Sisense
概述
总部
美国
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成立年份
2004
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公司类型
私营公司
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收入
$100m-1b
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员工人数
201 - 1,000
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网站
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公司介绍
Sisense 是一家商业分析软件公司,它使非技术用户能够加入和分析大型数据集。该公司为分析应用程序的构建者提供强大的工具,以简化复杂的数据并为组织内外的每个人提供洞察力。它使用人工智能算法来分析组织数据。 Sisense 让构建者在单一平台上进行协作,在混合、云原生环境中以业界最低的拥有成本交付,以实现数据和分析的真正民主化。该公司大大加快了构建、嵌入和部署智能分析应用程序所需的时间,这些应用程序可以释放用户的创造力和参与度。它在全球拥有数千名客户,包括 Tinder、Flexport、Expedia、UiPath、纳斯达克、世界经济论坛和救世军等行业领导者。 Sisense 总部位于美国纽约,在旧金山、斯科茨代尔、特拉维夫、基辅、伦敦和东京设有办事处。
物联网解决方案
Sisense 数据和分析平台是一个完整的端到端 BI 平台,它使数据工程师、开发人员和分析师能够构建提供高度交互式用户体验的分析应用程序。
主要客户
惠普、飞利浦、纳斯达克、摩托罗拉、富士通
物联网应用简介
技术栈
Sisense的技术栈描绘了Sisense在平台即服务 (paas), 应用基础设施与中间件, 分析与建模, 和 功能应用等物联网技术方面的实践。
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设备层
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边缘层
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云层
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应用层
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配套技术
技术能力:
无
弱
中等
强
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实例探究.
Case Study
Vitality's Transformation into an Enterprise-Level Product with Sisense's Embedded Analytics
Vitality, a company focused on making buildings smart by analyzing IoT data for energy savings and risk mitigation, faced a significant challenge as it grew. The company's original plan involved building basic analytics into its platform. However, as the company expanded, customer demands for analytics quickly outpaced what Vitality could build in-house. The company realized it needed to purchase analytics capabilities to stay relevant to its customers. These capabilities needed to be seamlessly integrated into its proprietary platform, matching the look and feel of its software, and delivering an industry-leading user experience. Additionally, Vitality saw a huge potential for future growth by augmenting its powerful algorithms with industry-leading embedded analytics.
Case Study
Transforming Data Reporting: Profusion's Journey with Sisense
Profusion, a data science and marketing services company, was grappling with the challenge of slow and reactive reporting for its clients. The company wanted to transition its clients from relying on manual, Excel-based reporting to a more proactive, real-time optimization. A specific challenge was presented by a London creative agency, which required Profusion to develop a solution for reporting ticketing data to its client, an international live show production company. The agency had two requirements: an intuitive interface to communicate financial investment and return through different marketing channels, and the ability to query a single customer view of its customer and extract this data for use within its other business tools. The existing process was labor-intensive, with information only available sporadically or on the client’s request.
Case Study
Marketing Agency TLC Sees 25% Improvement in Productivity
TLC’s approach to organizing high-quality data for analysis and distribution across the company and to clients was both labor-intensive and extremely time-consuming. Client data wasn’t being retained in any real meaningful fashion with data analysis and reporting was mostly done manually and managed in extremely complex Excel spreadsheets.On top of this, report delivery was done on a monthly basis by email and the sheer size of the spreadsheets was becoming problematic. Their data was triple the size of what any cloud-based system could handle and the need for superior reporting and analysis in a timely fashion to maximize fundraising was imperative.
Case Study
Interfolio's Modern Data Strategy: A Case Study
Interfolio, a software service provider for higher education institutions, faced a significant challenge as its user base and data volume grew. The company needed a modern data strategy that could unify internal data, streamline reporting processes, and be flexible and scalable enough to serve as an embedded solution within the Interfolio platform. The primary challenge was selecting a BI platform and a cloud data platform that could handle multiple data sources, model complexity, and enable straightforward dashboard creation. The company had been using a competing BI vendor and an in-house solution for managing their consumer-based SaaS metrics and reporting, and for managing reporting data for quarterly business reviews. However, as data sets grew exponentially, these solutions were no longer performant or scalable.
Case Study
Automating BI and ETL for Enhanced Enrollment: A MindMax Case Study
MindMax, a company that partners with universities to increase enrollment, particularly among continuing education and adult learners, faced a significant challenge in scaling its customer base. The company's legacy analytics and BI solution required manual extraction of data from disparate sources, including Salesforce, Google Analytics, Facebook Ads, LinkedIn, and Marketing Automation systems. This process was time-consuming and inefficient, making it difficult to create meaningful reports and dashboards that incorporated data from all these different sources. The company's VP of Technology, Brian DiScipio, and Senior Business Analyst, Kiersten Warendorf, recognized the need for a cleaner, faster way to empower their customers with data-driven insights. They knew that the full automation of BI and ETL through the creation of a modern data pipeline and stack was crucial for the company's growth.
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