预测分析与数据可视化

Satheeshkumar Palanisamy
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引用次数: 6

摘要

为了提高整体绩效,每个组织、每个部门(如金融、软件、医学甚至天文学)对分析和商业智能工具的需求都在急剧增长。C-factor Computing拥有同样的愿景,即通过数据分析和预测来增强现有产品的能力,以更好地满足客户的需求和利益相关者的决策制定。该项目涉及分析学的5个关键方面——数据采集、大数据或数据存储、数据转换(非结构化到结构化)、数据整理、预测建模/可视化。数据获取包括收集使用该产品的客户和旅游聚合商的现有交易和搜索数据。这些数据用于创建强大的仪表板,能够进行预测分析,帮助公司做出明智的选择。提到的关键方面可以通过各种可用的工具来实现,但需要在每个阶段进行测试,以便为公司中存在的数据实现适当的软件。因此,该项目涉及研究和实施选定的工具,以提供正确的框架来实现能够预测分析的交互式仪表板,该仪表板也可以集成到公司的现有产品中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Analytics with Data Visualization
There has been tremendous growth for the need of analytics and BI tools in every organization, in every sector such as finance, software, medicine and even astronomy in order to better overall performance. C-factor Computing has the same vision of empowering their existing products through data analysis and forecasting to better suit the need of customers and decision making of stakeholders. The project involves 5 key aspects in Analytics - Data Acquisition, Big data or data Storage, Data Transformation (Unstructured to Structured), Data Wrangling, Predictive Modeling / Visualization. Data Acquisition involves gathering existing transactional and search data of customers and travel aggregators who use the product. This data is used to create powerful dashboards capable of predictive analytics which help the company make informed choices. The key aspects mentioned can be achieved through various tools available but requires testing at every stage in order to realize the appropriate software for the data present in the company. Hence the project deals with studying and implementing selected tools in order to provide the right framework to achieve an interactive dashboard capable of predictive analytics which can also be integrated into the existing products of the company.
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