Sanitas 是一家医疗保健提供商，正在努力应对理解位置对其诊所和医院绩效的影响的挑战。医疗保健行业的位置起着重要作用，Sanitas 希望深入了解其诊所位置的具体特征。他们想了解这些特征（包括当地人口的年龄和收入）如何影响诊所的业绩和收入。此外，他们希望根据有关其客户、竞争对手和该地区其他兴趣点的信息来介绍他们的诊所。

美国第二大无线运营商 T-Mobile 在 2021 年初推出 5G 家庭互联网服务时面临着重大挑战。在开始试点后，该服务已向美国 3000 万个家庭提供。 2019 年。挑战在于，固定地址的无线互联网需要与传统互联网服务提供商 (ISP) 截然不同的资格流程。做出有关候选资格的明智决策需要大量空间数据。美国有 1.85 亿个唯一地址，每个地址都有无数与之相关的变量，T-Mobile 需要确定谁有资格获得服务。这包括从总体上确定哪些邮政编码、MSA 或州具有最大的潜力。

Aena 是全球最大的机场管理公司，面临着改善机场内乘客导航的挑战。该公司希望增强乘客在旅程各个阶段的整体体验。主要目标是让乘客能够可视化整个旅程并找到关键兴趣点，例如餐厅、商店、厕所或安全控制。此外，Aena 希望为乘客提供到达登机口所需时间的估计。考虑到每年有超过 2.75 亿旅客经过 46 个西班牙机场以及伦敦-卢顿和美国的 23 个机场，这是一项重大挑战。

ASDA 是英国最大的连锁超市之一，在扩展其“toyou”包裹服务时面临着挑战。最初，该服务在其庄园内的 639 个地点提供。然而，ASDA 的目标是通过在更靠近客户的地方设置外部投递箱，将这一数字增加到 5,000 个地点，而不是仅仅依赖传统的场所（消费者通常需要 10 分钟的通勤时间）。为了启动其扩张计划，ASDA 需要位置数据和见解，以了解部署前新的点击提货位置选址的关键驱动因素。他们还需要了解与目标人口和社会经济群体（例如大学）的接近程度。

Bumble 团队正在寻找在渗透率较低的市场中扩张的机会。传统上，他们通过查看每月和每日的活跃用户来衡量自己的市场份额。虽然这让他们了解了特定市场的用户群规模，但并没有清楚地了解他们的实际市场渗透率。例如，美国、中国、巴西等人口众多的市场自然拥有更大的用户基础。然而，活跃用户数量并不一定反映公司的市场地位。因此，Bumble 需要一种更准确的方法来估计其总目标市场 (TAM) 和市场渗透率。

西班牙巴伦西亚地区是当地和国际游客的热门目的地，拥有 340 多个海滩。在局势降级阶段，该地区接待了大量游客。巴伦西亚自治区政府巴伦西亚自治区政府指出，管理海滩容量以确保游客安全是一项挑战。他们需要一种可以向游客提供有关海滩容量的实时信息的工具。该工具需要适合移动设备，因为大多数访问者可能会在移动设备上访问信息。

空间数据分析正处于关键时刻。在过去十年左右的时间里，客户必须管理自己的基础设施，包括 GIS 软件的安装和维护。这可能是在笔记本电脑、台式机甚至大型机上，但确定计算机的大小、所需的 CPU 周期以及所需的存储容量的责任落在客户身上。这个过程不仅耗时，而且需要大量的技术专业知识。此外，客户必须找到并准备分析所需的数据集，这可能是一个具有挑战性且成本高昂的过程。

Hodges Ward Elliott 是一家商业房地产投资公司，希望利用数据科学在房地产市场上获得竞争优势。该公司认识到数据科学在房地产行业的潜力，而房地产行业传统上采用此类技术的速度很慢。我们面临的挑战是找到一种有效利用数据科学来了解人群偏好以及这些偏好如何随时间变化的方法。这种理解对于预测房地产趋势至关重要，因为它可以深入了解人们想要在哪里生活、购物和工作。然而，由于房地产行业缺乏现成的数据，获取和分析相关数据是一项重大挑战。

The city of Medellín wanted to serve a broader demographic by applying new technologies to connect city departments and agencies like transportation, administration, healthcare, education, utilities, and construction. To accomplish Medellín’s objectives, priority was given to the areas of the city where bigger social and economic issues were found. Emphasis was placed on the planning and development of urban projects to transform the physical environment in order to implement profound social and cultural shifts in the targeted communities.

