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Why did IBM acquire Databand.ai?
Why did IBM acquire Databand.ai?

Why did IBM acquire Databand.ai?

Financial details of the deal were not disclosed

Published Updated

Key takeaways

  • IBM has acquired Databand.ai to enhance its data observability capabilities within its Data and AI division.
  • Databand.ai provides software that helps organisations identify and resolve data issues before they affect performance.
  • The acquisition aligns with IBM's strategy of expanding its portfolio, having acquired over 25 companies since 2020.
  • Databand.ai's platform centralises alerting and incident management for data engineers, improving data health standards.
  • The financial details of the acquisition have not been disclosed, maintaining confidentiality around the transaction.
5 min

Since Arvind Krishna took charge of IBM in 2020, the tech giant has acquired more than 25 companies. This year alone, the company has added five more names to its kitty, with the latest acquisition being Databand.ai. Databand.ai is a provider of data observability software that helps organisations address challenges such as errors, pipeline failures and poor quality, before they impact their bottom line.  

Databand.ai is headquartered in Tel Aviv, Israel and will join IBM Data and AI. IBM did not reveal the financial details of the transaction. Using Databand.ai with IBM Observability (by Instana APM) and IBM Watson, IBM will be able to address data observability applications across IT operations.

What is in for IBM

Databand.ai was co-founded by Josh Benamram, Victor Shafran and Evgeny Shulman in 2018. The firm says that the main service its products provide is to help data engineers scale their infrastructure while maintaining data health standards enabling organisations to build better data products.

In 2020, the company raised $14.5million in a Series A funding round led by Accel Partners, with participation from earlier investors Blumberg Capital, Lerer Hippeau, Ubiquity Ventures, Differential Ventures, F2, and Bessemer Venture Partners. 

Offerings

  • Observability platform-The data observability platform provides a central place to define and receive alerts around data incidents. One can detect, alert, and resolve incidents without jumping from screen to screen. The user can profile all alerts under one roof across your entire data stack and create customer alerts on incidents like missed data deliveries, unexpected schema changes, and anomalies in column-level statistics.
  •  Open Core-It is a core part of the firm's DataOps platform, which helps the user to track data quality information, monitor pipeline health, and automate advanced DataOps processes. The company says that it has kept the library open source to provide users control over how data is tracked and enable users to build custom extensions for different kinds of requirements.

With this acquisition, Databand.ai will be able to expand its observability capabilities for wider integration across other open-source and commercial solutions to power modern data stacks. Enterprises could now run Databand.ai as-a-Service (SaaS) or offer a self-hosted software subscription.

Databand.ai and IBM Instana could provide a complete and explainable view of the infrastructure and data platform system, helping teams to avoid loss of revenue and reputation.

Data observability solutions are a key part of IBM's broader data strategy and architecture – with Databand.ai on board, it will ensure that through IBM's existing solutions, only the "most accurate and trustworthy data is being put into the right hands at the right time – no matter where it resides."

What is data observability?

"Data observability" refers to understanding the health and the state of data in the system. It covers a range of activities and technologies which helps the user to identify, troubleshoot, and resolve data issues in near real-time.

Data observability provides context to enable the engineer to resolve the problem and start conversations to prevent that type of error from further occurring. "Data observability is the natural evolution of the data quality movement, and it's making DataOps as a practice possible," Databand.ai states.

IBM's strong focus on AI and Cloud

Some of the most prominent acquisitions made by IBM are:

  • Envizi- Just at the beginning of the year, IBM acquired Envizi, a data and analytics software provider for environmental performance management. Envizi's software automates the collection and consolidation of over 500 data types and also major sustainability reporting frameworks.
  • Sentaca- In February, it acquired Sentaca, a telco consulting services and solutions provider. The firm will accelerate IBM's hybrid cloud consulting business that will add skills to help communications service providers (CSPs) and media giants modernise on multiple cloud platforms and innovate.
  • Its second acquisition in February was Neudesic, a U.S. cloud services consultancy specialising primarily in the Microsoft Azure platform. As per IBM, this acquisition was to expand the company's portfolio of hybrid multi cloud services and further advance the company's hybrid cloud and AI strategy. 
  • Last month IBM announced plans to acquire Randori, an attack surface management (ASM) and offensive cybersecurity provider. Randori helps clients continuously identify external facing assets, on-premise or in the cloud and prioritise exposures which pose the greatest risk. 
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