July 7, 2022
Data observability tools are designed to troubleshoot and resolve data quality issues in near real-time. IBM pointed to recent Gartner research which found that poor data quality costs the average enterprise $12.9 million. Poor data quality results in executives making bad decisions, which can impact revenues and profits.
Reconciling data quality issues is becoming increasingly important to organizations. Gartner has forecast that 70% of organizations this year will track data quality using metrics to improve it by 60%. IBM sees data observability as the gathering of data workload and pipeline trends at the source to discover discrepancies.
IBM’s Mike Gilfix
“Data observability takes traditional data operations to the next level by using historical trends to compute statistics about data workloads and data pipelines directly at the source, determining if they are working, and pinpointing where any problems may exist,” according to a blog post by Mike Gilfix, IBM’s data and AI VP of product management.
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IBM will combine Databand with its Observability by Instana APM and Watson Studio to create a full stack observability offering. IBM acquired application performance monitoring (APM) provider Instana in 2020. “Databand.ai will be a core component of observability use case alongside IBM Observability by Instana APM and Watson Studio on IBM Cloud Pak for Data,” Gilfix noted.
IBM’s Daniel Hernandez
Together, IBM is positioning the the tools to help organizations reconcile issues. “Combined with full stack, data observability determines the source of problems ranging from infrastructure, applications, data and machine learning platforms,” Daniel Hernandez, general manager for data and AI at IBM, said in a statement.
IBM’s 2022 Focus on AI and Automation
Futurum Research analyst Daniel Newman weighed in on the IBM deal on Thursday. Newman recalled an October investor briefing when IBM CEO Arvind Krishna underscored AI and automation as a key 2022 focus.
Futurum’s Daniel Newman
“Data observability and AI, a market that is on the precipice of huge growth, gives organizations a competitive advantage,” Newman said. “It makes sense that IBM would continue to add to its portfolio suite to meet the needs of its customers.”
IBM will provide the Databand platform as a SaaS offering, or as a hosted subscription service. IBM’s Gilfix said the company will extend Databand.ai to its data fabric architecture. While customers can use Databand independently, Gilfix, IBM is recommending that they use it in conjunction with a complete data fabric architecture to automate the data lifecycle. Besides data observability, Gilfix noted that customers can use Databand for multi-cloud data integration, data governance and privacy, customer 360, and MLOps and trustworthy AI.
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