应用程序是现代公司的门面，但作为数字世界的基石，它们也是攻击者的主要目标。根据 WhiteHat Security 的 2021 年 AppSec Stats Flash 报告，超过 40% 的应用程序正在主动泄露数据，可能会暴露敏感信息。在当今的编码环境中，防止此类漏洞是一项日益严峻的挑战。随着软件开发的加速以及企业使用敏捷模型更快地部署更多应用程序，安全问题变得更加复杂。结果？传统的应用程序安全工具无法有效改善公司的安全状况，因为风险并非源于单一的代码更改或错误配置，而是源于多种因素的复杂组合。这就是 Apiiro 发挥作用的地方。

阿拉伯银行需要加速创新并实现数字相关性，以保持其在市场中的领导地位，并满足中东和北非地区不断增长的消费者市场和中小企业部门的需求。

Body & Fit 面临着可扩展性和现有电子商务平台上组件之间集成薄弱的挑战。他们需要一个能够提供卓越的客户体验、全球扩张潜力、持续优化和个性化内容的解决方案。

邦尼尔出版社需要将其商业模式从印刷转向数字，以便在不断萎缩的杂志行业中生存和发展。他们设定了六个月的期限来实现这一目标，并向 Google Cloud 寻求帮助。

Book Creator 希望通过为学生提供自助出版计划来创建自己的数字图书，从而提高学生的参与度和创造力。

数字批发商 Boxed 在 COVID-19 大流行期间其平台上的流量和需求显着增加。该公司需要扩大其基础设施和数据处理规模，以应对大量订单的涌入。

空客情报部门需要重新设计其卫星图像平台，以满足客户日益增长的期望。现有的解决方案无法加速图像和数据的生成和交付。

金融领域的银行面临数字化转型和网络安全威胁的挑战。 BBVA 希望获得敏捷性、减少碳足迹并与数字原生金融科技公司竞争。

印度的小农缺乏获得农业相关信息、新种子和改良土壤分析的机会。不可预见的天气和害虫损害了他们的农作物。

Airwallex 需要确保其基础设施和其他 PCI DSS 相关应用程序满足严格的行业合规性评估。他们还需要可靠性、低延迟和可管理的成本。作为一家初创公司，他们希望专注于其产品的应用程序层而不是基础设施。

Raisin, a successful Fintech start-up in Germany, was facing challenges with data management. Much of the company's data was stored in Excel spreadsheets, making it difficult to access and utilize effectively. The rapid growth of the company and management’s vision of a strong data culture necessitated a streamlined approach to data handling. The company's vision was to make data accessible to every employee, enabling them to make as many decisions as possible with data support. However, they lacked the necessary infrastructure to achieve this. They needed a self-service platform that would provide a unified view of all data sources and allow each employee to obtain easy access to the relevant insights.

A2A 是一家意大利公用事业提供商，面临着扩大业务规模和满足 250 万客户需求的挑战，同时还要努力实现联合国设定的 2030 年可持续发展目标。该公司需要一个数据驱动、以客户为中心的战略支持其增长并适应不断变化的能源市场。

Harver, a pre-employment assessment software company, was facing the challenge of scaling to meet the demands of its growing enterprise customers. Initially, the company relied on labor-intensive statistical analysis in R or Excel to surface hiring metrics to their customers. However, as Harver continued to grow and add more enterprise customers, it had to automate and scale processes in order to provide their growing customer base the insights and customization they expected. The company needed an analytics solution that could also support its multi-tiered product offering, integrate with other tools such as Zendesk, and support multi-tenancy. In addition to the technical functionality, it was also critical that an embedded solution could appear seamless and natural within the impeccably designed Harver platform.

ATB Financial 是加拿大的一家金融机构，面临着来自大型银行和金融科技公司日益激烈的竞争。他们希望增强 IT 环境并改善客户体验。

Blue Apron, a pioneer in the meal kit delivery service industry, faced challenges in managing its complex operations. The company needed to source ingredients at the right time, quality, and price, pack orders efficiently and in exactly the right proportions, and ensure meal kits were delivered to the customer fresh and on time. As data volumes grew and queries became more complex, it became difficult to scale their existing data warehouse hosted on another cloud provider. The only options were choosing ever-larger server classes and increasing storage throughput by purchasing a higher number of provisioned IOPS. This led to a need for a more efficient and scalable solution.

Moderna, a research-driven organization, has always relied heavily on data for its operations. However, the company faced challenges in accessing actionable insights from its data. The majority of employees relied primarily on Excel for data analysis, with some researchers utilizing Spotfire Desktop. These tools required significant manual work and set a high barrier to entry. This manual process led to data silos across the organization, limited opportunity to further explore data, and created issues of consistency resulting from various and conflicting versions of the same report. The company needed a solution that would improve self-service and exploration, maintain data quality and consistency, and ensure the new tool would be cost-effective and integrate with the tools Moderna already had in place.

Sunrun, a leading provider of residential solar power, was facing challenges in managing their growing volumes of data across installation operations, installed systems, customer operations, and sales. The company was using a legacy data stack that required IT and data team support for almost every internal data request. This reliance on IT and the data team drained time and resources with ad-hoc requests, changing requirements, and backlogs of reporting requests. Moreover, the data pipelines and infrastructure weren’t scaling to meet either data growth or increased demand for data access. The data team struggled to respond to changing data sets or new sources of data as quickly as the business demanded, and Sunrun's legacy Oracle data warehouse was not equipped to scale across growing analytics demands or unlock predictive insights with ease.