Red Eléctrica de España (REE) wanted to provide the public with real-time information on over 2,000 indicators related to the Spanish electrical grid. It was critical to find a solution that was comprehensive and easy-to-use because indicators are responsible for making timely information public by law. With thousands of indicators, many updating every ten minutes, REE had to find a way to organize and display them so they could be found, analyzed, and understood. There was also a desire to show the data to an audience that lacked technical knowledge. They needed a solution that was fully customizable and provided an easy platform for spatial data analysis. Additionally, REE needed a model to visualize the power supply across the whole country, liaise with suppliers, coordinate supply with neighboring countries, and many other measures, that would reveal the performance of the energy market and other interesting data in a way the public could understand.

Fon Wireless Ltd. (Fon) is a leading, worldwide WiFi provider that operates a system of dual access wireless networks. With more than 19 million crowdsourced hotspots, their goal is to extend WiFi around the world. Fon wanted to develop a tool to expose their access point coverage throughout the world, as well as their partner network in various countries. They needed to build an open portal to help customers and clients explore and find millions of access points that they could connect to in the Fon Community WiFi. The portal required a visualization that could be adapted at every zoom level, preserving optimum performance, and the ability to include logos and details of all of Fon’s partners. Additionally, Fon wanted to have a more appealing visualization on their corporate website that enabled partners to have their own map including their specific access points.

Endesa, the largest electric utility company in Spain, was looking to grow its customer base and maintain its leadership in the Spanish market. They needed to understand how to best serve their existing B2C customers and how to gain market share from their competitors. Their Business Intelligence team had previously used Microsoft Excel to evaluate their coverage and measure demand in complex models which were not always accessible to business users in other departments across their business. Endesa wanted to make this process easier, using a more intuitive tool to share insights with departments such as Corporate Strategy, Finance and Location Planning.

OneMap, a real estate and property development mapping platform, was facing a time-consuming process for producing custom maps and reports. They also had to undertake a substantial amount of data entry for their weekly updates. Their primary objective was to reduce the time involved in providing their customers with complete and accurate property reports. They aimed to compile detailed property information into a single, easy-to-use platform capable of leveraging location data and processing a high volume of attributes from each point. They also sought the capacity to create high-quality digital maps that would empower their customers, providing them with the means to visualize multiple data streams and perform their own filtering and spatial analysis.

Descifra, a global Location Analytics provider based in Mexico City, aimed to disrupt the site planning and sales prediction process with their product, Omen. The product brings together a large and diverse range of datasets, making it crucial to have an intuitive and slick interface for decision-makers to extract insights. The visualization tool needed to handle millions of data points, often in real-time, without compromising on speed, security, and geographical granularity. The challenge was to forget traditional 150-page PDF reports and put cutting-edge Location Intelligence visualization in the hands of their clients.

Securitas Direct, a leading connected alarms provider, had a large and growing sales force of 1,000 reps tasked with visiting existing and potential customers to retain and acquire new business. However, the allocation of leads and opportunities from their marketing department was done manually without exploiting the context of location data. This resulted in several different sub salesteams looking at the same opportunities and leads often being manually assigned by province, rather than geographical proximity, wasting sales rep’s time and resources. Securitas Direct needed a location-driven solution that would allow their team to be more efficient and productive, and that would work smoothly alongside their existing CRM technology (Force Manager).

Wecity, a sustainable mobility app, wanted to crowdsource and visualize smartphone-generated location data collected from thousands of users every month, for both their web and mobile app. They needed a location technology that would allow them to seamlessly collect, visualize and analyze user-routing data from cities and governments, and also about intermodality for potential partners, to create safety insights and indicators for its users. They also wanted to create a compelling platform by embedding maps that were beautiful and easy to use, as well as in line with the rest of their app.

