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We're here to help you find itAdvanced Data Vault Modeling Course Overview
The Advanced Data Vault Modeling course is a comprehensive program designed to enhance the skills of data professionals in building scalable and flexible data warehousing solutions using the Data Vault 2.0 methodology. This course covers a range of topics from Event modeling, Context array impacts on satellite design, to deploying architectures for big data, cloud, and streaming platforms.
Learners will explore Advanced link design, Address modeling, and strategies for managing Personally Identifiable Information (PII) within a data warehouse. The course delves into techniques for dealing with the lack of an Enterprise Key, Integration challenges, and Alternate key strategies. It also provides insights into Automation best practices for Data Vault modeling.
By completing this data vault training, students will gain expertise in the latest data vault 2.0 training practices, positioning themselves at the forefront of data warehousing design and implementation. Each module is packed with lessons that are critical for mastering the Data Vault 2.0 standard, ensuring learners are well-equipped to tackle complex Data integration and warehousing challenges.
Purchase This Course
USD
View Fees Breakdown
Flexi Video | 16,449 |
Official E-coursebook | |
Exam Voucher (optional) | |
Hands-On-Labs2 | 4,159 |
+ GST 18% | 4,259 |
Total Fees (without exam & Labs) |
22,359 (INR) |
Total Fees (with exam & Labs) |
28,359 (INR) |
♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
The Advanced Data Vault Modeling course is tailored for IT professionals focused on next-level data warehouse modeling techniques.
Target Audience Includes:
Gain expertise in advanced Data Vault modeling techniques for handling complex data warehousing challenges, including big data, cloud deployments, streaming data, and integrating disparate systems with privacy concerns.