Organizations must conduct a data audit as part of their approach to data intelligence. This step is especially crucial for enterprises without formalized data structures or a data team/partner – however, all organizations can benefit from ongoing or regularly scheduled audits. The average organization receives data from 400 sources, with 20% of organizations drawing from 1,000-plus data sources. Understanding this disarray is the first step to correcting it.
During this process, leaders will develop an indonesia whatsapp number data understanding of existing organizational data governance and hygiene practices. They must use this understanding to establish a formalized data management framework, using current stumbling blocks as a guiding light. For example, if an organization struggles to understand its data governance, including data provenance and meaning, it’s likely too early to consider DataOps strategies. For reference, 60% of data leaders indicate that governance remains their organization’s top priority.
These steps lay the groundwork for a robust data management strategy. However, data intelligence requires more than management. To truly unlock meaning from data in motion, leaders must deploy leading data integration and quality tools, including master data management (MDM) solutions.