庆祝数据可靠性的新先锋

说你们公司看好数据是轻描淡写的. 

你的首席执行官一直在谈论她的新Tableau仪表盘, 一份报告,告诉你哪些产品对客户“最具粘性”. 说服你的首席技术官并不难 Snowflake. 你的整个数据工程团队都在致力于这种“数据即代码”的运动.

The flip side of this data-driven coin: your stakeholders (CEO and CTO included) ping you nearly every other hour to ask you: “is my data up-to-date?”, “who owns this report?,甚至是“为什么我的数据丢失了。?”

随着数据系统变得越来越分布式和复杂,以支持额外的用例, the opportunity for data downtime only grows. 事实上,根据邓恩发表的研究 & Bradstreet, 近20%的公司 因不完整或不准确的信息而失去客户.

The good news? 在这个基础上是有希望的 现代数据栈的一层: data observability. With data observability, 数据团队可以获得对其数据的信任, 这意味着数据工程师和分析师们松了一口气, happy execs, and no data downtime. 

可以玩滚球的正规app推荐一个正规滚球网站很荣幸能与那些正在开辟通往 data reliability, 这是加速大规模采用数据的第一步.

庆祝这一新领域的先驱, 推荐一个正规滚球网站很荣幸地强调了这组精选的数据领导者和早期采用者.

These enterprises are charting a new course for what it means to be truly data-driven in today’s world: having trusted, B2B SaaS等行业的可靠数据, digital marketplaces, financial technology, eCommerce, consumer technology, and retail.

B2B SaaS

PagerDuty

PagerDuty is the world’s leading digital operations platform for full-stack incident response and on-call management. As an organization, they are dedicated to helping professionals achieve reliability across their software and data ecosystems. 数据决定着每一个商业决策, 从客户支持到功能开发, and most recently, 如何支持受COVID-19影响最大的组织的定价计划. 

当迁移到雪花, PagerDuty wanted to understand the health of their data pipelines through fully automated data observability. 为了实现这种数据信任,他们求助于可以玩滚球的正规app

“Powered by real-time data, PagerDuty的数字运营管理平台支持超过13个,为了应用程序的可靠性,全世界有000家企业达到了正常运行时间sla. 当涉及到确保PagerDuty业务数据的正常运行时间时,推荐一个正规滚球网站的数据工程 & Business Insights team applies similar principles of AI-driven observability and monitoring to stop data quality issues in their tracks. With Monte Carlo, my team is the first to know when data breaks so that we can manage that incident lifecycle through Pagerduty, 从而允许推荐一个正规滚球网站在数据停机影响业务之前防止和解决它,” said Manu Raj, PagerDuty数据平台和分析高级总监.

Hotjar

For Hotjar, 数据支持各种各样的用例, 从制作理想的营销活动,创造令人愉快的产品特征. Hotjar的数据工程团队支持超过180个涉众和他们的数据需求, 从部署模型和构建管道到密切关注数据健康状况.

以确保他们的数据管道是可靠和值得信任的, Hotjar relied on dbt for testing and transforming their data before it entered their business intelligence layer. 然而,这种方法经常导致关于管道延迟的警报问题. 为了适应这一差距,并补充他们的测试策略, Pablo Recio and the rest of Hotjar’s data engineering team chose to implement Monte Carlo for 端到端数据可观测性, monitoring, and field-level lineage, 通知他们管道中的关键问题,为他们节省3倍的基础设施成本. 

“Monte Carlo gives us the power to know what’s going on with our data at any given point in time so we can ask the right questions when data downtime strikes, 例如,推荐一个正规滚球网站认为这里出了问题, did you change anything, or is this expected?’”Hotjar的数据工程师巴勃罗·雷西奥(Pablo Recio)说.

Consumer Technology 

Jimdo Data

Jimdo, 德国网站建设和一体化主机解决方案, 允许商业专业人士毫不费力地创建一个网站或商店为他们的小企业. 用数据驱动产品路线图, executive decision making, 甚至是进入市场的策略, Jimdo负担不起数据停机的费用. 为涉众提供可靠的数据,并确保跨业务的端到端数据信任, Jimdo turned to Monte Carlo.

