Data wrangling, dataops, data prep, data integration—whatever your organization calls it, managing the operations to integrate and cleanse data is labor intensive. Many businesses struggle to integrate new data sets efficiently, improve data quality, centralize master data records, and create cleansed customer data profiles.
Dataops isn’t a new challenge, but the stakes are higher as more companies want to become data-driven organizations and leverage analytics as a competitive advantage. Digital trailblazers are also extending dataops into unstructured data sources to build AI search capabilities and prep data for use in large language models.
