Collibra
NOVEMBER 1, 2021
Gartner research predicts that by 2022, 75% of all databases will be deployed or migrated to the cloud. . But like any migration, cloud data migration is also fraught with problems, the top challenge being data quality. Achieving data quality during a cloud data migration.
Reltio
DECEMBER 2, 2020
Since we’ve been getting a lot of questions about how to successfully execute a master data migration, I invited Ranga Iyengar, our Vice President of Expert Services to provide answers. In the first two weeks we’ll review the legacy system, review any new requirements, and create a fit-gap analysis and implementation plan.
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AIIM
JUNE 8, 2021
If leaving your data in place is not an option, and moving it makes you lose sleep at night , you can quickly feel overwhelmed by the chaos. Thankfully, there are some new approaches to data migration that may provide an answer. Let's take a look at three common approaches to migration to compare them. Extensive Analysis.
The Last Watchdog
OCTOBER 23, 2023
Gonzalez Relying on data collection and organization tools like the traditional SIEM to analyze the various log data for threat detection requires constant updating of the analysis methods and, more importantly, puts the onus of observability onto the security engineer.
Collibra
NOVEMBER 29, 2022
Enable data engineers and DataOps engineers to deliver reliable and trusted data across the enterprise. Enable root cause investigation through lineage, time series analysis, and cross-metric anomaly detection. The focus is on upstream use cases of anomaly detection, pipeline monitoring, and data integration.
Collibra
MAY 26, 2022
Is it increasing operational efficiency or data migration efficiency? Data quality checks across data pipelines . Data masking. Lineage and time series analysis capabilities. Data discovery and rule enforcement. Cut costs: Accelerate cloud data migrations. A unified DQ scoring system .
erwin
OCTOBER 8, 2020
These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.
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