“数据领域正处于一个转折点. We have unprecedented volumes of data and incredible amounts of computing power but also constantly increasing complexity. 具有讽刺意味的是,推荐一个正规滚球网站掌握的数据越多,情况似乎就越模糊. 当数据团队试图衡量自己的表现时,这一点再正确不过了. Are tables up to date? Is the data safe to use? 这种异常是业务结果还是数据管道问题?,” said Gordon Wong, Jimdo临时CDO,主要解决方案架构师.

“What excites me about Monte Carlo is their vision for making the delivery of data more reliable and transparent through observability. 该平台的机器学习分析查询, logs, metadata, and other contextual information in such a way that provides the trifecta of data trust: automatic field-level lineage, data discovery, 还有异常检测. This end-to-end solution enables us to both reactively fix data pipeline problems before they impact users and proactively target real system improvement. 其净影响是团队畅通、高管快乐、数据平台成本更低.”

Financial Technology

Pie Insurance

Pie Insurance 负责承担成千上万小企业的风险, 将数据保真度和可靠性作为首要任务. Pie relies on high-quality third-party data combined with predictive analytics to quote a small business owner’s workers’ compensation policy in minutes, 为客户提供无缝的体验. The significance of these insights means that Pie—and its customers—are dependent on this data to be accurate and reliable at all times. Pie Insurance chose Monte Carlo’s end-to-end approach to data observability and lineage to uncover schema, distribution, 还有新鲜度问题,否则这些问题就会被忽视, costing them time, money, and trust in their data.

“To power product growth and deliver exceptional user experiences across our suite of insurance offerings, 推荐一个正规滚球网站可以玩滚球的正规app合作自动驾驶, 端到端数据可观测性.  Within minutes, 几天之内,推荐一个正规滚球网站就在可以玩滚球的正规app开始运作, the platform was uncovering critical schema and pipeline changes that would have impacted the business if left undetected,” said Matt Frazier, Pie Insurance首席分析官.

Clearcover

Clearcover 致力于让车主在保险上节省时间和金钱,变得简单和安全. Their artificial intelligence data-driven platform relies on high-quality data to make coverage recommendations for customers. 确保支持他们的洞察力驱动决策的数据尽可能可靠, Clearcover选择蒙特卡罗提供数据的可观测性, monitoring, 以及跨越雪花和Tableau数据栈的端到端沿袭. 

“使用蒙特卡罗的ml驱动异常检测和场级血统, our data team can effortlessly manage and triage data incidents before they affect downstream consumers, 积极地了解这些问题的影响,这样推荐一个正规滚球网站就能纠正错误. Now, our data engineers and analysts can collaborate to achieve data trust at each stage of the data pipeline, from ingestion to analytics. 他们的未来是光明的,推荐一个正规滚球网站不能更兴奋与他们开创数据可靠性!Clearcover的高级数据工程师Braun Reyes说.

E-commerce

Red Ventures UK

数据是机器学习和商业分析工作的基础 Red Ventures UK,是一套全球领先的消费市场品牌. 因为数据在组织中扮演的角色, 当数据出现问题时,Red Ventures的数据团队必须是第一个发现问题的人, 而不是收到关于“仪表盘坏了”和“值丢失”的疯狂的Slack ping或短信.“在他们的公司投资组合中实现端到端数据可靠性, 他们转向蒙特卡罗的数据观测平台.

“RVU is committed to delivering reliable and accurate data products for teams across our portfolio of companies. 利用蒙特卡罗的端到端数据可观察性, 推荐一个正规滚球网站的数据工程师和分析师可以自动协作进行检测, alert on, 并在数据停机成为业务问题之前解决它. 他们支持ml的监控器可以很容易地跟踪推荐一个正规滚球网站管道中隐藏的数据问题, 允许推荐一个正规滚球网站在数据生命周期的每个阶段都信任它,” said Siddharth Dawara, Principal Engineer, at Red Ventures UK

Media & Entertainment

Kolibri Games

Berlin-based Kolibri Games has had a wild ride, rocketing from a student housing-based startup in 2016 to a headline-making acquisition by Ubisoft in 2020. 虽然在这五年里发生了很多变化, one thing has always remained the same: the company’s commitment to building an insights-driven culture based on accurate and reliable data. 

