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Linkedin - Using AI to Improve Ops for Your Data Organization - Printable Version

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Linkedin - Using AI to Improve Ops for Your Data Organization - AD-TEAM - 09-10-2024

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108.09 MB | 00:04:24 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
01 - Transformational change for your data organization (4.14 MB)
02 - Introduction to DataOps and the benefits of using AI tools to enhance operations (7.17 MB)
01 - Identify and prioritize your organization's data (5.87 MB)
02 - How AI can be used to discover, catalog, and understand your data sources (9.94 MB)
03 - Automate data cataloging and classification using Collibra Data Intelligence Platform (12.11 MB)
04 - Risks and controls for consideration (6.21 MB)
01 - Introduction to data quality monitoring and traditional methods (3.75 MB)
02 - Enhance the quality of streaming data pipelines using AI and stream monitoring tools (2.95 MB)
03 - Enhance the quality of batch processing pipelines using AI (4.29 MB)
04 - Demonstration of AWS Glue data quality (3.52 MB)
05 - Enhance the quality of structured and unstructured data using AI (2.71 MB)
07 - What to know before implementing AI for data quality automation (3.49 MB)
01 - The power of data analytics, business intelligence tools, and AI (3.83 MB)
02 - Demonstration of pattern recognition and predictive analytics using Power BI (7.47 MB)
03 - Demonstration of automating anomaly detection and root cause suggestion using Power BI (4.92 MB)
04 - Demonstration of automating sentiment analysis with Power BI (3.57 MB)
05 - Forecasting time-series data using Power BI (4.04 MB)
06 - Talk to your data using AI (2.86 MB)
07 - Risks of using AI for data analytics and mitigating controls (9.63 MB)
01 - Extending AI in your data operations (5.53 MB)
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