IBM has written a cheque for Databand.ai, an Israel-based developer of a data observability platform, which claims to catch bad data before it impacts a customer’s business.
IBM’s cunning plan is to use Databand.ai to strengthen its data, AI, and automation software portfolio to ensure trustworthy data goes to the right user at the right time. The company also expects the acquisition to help Databand.ai take advantage of IBM’s own R&D investments and other IBM acquisitions.
Observability helps not only describe a problem for engineers, but also provides the context to resolve the problem and look at ways to prevent the error from happening again, according to Databand.ai.
“The way to achieve this is to pull best practices from DevOps and apply them to Data Operations. All of that to say, data observability is the natural evolution of the data quality movement, and it’s making DataOps as a practice possible”, the company said.
IBM, citing Gartner, said that poor data quality costs organisations an average of $12.9 million every year while increasing the complexity of data ecosystems and leading to poor decision making.
IBM vice president of product management for data and AI Mike Gilfix said that bad data was expensive.
“We’re excited about the fast-growing data observability market. We know when data stops, companies lose business. If you depend on data to run your company, and that data is corrupt or has other issues, we want Databand.ai to help find the issues and resolve them faster.”
IBM’s indirect channel partners are an important part of the company’s observability business, and Databand.ai will be no different once it is integrated, Gilfix said.
