The survey associated with this report, commission by Immuta, focused on identifying the limiting factors in the data “supply chain” as it relates to the overall DataOps methodology of the organization. DataOps itself is the more agile and automated application of data management techniques to advance data-driven outcomes, while the data supply chain represents the technological steps and human-involved processes supporting the flow of data through the organization, from its source, through transformation and integration, all the way to the point of consumption or analysis.
DataOps Dilemma: Survey Reveals Gap in the Data Supply Chain
The survey associated with this report, commission by Immuta, focused on identifying the limiting factors in the data “supply chain” as it relates to the overall DataOps methodology of the organization. DataOps itself is the more agile and automated application of data management techniques to advance data-driven outcomes, while the data supply chain represents the technological steps and human-involved processes supporting the flow of data through the organization, from its source, through transformation and integration, all the way to the point of consumption or analysis.
Data Engineering Survey: 2021 Impact Report
This Data Engineering Survey: 2021 Impact Report summarizes key findings from the inaugural survey and provides a glimpse into the current and future state of data engineering and DataOps. The report highlights some of the major trends uncovered in this year’s survey including the adoption of cloud data platforms, what platforms are winning (and emerging), what data engineers find to be their biggest challenges, and how organizations are handling sensitive data.
Data Engineering Survey: 2021 Impact Report
This Data Engineering Survey: 2021 Impact Report summarizes key findings from the inaugural survey and provides a glimpse into the current and future state of data engineering and DataOps. The report highlights some of the major trends uncovered in this year’s survey including the adoption of cloud data platforms, what platforms are winning (and emerging), what data engineers find to be their biggest challenges, and how organizations are handling sensitive data.