WinWire
概述
总部
美国
|
成立年份
2006
|
公司类型
私营公司
|
收入
$10-100m
|
员工人数
51 - 200
|
网站
|
公司介绍
WinWire Technologies 是一家专业的 IT 解决方案公司,专注于为企业提供可操作的信息。我们通过利用预先构建的协作和分析解决方案加速器以及跨平台移动技术,帮助业务和技术领导者实现“移动中”的业务环境。需要移动和云解决方案的企业依靠 WinWire 的咨询专业知识和思想领先的解决方案来连接其业务部门、员工和客户,从而提高协作以及决策的质量和速度。 WinWire 处于移动革命的最前沿,专注于利用原生、HTML5、 移动企业应用平台和云作为后端 (MBaaS) 技术的移动企业应用。作为 Microsoft 托管合作伙伴,多年来,我们通过利用 SharePoint、SQL Server、Office365 等平台以及基于 Azure 和 .NET 编程框架的定制解决方案,帮助企业客户实现其业务目标,从而建立了我们的全球业务。 WinWire Technologies 由微软前高管创立,总部位于加利福尼亚州圣克拉拉,在芝加哥、纽约、亚特兰大、达拉斯和印度班加罗尔和海得拉巴设有离岸开发中心。
物联网应用简介
WinWire 是 云规划/设计/实施服务, 和 系统集成等工业物联网服务方面的供应商。同时致力于建筑与基础设施等行业。
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实例探究.
Case Study
A centralized data warehouse for unified reporting and analytical needs
One of the main challenges was that the company required a centralized data warehouse for unified reporting and analytical requirements. The data was not consolidated properly and its structure was not suitable for user requirements. Besides, reporting process was extremely slow. Individual systems had expanded to the point that information was no longer stored and presented in the centralized manner that could facilitate efficient organizational decisions across the company as a whole. It was also becoming obvious that a data warehouse should better enable internal and external user access to data and increase the performance of analysis and reporting activities. To evolve its offering from simple data feeds to self-service BI, the company needed a new robust platform that could enable users come out of excel mindset and could take them to exploratory mode for better and faster decision making. The objective was to integrate the line of business applications (On-Premise and SAAS).
Case Study
WinWire's Digital Transformation Journey with Azure and Generative AI
The case study revolves around the challenge of digital transformation faced by many organizations. In the rapidly evolving digital landscape, businesses are under constant pressure to adapt and innovate. They need to increase their business agility, improve customer experience, and lower the total cost of ownership. However, the process of digital transformation is complex and fraught with challenges. It requires a deep understanding of technology, a clear vision for the future, and the ability to execute effectively. The challenge is not just about adopting new technologies, but also about changing the way businesses operate and deliver value to their customers.
Case Study
WinWire's Digital Transformation Journey with Azure and Generative AI
In the rapidly evolving digital landscape, organizations are constantly seeking ways to unlock new opportunities and accelerate their digital transformation. The challenge lies in increasing business agility, improving customer experience, and reducing the total cost of ownership. Traditional methods and technologies often fall short in meeting these demands, creating a need for innovative solutions that can drive transformational goals with pace and passion.
Case Study
Chatbots Revolutionize Employee Experience in Materials Engineering Solutions Company
The customer, a global leader in materials engineering solutions, was facing a challenge in managing the increasing number of queries from its employees. The company's help desk team was overwhelmed with the volume of tickets created in Service Now, which was impacting their productivity and increasing support costs. The company needed a more streamlined approach to facilitate their employees and users to avail information from their help desk team. The challenge was to reduce the number of tickets hitting the help desk without compromising the quality of service. The company identified the need for a well-trained conversational bot that could automate responses for FAQs leveraging the power of Artificial Intelligence (AI), Natural Language Processing, and Cognitive Services.
Case Study
Hadoop to Apache Spark Migration: A Case Study on Performance Improvement
The customer, a leading American multinational software firm, was facing significant challenges with their existing Big Data platform. They had initially created a solution using the Hadoop Map Reduce engine and Hive Queries (HQL), but this setup was proving to be inefficient. The main issues were slower code execution speed, higher storage requirements, and difficulty in maintaining workflows. These issues were impacting their business performance and slowing down their digital innovation. As part of a multiyear initiative, the company was planning to move their Big Data platform from Cloudera Hadoop On-Prem instance to Cloudera Data Platform (CDP) on Azure. The first step in this process was to explore the prioritized MapReduce jobs in the current state and consider migrating them to Spark to reduce execution and processing time.
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