Indigo Agriculture, a company that works with growers to reimagine the entire agriculture system, faced several challenges in their data-driven approach to business. Their analytics team had to deal with a wide range of internal and external data sources, including internal CRM data from Salesforce, external meteorological datasets, and data collected in the field. The team needed to pull data from existing systems and upload a variety of data formats for collaboration across departments and the creation of a seamless end-to-end experience for customers. Another challenge was turning complex geospatial data into actionable insights for business users. The team sought to provide business users in marketing, sales, and field operations a more intuitive and interactive format for viewing data, instead of relying solely on traditional, tabular data. Lastly, the business units often needed to see prototypes or analysis against tight deadlines. The team needed to quickly bring together data, carry out complex geospatial analysis, and deliver dashboards to ensure geospatial analytics were considered in all business decisions.

Mastercard, one of the world's largest financial services companies, processes over 160 million transactions every hour. This transaction data is extremely valuable and represents a significant resource for the company. However, monetizing this data presents several challenges. Firstly, any data monetization strategy must prioritize data privacy and security to maintain Mastercard's promise of keeping payments safe and secure. This requires anonymizing and aggregating the data to remove individual identifiers and prevent the inference of specific identifiers once the data has been aggregated. Secondly, the data needs to be productized in a way that appeals to a diverse audience with varied needs. This requires delivering an intuitive and singular user interface while ensuring the user experience is tailored based on industry and role. Lastly, the spatial nature of the transaction data presents challenges in determining the spatial scales at which to aggregate data. This is particularly complex when working internationally, as different countries have distinct geographic units.

Tinsa Digital wanted to provide more powerful solutions that would allow their clients (Financial Institutions, Investment Funds and Real Estate agencies) to manage their portfolios in a more agile way - with more spatial insight. The solution needed to provide a series of indicators in relation to asset locations so that clients could see relevant segments using multiple layers of information in just a few clicks. Working with CARTO’s platform allowed Tinsa Digital to automate processes, such as the loading and visualization of information, generating a 'user-friendly' display, requiring no specialized training. This allowed these different divisions of their business to perform complex calculations, delivering results faster, as well as including different layers to complete Real Estate, financial, or geospatial analyses. This would allow them to create AOIs (Areas of Influence) correctly attributing values to different administrative regions, as well as optimizing their own geometries. The key challenges included: User management for large volumes of information, Flexibility and responsiveness when working alongside Tinsa Digital clients, Effective integration and automation of ETL processes.

Securitas Direct 是欧洲领先的联网警报提供商，其销售部门面临着重大挑战。尽管拥有一支由 1,000 名代表组成的强大销售队伍，该公司并未充分利用位置数据在其销售策略中的潜力。销售团队一直在手动分配营销部门的销售线索和机会，而没有利用位置数据的上下文。这种方法不仅效率低下，而且无法最大限度地提高销售人员的生产力。为了提高销售业绩，Securitas Direct 需要一个位置驱动的解决方案，该解决方案不仅可以提高团队的效率和生产力，还可以与现有的 CRM 技术无缝集成。

SEUR 是西班牙领先的包裹递送公司，在优化其冷运输网络方面面临着挑战。该公司正在寻找一种解决方案，使他们能够评估网络的当前状态，识别高需求区域，并确定其配送中心 (DC) 的位置是否具有战略意义。他们还希望量化当前网络变化的影响，例如配送中心的开设或关闭以及配送区域的变化。此外，SEUR 正在寻求建立一个优化模型，以确定配送中心应位于何处并设计其运输网络（供应链网络设计）。

Telefónica 是一家跨国电信公司，希望增强其数据分析能力。该公司确定了数据分析的三个级别：描述性、预测性和规范性。描述性方面涉及可视化数据模式，是一个特殊的挑战。传统的数据表示方法（例如 Excel 工作表）无法有效传达智能步骤的模式，包括人们如何移动、从哪里来以及去哪里。该公司需要一种解决方案，能够提供一种更具交互性和视觉吸引力的方式来向客户呈现数据，因为客户非常注重视觉效果并且更喜欢与数据交互。

