IBM acquires Databand to improve machine learning models


IBM has acquired Israeli data observability start-up Databand for an undisclosed sum in a deal that it says will help to improve machine learning models by catching bad data early.

Databand is the fifth acquisition for IBM so far this year, including other AI and observability plays. (Photo by MIGUEL MEDINA/AFP via Getty Images)

What is Databand?

Founded in 2018, Databand produces software that is designed to help organisations improve the quality of their data. It says it does this by fixing errors, pipeline failures and poor-quality elements before they reach machine learning models.

It is the fifth acquisition for IBM in the AI and hybrid cloud space this year. These include the takeover of Envizi in January, a data and analytics software provider for environmental performance management and Microsoft Azure consultancy firm Neudesic in February.

IBM says its goal with the acquisitions is to strengthen its software portfolio across data, AI and automation in an attempt to address the “full spectrum of observability”.


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Poor data costs organisations about $12.9m every year, according to research from Gartner, and could lead to “poor decision making” in the long term if bad data feeds into predictive models used to drive the direction of a company or product, the analyst company says.

Data observability, like the platform developed by Databand, deals with understanding why a dataset or pipeline isn’t doing what you expect.

“You can’t protect what you can’t see, and when the data platform is ineffective, everyone is impacted –including customers,” said Josh Benamram, co-founder and CEO of Databand. “Joining IBM will help us scale our software and significantly accelerate our ability to meet the evolving needs of enterprise clients.”

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IBM to integrate Databand with other recent acquisitions

Another relatively recent IBM acquisition, Instana, which was purchased in 2020, gave IBM software that provides businesses with the ability to manage the performance of complex cloud-native applications regardless of where they reside.

“By using with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations,” an IBM statement said.

This will include using Databand to alert engineers of missing data, then using Instana to explain where the missing data came from and produce a more complete view of the entire application infrastructure and data platform, which IBM says will “help organisations prevent lost revenue and reputation”.

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IBM says it will provide Databand with the resources to expand its observability capabilities and offer a broader range of options – across commercial and open source platforms.

“Our clients are data-driven enterprises who rely on high quality, trustworthy data to power their mission-critical processes. When they don’t have access to the data they need in any given moment, their business can grind to a halt,” said Daniel Hernandez, general manager for data and AI at IBM.

“With the addition of, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale.”

Read more: Post-Covid-19 flexibility driving IBM’s investments – UK CEO

Topics in this article: IBM

IBM收购了以色列数据观察初创企业Databand,交易金额未披露。该公司表示,这笔交易将有助于通过早期捕捉错误数据来改进机器学习模型。Databand成立于2018年,生产旨在帮助组织提高数据质量的软件。该公司表示,它通过在错误、管道故障和质量低劣的元素进入机器学习模型之前修复它们来做到这一点。这是IBM今年在人工智能和混合云领域的第五笔收购。其中包括1月份收购环境绩效管理数据和分析软件提供商Envizi,以及2月份收购微软Azure咨询公司Neudesic。IBM表示,其收购的目标是加强其在数据、人工智能和自动化领域的软件组合,以解决“全方位可观察性”问题。Gartner公司表示,根据该公司的研究,糟糕的数据每年给企业造成约1290万美元的损失。如果糟糕的数据输入到用于推动公司或产品方向的预测模型中,从长远来看可能会导致“糟糕的决策”。数据可观察性,就像Databand开发的平台,处理的是理解为什么数据集或管道没有执行您所期望的操作。“你无法保护你看不到的东西,当数据平台失效时,每个人都会受到影响——包括客户,”Databand联合创始人兼首席执行官乔希·贝纳姆(Josh Benamram)说。加入IBM将帮助我们扩大软件规模,并显著加快我们满足企业客户不断变化的需求的能力。”IBM最近的另一笔收购是在2020年收购的Instana,它为IBM提供了一种软件,让企业能够管理复杂的云本地应用程序的性能,无论它们位于何处。通过使用Databand”。IBM在一份声明中表示:“通过Instana APM和IBM Watson Studio的IBM Observability, IBM可以很好地解决IT运营的全光谱的可观察性。”这将包括使用Databand提醒工程师丢失数据,然后使用Instana解释丢失数据的来源,并生成整个应用基础设施和数据平台的更完整视图。IBM表示,这将“帮助组织防止收入和声誉的损失”。IBM表示,它将为Databand提供资源,以扩展其可观察性能力,并提供更广泛的选择——跨越商业和开源平台。“我们的客户是数据驱动型企业,他们依赖高质量、值得信赖的数据来推动关键任务流程。IBM数据和人工智能总经理丹尼尔•埃尔南德斯(Daniel Hernandez)表示:“当他们在任何时候都无法获得所需的数据时,他们的业务就会陷入停顿。加入了Databand。在人工智能方面,IBM为IT提供了最全面的跨应用程序、数据和机器学习的可观察能力,并继续为我们的客户和合作伙伴提供他们所需的技术,以交付可信的数据和大规模人工智能。”