Microsoft/Azure SQL Data Warehouse Performance Tuning and Optimization


Microsoft Azure Training Overview

SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that utilizations Massively Parallel Processing (MPP) to immediately run complex questions crosswise over petabytes of information. Use SQL Data Warehouse as a key part of a major information arrangement. Import enormous information into SQL Data Warehouse with straightforward PolyBase T-SQL questions, and afterward utilize the intensity of MPP to run elite investigation. As you coordinate and break down, the information distribution center will turn into the single variant of truth your business can depend on for bits of knowledge. Audience : IT experts who are keen on getting an Azure accreditation Those hoping to execute information streams inside their associations  
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Azure SQL Certification Course schedule & Prices

Course Details Schedule
Live Virtual Classroom (Instructor-Led)
Duration : 2 Days (4 Days for 4 Hours/Day)
Fee : 700 (Includes Taxes) 
9 AM - 5 PM (Flexible Time Slots for 4 hours option)








Client's Location
As per mutual convenience
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
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Course Prerequisites

Course Pre-requisites: A fundamental comprehension of information streams and their employments  

After completion this course, you will learn following topics: Describe the key components of an information warehousing arrangement Describe the fundamental equipment contemplations for building an information stockroom Implement a coherent structure for an information distribution center Implement a physical structure for an information stockroom Create columnstore records Implementing an Azure SQL Data Warehouse Describe the key highlights of SSIS Implement an information stream by utilizing SSIS Implement control stream by utilizing errands and priority imperatives Create dynamic bundles that incorporate factors and parameters Debug SSIS bundles Describe the contemplations for actualize an ETL arrangement Implement Data Quality Services Implement a Master Data Services model Describe how you can utilize custom parts to expand SSIS Deploy SSIS ventures Describe BI and normal BI situations