沃达丰是一家领先的电信公司，严重依赖位置情报来管理其网络并为其客户提供优质服务。该公司的目标是了解客户在哪里、他们要去哪里以及如何为他们提供最好的服务，包括光纤和其他技术。挑战在于数据的准确性和精度。沃达丰的目标是打造一款能够精确预测人们行踪的产品，准确地知道人们要去哪里和去哪里。为了达到这种精度水平并超越竞争对手，沃达丰需要克服使用复杂算法和软件构建技术的挑战。

与世界上许多其他主要城市一样，马德里市也面临着交通拥堵的挑战。每天有五十万辆汽车进出城市，管理交通流量和减少拥堵是一个重要问题。 Waze 是一款众包导航和交通应用程序，在全球拥有超过 1 亿活跃用户，它致力于解决这个问题。然而，虽然位智可以访问大量用户生成的数据，但它需要一种与政府组织和市政当局联系的方式来有效利用这些数据。面临的挑战是将原始、开放的数据转化为可操作的情报，可用于改善交通管理，并为公民提供准确、实时的交通信息来规划他们的日常通勤。

在 COVID-19 大流行期间，农村创新中心 (CORI) 面临着分析美国各地差异水平以确定更需要支持的领域的挑战。这一流行病对农村社区产生了重大影响，迫切需要了解这种影响的程度。挑战不仅在于收集相关数据，还在于以能够清晰洞察情况的方式分析和呈现这些数据。这包括确定受缺乏宽带可用性影响的学区以及因疫情而面临重大就业风险的县。

Clear Channel Outdoor 是全球最大的户外媒体公司之一，其运营面临着重大挑战。他们使用移动位置数据连接物理世界和数字世界，识别暴露在户外 (OOH) 面板上的设备，并在 RADAR® 产品中收集这些见解。然而，他们在如何让广告商轻松访问这些数据以进行活动规划时遇到了问题。我们面临的挑战是创建一种解决方案，使广告商能够轻松访问和利用从 Clear Channel Outdoor 收集的移动位置数据中获得的见解。这对于广告商更有效地规划其活动并更有效地接触目标受众至关重要。

金融科技 (fintech) 行业在认识位置数据的存在和可用性及其潜在好处方面面临着重大挑战。该部门拥有丰富的内部数据集和监控系统，可以通过位置数据的集成来增强这些数据集和监控系统。特别是在反洗钱领域，位置数据与金融数据的结合可能有助于协助执法和识别非法活动。然而，如何将这些数据纳入日常运营的意识和理解仍然是一个重大障碍。此外，位置数据的潜力不仅限于反洗钱，还可以通过提供对人们居住地点及其周围社区的深入了解，为营销和信用风险管理提供机会。

Enveritas 是一家非营利组织，成立于 2016 年，其使命是到 2030 年消除咖啡行业的全球贫困。该使命的一个重要部分涉及追踪咖啡从源头到消费者的旅程。这个过程不仅需要确定咖啡种植和加工的地理位置，还需要了解这些地方普遍存在的社会、环境和经济条件。面临的挑战是基于 ECX 分类系统创建复杂类型咖啡的全面动态可视化。该组织需要一个用户友好的解决方案，可以提供咖啡供应链的清晰且易于访问的表示。

谷歌的BigQuery在地理空间分析领域面临着挑战。用于地理空间分析的传统硬件和软件限制了 BigQuery 的潜力。现有基础设施的限制阻碍了地理空间分析的可扩展性和性能。此外，整合地理空间数据的过程既繁琐又耗时。用户经常被要求执行管理任务和参考表，这被认为是“无聊”但必要的。面临的挑战是增强 BigQuery 的地理空间分析能力，并使地理空间数据的集成更加高效和用户友好。

Hodges Ward Elliott 是一家房地产公司，在创建数据驱动的地图方面面临着重大挑战，这是其日常运营的一个基本方面。该过程既费力又耗时，制图部门通常需要 3-4 天才能制作出一张地图。数据科学团队的引入以及Leaflet等开源工具的使用改善了这种情况，但创建高质量地图仍然需要四个小时。该公司正在寻找一种解决方案，可以进一步简化此流程，减少所需时间，并使创建和迭代这些地图变得更加容易。