Data center News
IBM Goes Big On Data Observability With Databand.ai Acquisition
Joseph F. Kovar
IBM expects that Databand.ai, along with IBM Observability by Instana APM and IBM Watson Studio, will help position IBM to address the full spectrum of IT data observability to find bad data issues and resolve them before they impact a customer’s operations.
IBM Wednesday unveiled the purchase of Databand.ai, an Israel-based developer of a proactive data observability platform, which claims to catch bad data before it impacts a customer’s business.
Financial details of the acquisition, which actually closed June 27, were not disclosed by IBM.
The term “data observability,” as defined by Databand.ai, is the blanket term for understanding the health and the state of data in a system that allows a business to identify, troubleshoot, and resolve data issues in near real-time.
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 expects 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.
IBM, citing Gartner, said that poor data quality costs organizations an average of $12.9 million every year while increasing the complexity of data ecosystems and leading to poor decision making.
That makes this an exciting acquisition, said Mike Gilfix, vice president of product management for data and AI at IBM.
“Bad data is expensive,” Gilfix told CRN. “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.”
Databand.ai is part of a three-legged way to bring observability to businesses, Gilfix said.
Databand.ai is focused on data observability, and is important to ensuring that data pipelines work as promised, he said.
The second leg is IBM Observability by Instana APM, which IBM acquired in late 2020. Instana brings observability specifically to applications by observing the makeup of the application and the performance of the app itself, he said.
The third is IBM Watson Studio, which brings observability to AI models, he said.
For IBM, Databand.ai is also an important component in a data fabric, which Gilfix defined as an architectural approach that enables consumers of data including engineers to access data, discover it, catch it, build data pipelines, and protect data across multiple data silos, Gilfix said.
“Many companies struggle with data silos,” he said. “A data fabric is a good way to connect those silos together.”
IBM’s channel partners are an important part of the company’s observability business, and the way they sell Databand.ai will be no different once it is integrated, Gilfix said.
“The channel is a big part of our business,” he said. “We believe a rich ecosystem is critical. Partners add expertise, make sure customers are successful, and bring in their own value adds to be even more successful.”