud environments as part of their analytics initiatives. Many are turning to new tools and managed services to help them cope with integration challenges. In a lot of cases, though, they're also moving to decrease the number of vendors they currently use.

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

ESG Brief: The Operational Management Conundrum of Data and Analytics in the Cloud

Abstract:

Most organizations use technologies from a variety of public cloud and third-party software providers to support their data management and analytics strategy. That complicates ongoing operational management of cloud analytics environments, and multi-cloud deployments exacerbate the challenges—and the headaches they cause. This research highlights what organizations are doing to try to ease the pain without disrupting critical data workflows.

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

ESG Brief: The Continued Opportunity to Improve Time to Value in Data and Analytics Initiatives

Abstract:

While most IT decision makers believe their organization is doing a good job of acting on data insights, it often takes weeks or months to generate and then act on those insights. There's an opportunity to do better by deploying new technologies and making the data lifecycle more efficient—and organizations that don't address the time-to-value gap may find themselves lagging behind faster and more agile rivals.

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

ESG Brief: Cloud Analytics Tools Adoption Trends

Abstract:

More organizations are turning to the public cloud to support data initiatives, many of them using cloud services from both cloud providers and third-party software vendors. Within 12 months, sizable majorities of organizations plan to run various data management and analytics tools on public cloud infrastructure. Hybrid environments that also include on-premises systems often need to be maintained, but investments in cloud-based technologies clearly are on the rise to help meet data-driven business goals.

Topics: Data Platforms, Analytics, & AI Application & Infrastructure Modernization

ESG Brief: The Criticality of the Cloud to Data-centric Success

Abstract:

The public cloud is a good match for modern data needs and goals, and organizations increasingly recognize that as part of their data analytics strategy. The benefits they’re gaining will drive further adoption of public cloud services to support data initiatives. But there are challenges that must be overcome to ensure that cloud analytics deployments are successful. This research provides insight into the top benefits and challenges of using the cloud.

Topics: Data Platforms, Analytics, & AI Application & Infrastructure Modernization

ESG Research Report: The State of DataOps

Research Objectives

The need for rapid insight is forcing organizations to prioritize agility, transparency, and speed across their data ecosystems with a goal of improving operational efficiency, improving collaboration, and accelerating time to value from investments in support of data-driven initiatives. But organizations need help ensuring seamless orchestration, appropriate management, and timely delivery of data in support of the people, tools, processes, and environments that fuel their business. Between data quality issues, distributed data, tool proliferation, overburdened and under-skilled teams, rising costs, and increased risk, the complexity of today’s data ecosystem hinders democratization of data and analytics. This is a big reason why organizations are turning to DataOps—an agile, automated, and process-oriented methodology used by data stakeholders to improve the quality, delivery, and management of data and analytics. And the wide belief is that establishing DataOps will set organizations up for success as they look to achieve a data-driven future through an agile, process-oriented approach to securely accessing and analyzing data at scale.

Topics: Data Platforms, Analytics, & AI

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