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Logical and Physical Modeling for Analytical Applications

Logical and Physical Modeling for Analytical Applications crack

A bad data model leads to an application that does not perform well. Therefore, when developing an application, you should create a good data model from the start. However, even the best logical model can’t help when the physical implementation is bad. It is also important to know how SQL Server stores and accesses data, and how to optimize the data access. Database optimization starts by splitting transactional and analytical applications. In this course, you learn how to support analytical applications with logical design, get understanding of the problems with data access for queries that deal with large amounts of data, and learn about SQL Server optimizations that help solving these problems.

 

Logical and Physical Modeling for Analytical ApplicationsStar and Snowflake Schemask
00:20:19
Introduction
02:43
Normalized Schema
03:51
Star Schema
02:29
Shared Dimensions
00:36
Dimension Denormalization
00:42
Snowflake Schema
00:52
Hybrid Approach
01:14
Granularity
02:03
Auditing Lineage
01:39
DWTerms
02:59
Summary
01:11
Logical and Physical Modeling for Analytical ApplicationsDesigning Dimensions and Fact Tables
00:38:19
Introduction
00:53
Dimension Columns
02:27
Hierarchies
02:14
SCD Classic
03:15
Referencing Monster
02:38
SCD Custom
02:24
Demo Dimensions
05:45
Fact Columns
01:30
Measures Additivity
02:51
Demo Fact
02:53
MtoM
03:21
Demo MtoM
07:10
Summary
00:58
Logical and Physical Modeling for Analytical ApplicationsData Warehousing Data Access Problems
00:21:49
Introduction
01:40
Algorithms Complexity
01:51
SSAS Addressing
02:34
Joins
02:32
Linearize Joins
01:38
Bitmap
01:04
Bloom
03:28
Trans-Relational
01:30
Columnar Storage
03:54
Summary
01:38
Logical and Physical Modeling for Analytical ApplicationsSQL Server Data Warehousing Support before Version 2012
00:33:18
Introduction
01:05
Partitioned Table
03:10
Sliding Window
04:26
Demo Partitioning
05:45
Filtered Index
01:39
Indexed View
02:14
Demo Filtered Indexed
06:34
Data Compression
05:20
Demo Data Compression
01:57
Summary
01:08
Logical and Physical Modeling for Analytical ApplicationsSql Server Data Warehousing Optimizations in Version 2012
00:34:01
Introduction
00:56
Window Functions
02:48
Demo Window Fun
04:45
Columnstore Indexes
01:19
Columnstore Compression
02:48
Reducing IO
01:36
Reducing CPU Batch
03:22
Columnstore Restrictions
02:56
Data Loading Usage
02:40
Demo Columnstore Batch
07:26
Version 2014 Summary
03:25

یک برنامه خوب نیاز به یک دیتابیس خوب نیز دارد.برای پایگاه داده ای که با حجم انبوهی از اطلاعات سروکار دارد، یک طراحی حرفه ای و بهینه الزامی است.مسلما هرچه دیتابیس بهینه تر و حرفه ای تر طراحی شده باشد، علاوه بر سرعت پاسخگویی بیشتر، استفاده از منابع سخت افزاری را کمتر می کند.

در این دوره شما نحوه پیاده سازی فیزیکی و منطقی پایگاه داده های SQL SERVER و همچنین تحلیل اپلیکیشن ها و کوئری های اس کیو ال سرور را می آموزید.

این مجموعه آموزشی (Logical and Physical Modeling for Analytical Applications) توسط موسسه آموزشیPluralSight  در سطح متوسط و مدت زمان 2 ساعت و 27 ارائه شده است.

برخی عناوین مطرح شده در این مجموعه:

  • ابعاد Denormalization
  • رویکرد ترکیبی
  • طراحی ابعاد و جداول واقعی
  • سلسله مراتب
  • کلاسیک SCD
  • نمونه پروژه MTOM
  • پیچیدگی الگوریتم
  • Bitmap
  • Bloom
  • پنجره کشویی
  • پارتیشن بندی
  • ایندکس فیلتر شده
  • فشرده سازی داده ها
  • قسمت بندی جدول
  • شاخص Columnstore
  • فشرده سازی Columnstore
  • کاهش IO
  • محدودیت Columnstore
  • و…
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