foreAction data analytics: Optimization of SQL and NoSQL hybrid architectures

foreAction 数据分析：SQL 和 NoSQL 混合架构的优化

• 批准号: 486616-2015
• 负责人: Kiringa, Iluju
• 金额: $ 1.6万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=585708
• 关键词: foreAction; data; analytics; Optimization; SQL

A software development and technology consulting firm based in Ottawa has developed a software product for the political and non-profit space that collects, stores and analyzes contact data. Based on information stored within the data, the software is used to "micro-target" contacts for specific marketing and informational materials. The software is being developed to allow for the creation of contact lists along three specific axis: the likelihood of a customer to be responsive to a message (propensity score), the value/priority of the contact (value score), and the desired method of contact (medium score). The analytics of these three axis will determine whether a specific engagement must be initiated with the contact during a campaign of any nature. Data is collected continually via ongoing interactions with contacts, via social media polling, via third party statistics (demographics, polling), via surveys/petitions, at events, etc. There is a pressing need to balance the analytics to create valuable, targeted contact lists and a Business Intelligence dashboard (Key Performance Indicators) in a timely and effective way against the need for real time access to updates to the information. In the political space in particular, in the days leading up to an election, the volume of new data can be significant, and needs to be parsed and included in analytics as a part of the outreach strategy for voters. The proposed research looks into optimization techniques, algorithms (especially) and architectures that will allow to update data in real time, and still perform large-scale analytics on the data. An implementation of the solution developed during the research will be done for the consulting firm.

一家总部位于渥太华的软件开发和技术咨询公司为政治和非营利领域开发了一款软件产品，该产品可以收集、存储和分析联系人数据。基于存储在数据中的信息，该软件被用来为特定的营销和信息材料“微目标”联系人。正在开发该软件，以允许沿三个特定轴创建联系人列表：客户响应消息的可能性(倾向分数)、联系人的价值/优先级(价值分数)和所需的联系方法(中等分数)。对这三个轴的分析将决定是否必须在任何性质的活动期间启动与联系人的特定接触。数据是通过与联系人的持续互动、通过社交媒体民意调查、通过第三方统计(人口统计、民意调查)、通过调查/请愿、在活动中等持续收集的。迫切需要平衡 分析，以及时有效的方式创建有价值的、有针对性的联系人列表和商业智能仪表板(关键绩效指标)，以应对对信息更新的实时访问需求。特别是在政治领域，在选举前的几天里，新数据的数量可能很大，需要进行分析，并将其纳入分析，作为选民外联战略的一部分。这项拟议的研究着眼于优化技术、算法(特别是)和架构，这些技术、算法和架构将允许实时更新数据，并仍然对数据进行大规模分析。将为咨询公司实施在研究期间开发的解决方案。