IBM acquires Databand for data monitoring technology

IBM expanded its data structure platform with the acquisition of data monitoring startup Databand on Wednesday.

Financial terms of the deal were not disclosed.

Databand, founded in 2018 and based in Tel Aviv, raised $14.5 million in funding to build its data monitoring technology that provides organizations with visibility and monitoring for data pipelines, which can be used for training in machine learning, data analysis and business intelligence.

Databand – formerly known as Databand.ai – is the second observability vendor that IBM has acquired in as many years, after monitoring app vendor Instana in November 2020

The data monitoring market is highly competitive with multiple vendors all looking to grow, esp Monte Carlo, which grossed $135 million in May and startup Bigeye.

There is a growing need for data monitoring, according to Paige Bartley, an analyst at 451 Research at S&P Global Market Intelligence. Data is increasingly used by less technical workers in enterprise settings, and so enterprises need more data monitoring tools to maintain access to quality data.

“While periodic, cyclical efforts to clean up individual data sets will still be necessary in certain cases, data monitoring efforts offer a more proactive and real-time approach to maintaining the data pipeline, helping to ensure ongoing data flow with a high degree of integrity across the organization,” Bartley said.

Data monitoring technology today is most often closely related to data reliability and data quality assurance applications. According to Bartley, data monitoring technology has room to grow to be more widely used for other key business purposes, such as optimizing the cost of data systems and the cost and allocation of cloud resources.

Why IBM needs data monitoring to enable its data structure

Databand will fit in IBM Data Platformwhich enables the organization to manage and use data for analytics, BI and machine learning.

The data platform helps organizations connect data consumers wherever the data resides, whether on-premises or in the cloud, said Michael Gilfix, vice president of data product management at IBM.

An example of a typical application that Databand will now enable for IBM users is to ensure that the BI dashboard is accurate and up-to-date.

A BI dashboard is typically powered by a data feed that takes data from various sources. Databand technology can detect if the data is inaccurate or if something has gone wrong in the process that affects the data. Databand alerts users to the error and identifies its source so it can be corrected.

The intersection of data observability and data quality

The IBM Data Platform now includes IBM Watson Knowledge Catalogwhich provides data management and data catalog capabilities to enable users to identify and use data for training machine learning or data analysis.

The Watson Knowledge Catalog allows organizations to create rules about how data is used and then provides capabilities to enforce those rules. The combination of the data catalog and Databand technology in the data structure will provide better data quality, according to Gilfix.

Databand technology provides visibility into data generation across the pipeline. This visibility into how data is created will help improve the quality of data that organizations catalog and use, Gilfix said.

“Data observability will help people trust that the data that comes from different parts of the organization is reliable,” he said.

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