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: Robotic Process Automation Adoption Trends

Abstract:

As organizations look for ways to streamline operations, improve efficiency, and reduce costs, they are increasingly embracing automation technology like robotic process automation (RPA). While some view RPA as an ultimate destination to achieve peak business and process efficiency, those organizations that view themselves as digitally transformed have already embraced it and have their eyes set on the next phase: intelligent automation, where RPA is paired with artificial intelligence (AI) and machine learning (ML) to not only interact with systems but also to predict future insights/outcomes based on trending data.

Topics: Data Platforms, Analytics, & AI

ESG Infographic: The Advantages of a Data Science Team

Abstract:

ESG research shows that using a formal data science team is tied to better business outcomes.

Use this infographic to understand what that means for IT organizations in terms of total data use, the public cloud, serverless analytics, and more.

Topics: Data Platforms, Analytics, & AI

ESG Brief: The Advantages of a Data Science Team

Abstract:

As organizations look to prioritize data-driven initiatives, the success of those initiatives will be directly tied to people, processes, and technology. While data science may seem aspirational or even foreign to some organizations, ESG research shows direct ties between organizations with a data science team and better use of data, better use of technology, and better business outcomes. For those organizations looking to drive greater business value through the use of data, a formal data science team can help.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Will Data Lakes Drown Enterprise Data Warehouses?

Abstract:

With the value of data continuing to increase, organizations are constantly looking for better and faster ways to store, access, and analyze it. While many organizations have existing technologies to help stream, collect, store, and analyze both structured and unstructured data, challenges remain that are preventing wider usage of analytics within these organizations. With a goal of consolidating infrastructure and operational silos to address a constantly growing data footprint, data lakes are increasingly becoming the technology of choice.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Enterprise Data Warehouse Trends

Abstract:

Enterprise data warehouses (EDWs) have existed for about 20 years, serving as the foundation of insight-driven organizations, delivering timely analysis and reporting of structured data; handling large analytics workloads; and supporting the high levels of concurrency that organizations demand. But while EDWs have been a familiar presence in many organizations, as companies look to reduce their data center footprints, increase organizational agility, and incorporate as much data as possible into their analytics workflows, the architectural rigidity, complexity, and cost of traditional EDWs have paved the way for modern data warehouses to better respond to the dynamic needs of the business.

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

ESG Brief: Cloud-based Analytics

Abstract:

As organizations look for better ways to integrate, analyze, visualize, and leverage insights from constantly growing data sets, the rise of the cloud has garnered significant interest and traction in the analytics space. The cloud offers numerous enterprise-class attributes that make it more appealing than on-premises environments for organizations, whether they are looking to embrace a data-driven culture or align specific technology to a single line of business.

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

ESG Brief: Informatica Announces Innovations for AI-driven Data Management

Abstract:

Informatica, a leader in enterprise cloud data management, recently announced several enterprise data management enhancements across its unified, AI-powered Intelligent Data Platform to promote agility, efficiency, and productivity. Updates include next-generation analytics, an AI-powered data catalog, cloud and hybrid updates for AWS and MS Azure provisioning and autoscaling, data governance, privacy, 360 engagement, and a customer success portal.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Cloudera Machine Learning

Abstract:

Organizations are turning to AI technologies to enhance their data analytics capabilities and address the real-time needs of the business through faster, more accurate predictive insights. But between skills gaps, limited collaboration, and ineffective or minimally available tooling, organizations are looking for help. Cloudera has introduced Cloudera Machine Learning as the next evolution of their proven Cloudera Data Science Workbench to provide organizations with the help they need to achieve success in leapfrogging the competition using AI.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Artificial Intelligence and Analytics Predictions for 2020

Abstract:

This ESG Brief will review some key predictions for 2020 in the artificial intelligence space, from skills gaps and actionable AI to chatbots and natural language processing.

Topics: Data Platforms, Analytics, & AI

ESG Brief: Workflow Orchestration Your Way with Google Cloud Composer

Abstract:

When complex workflows don’t perform as anticipated, IT can end up spending valuable time addressing infrastructure challenges rather than revenue-generating activities. Google’s Cloud Composer serves as an effective, end-to-end workflow orchestration tool to address the challenges of building, scheduling, and managing complex workflows across diverse environments. With Cloud Composer, Google continues to focus on building integrated solutions that incorporate intelligence and machine learning, while enabling flexibility and portability by being anchored in open source technology.

Topics: Cloud Services & Orchestration