Waterscan, a leading provider of commercial water management services in the United Kingdom, was facing challenges with its existing business intelligence system. The company was heavily reliant on Excel for its operations, which was proving to be an inhibiting factor for growth. The lack of a business intelligence tool or data model meant that Waterscan teams were constantly uploading and downloading Excel documents to and from their Waterline product to do their jobs. The static nature of Excel reports made it difficult and time-consuming to update numbers with the data from Waterline. Development of new reports or amendments to existing reports used to take up to 4 weeks due to development sprint cycles and release dates. Each new report or amendment would cost Waterscan more than $2,400. Waterscan needed a modern data solution that would save their team time and money in development resources, provide customers with up-to-the-minute insights, and scale as their customer base and demand for data grew.

由于之前的技术基础设施，Boa Vista Serviços 面临着可扩展性、处理能力和创新有限的挑战。他们需要将信息从物理服务器迁移到云端以实现数字化转型。

Before implementing Looker in 2014, Simply Business did not have a centralized data platform or process, which resulted in challenges bringing siloed information together and accessing consistent metrics. Without a single source of truth, many decision-makers across the organization spent their time manually creating their own reports. However, many of these reports and metrics didn’t match up, which led to confusion and mistrust of data, and ultimately delayed decisions and action. The insurance brokerage needed a single source of truth to unify data across its multiple applications. Additionally, since insurance is a highly-regulated industry, it was critical that information be consistent, auditable, and secure.

Grand Rounds, a healthcare company, was established to connect patients with the most qualified experts for their medical needs. The company works with firms of various sizes, from 1,000-member firms to Fortune 50 employers, in over 120 countries. They provide expedited access to top physicians for better health outcomes. However, Grand Rounds faced a challenge in managing and accessing its vast network of data. They needed a partner to help build a scalable, external dashboard to provide its customers with valuable reporting.

Deliveroo, a food delivery service, was facing challenges with its initial BI tool as the company expanded. The tool lacked the necessary security, user management, and automation to support the company's growth. Business users were unable to make agile decisions as they had to wait for technical staff to write SQL for each report they requested. Code management became time-consuming for the data team as each dashboard had a unique code base. Changes in the underlying data architecture required updating the code in about 100 different locations. Additionally, variable demand based on the day of the week or time of day could put unpredictable strains on the data warehouse capacity.

PeopleDoc, a leading provider of SaaS HR platforms, needed a solution that could meet its complex requirements while also complying with the legal framework set out by GDPR. The company aimed to optimize communication and streamline administrative processes between HR departments and employees. However, they lacked a system that could handle complicated data modelling, provide access to real-time accurate data, ensure highly confidential HR information was secure and offer an intuitive user experience.

为遍布巴西的多元化受众提供最佳的客户体验

In early 2014, Dollar Shave Club, a small e-commerce business, was struggling to make use of the vast amount of data they were collecting. They were up against established retail giants in the men's grooming products industry and needed to leverage their data to gain a competitive edge. However, they were facing a bottleneck problem where only a few people could access the data, and everyone else had to wait to get their questions answered. This was causing delays and inefficiencies in their operations. For instance, any reports they needed would have to go through a developer named Juan, which was a time-consuming process. They were also using traditional BI tools, which were not able to fully utilize their data.

Guidewire saw a market opportunity for industry-specific business intelligence software, but it wasn’t practical to build a solution from the ground up. Guidewire customers relied on the SurePower Innovation® enterprise suite for managing their day-to-day business operations, but they had to use third-party tools for business intelligence. They struggled to make sense of limited canned reports after enduring delays from data transfers, and the reports weren’t customized for the insurance business. Guidewire stepped in to close the gap by adding insurance-specific business intelligence features to the SurePower Innovation® suite. From a technical standpoint, the ideal BI solution had to eliminate data silos to offer 360-degree views of all the data, display interactive data visualizations, and support data exploration in real time. The tool also had to be scalable, provide fast performance, align with the Guidewire public cloud strategy, and integrate seamlessly with the SurePower Innovation® platform.

Commonwealth Care Alliance® (CCA) is a not-for-profit, community-based healthcare organization that provides care for high-cost, high-needs individuals. When the COVID-19 pandemic started, CCA knew their members, who live with complex medical, behavioral health and social needs, would be faced with new challenges and require an enhanced level of support and care. CCA also knew the best way to understand, prepare, and protect their members was through the use of timely and reliable data. The challenge was to quickly build monitoring dashboards and infuse COVID-19 information throughout other existing clinical dashboards to allow CCA's clinical workforce to understand how their members were being impacted, their potential risk, and the best next steps to help each member.

GoCardless, a rapidly growing payment platform for businesses, was facing challenges in accessing accurate and reliable data. The company was using a combination of traditional internally developed business intelligence tools and third-party SQL clients that required manual queries. Non-technical business owners had to submit tickets to the analytics team, who wrote code to extract insights. This process was time-consuming and inefficient. The finance team spent four days at the end of each month running revenue numbers, which delayed critical visibility into revenue trends and frustrated executives. The product team also lacked easy and rapid access to product usage data that could help drive a roadmap for accelerated company growth.

Vivino, the world's largest online wine marketplace, was facing challenges with data management. The company was using a plethora of spreadsheets owned by different stakeholders in different time zones, leading to inconsistent and inaccurate data. This was particularly problematic for the eCommerce side of the business, where data was being used to influence strategy and decision-making as the team scaled globally. In addition, technical users who ran their own database queries needed help making sense of conflicting results from queries run without consistent data definitions across the organization.

Charlotte Tilbury, a rapidly-growing global luxury beauty and skincare brand, was seeking to advance its data analytics processes while scaling up its ecommerce platform to meet growing customer needs across channels. The company needed a unified approach to analytics and reporting that would provide access to real-time, critical data insights across the business, from ecommerce to supply chain and finance.