实现端到端的数据可靠性 自助式、分散的数据体系结构, António Kolibri数据工程主管Fitas选择与可以玩滚球的正规app合作. 有了数据的可观察性,团队充分了解 unknown unknowns in their data pipelines, 允许他们自动识别, root cause, 并在数据问题影响下游分析之前解决它们. 

“数据是Kolibri Games DNA的一部分, 支持推荐一个正规滚球网站的产品路线图, marketing strategy, and growth operations. 每天会产生超过1亿个不同类型的独立事件, 推荐一个正规滚球网站的游戏产生了前所未有的大量数据, and in order to trust it, 推荐一个正规滚球网站需要知道什么时候推荐一个正规滚球网站的管道和仪表盘发生事故. 在尝试为数据监视构建自己的自定义解决方案之后, we realized it would require a full-time person to build a framework to extend it to different use cases and monitor all data assets. Monte Carlo helped us achieve data reliability by monitoring the quality of all of the data in the data warehouse, and providing extra capabilities about understanding the end-to-end lineage and root cause analysis of data issues to speed up troubleshooting and incident resolution,” said António Fitas, Kolibri Games数据工程主管.

Digital Marketplaces 

AutoTrader

Manchester-based Auto Trader 是英国和爱尔兰最大的数字汽车市场吗. For Auto Trader, 将数百万买家和数千卖家联系起来需要大量的数据. 

该公司每月的广告浏览量为2.35亿次,跨平台访问量为5000万次, with thousands of interactions per minute—all data points the Auto Trader team can analyze and leverage to improve efficiency, customer experience, and, ultimately, revenue. Data also powers business outcomes from advertising optimization to reporting to ML-powered vehicle valuations. 实现大规模的数据信任, Edward Kent, Principal Developer, 和他的数据工程团队转向了蒙特卡罗的端到端数据可观测平台. 

“Before Monte Carlo, 推荐一个正规滚球网站需要提前知道推荐一个正规滚球网站想要监控什么, 并手动设置dbt和SQL测试. AutoTrader每天定义数百个数据模型,构建数百个表, 这使得手动设置时间和资源密集. With Monte Carlo, we were able to achieve end-to-end data trust off the bat without us having to put in that effort and know what we needed to test for. With Monte Carlo’s schema, freshness, and volume checks, 推荐一个正规滚球网站比以往任何时候都能更清楚地了解推荐一个正规滚球网站的数据. Previously, a lot of these issues would have been caught and reported by data consumers are now getting automatically flagged. From a tracking perspective, this visibility is hugely important for us as we move towards decentralized data ownership and true data reliability,” said Edward Kent, Principal Developer, Auto Trader.

Retail 

Resident

Resident, 一个直接面向消费者的床垫品牌之家, 依靠数据来推动营销决策和支出, 拥有超过20个市场关系支持线索和客户跟踪, segmentation, and retail analytics. In 2019, the company suffered from unreliable data and strained relationships between teams because stakeholders weren’t able to access the most up-to-date data they needed to make decisions. 超越公司内部关系, 客户体验也受到了影响, 糟糕的数据会导致客户收到与他们无关的邮件.

丹尼尔和她的团队开始明白他们需要什么, 而不是构建一个定制系统, 居民开始使用蒙特卡罗来处理实时监控和警报, as well as lineage

“在可以玩滚球的正规app之前,我总是很警惕,害怕自己会错过什么. 我现在无法想象没有它的工作. 一年前的事故只有现在的10%. 推荐一个正规滚球网站的团队非常可靠,大家都依靠推荐一个正规滚球网站. I think every data engineer has to have this level of monitoring in order to do this work in an efficient and good way,” said Daniel Rimon, Head of Data Engineering, Resident. 

为数据可靠性的先驱们干杯! 

数据可靠性的前景远远超出了这些精选的企业群体, 影响整个医疗保健行业的公司, banking, hospitality, education, 几乎所有其他依赖数据创新和保持竞争优势的领域都是如此.

这是这段旅程中最好的部分? 与整个领域的数据领导者合作,开创数据可观察性范畴. 通过正确的数据信任方法,跨行业的团队可以消除 Data Downtime 释放他们数据的全部潜力.

有兴趣加入数据可靠性运动? Reach out to the Monte Carlo Team!

9月6日修正. 4, 2021: An earlier version of this article stated that “data downtime caused 1 in 5 companies to lose a customer,而不是“20%的公司。.”