Data Warehouse & Power BI For Beginners -DW ,SSIS, ETL, BI

Data Warehouse & Power BI For Beginners -DW ,SSIS, ETL, BI, available at $59.99, has an average rating of 3.75, with 93 lectures, based on 90 reviews, and has 6407 subscribers.

You will learn about Describe the key elements of a data warehousing solution Describe the main hardware considerations for building a data warehouse Implement a logical design for a data warehouse Implement a physical design for a data warehouse Create columnstore indexes Implementing a MS SQL Server Data Warehouse Describe the key features of SSIS Implement a data flow by using SSIS Implement control flow by using tasks and precedence constraints Create dynamic packages that include variables and parameters Debug SSIS packages Describe the considerations for implement an ETL solution Implement Data Quality Services Deploy SSIS projects Implement a Master Data Services model Describe how you can use custom components to extend SSIS Describe BI and common BI scenarios Create a data warehouse with Microsoft SQL Server Implement ETL with SQL Server Integration Services validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services. This course is ideal for individuals who are Database professionals or Business Analyst professionals or Data Engineering professionals It is particularly useful for Database professionals or Business Analyst professionals or Data Engineering professionals.

Enroll now: Data Warehouse & Power BI For Beginners -DW ,SSIS, ETL, BI

Summary

Title: Data Warehouse & Power BI For Beginners -DW ,SSIS, ETL, BI

Price: $59.99

Average Rating: 3.75

Number of Lectures: 93

Number of Published Lectures: 93

Number of Curriculum Items: 93

Number of Published Curriculum Objects: 93

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Describe the key elements of a data warehousing solution
Describe the main hardware considerations for building a data warehouse
Implement a logical design for a data warehouse
Implement a physical design for a data warehouse
Create columnstore indexes
Implementing a MS SQL Server Data Warehouse
Describe the key features of SSIS
Implement a data flow by using SSIS
Implement control flow by using tasks and precedence constraints
Create dynamic packages that include variables and parameters
Debug SSIS packages
Describe the considerations for implement an ETL solution
Implement Data Quality Services
Deploy SSIS projects
Implement a Master Data Services model
Describe how you can use custom components to extend SSIS
Describe BI and common BI scenarios
Create a data warehouse with Microsoft SQL Server
Implement ETL with SQL Server Integration Services
validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

Who Should Attend

Database professionals
Business Analyst professionals
Data Engineering professionals

Target Audiences

Database professionals
Business Analyst professionals
Data Engineering professionals

A data warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. Data warehouses are intended to perform queries and analysis and often contain large amounts of historical data. The data within a data warehouse is usually derived from a wide range of sources such as application log files and transaction applications.

A data warehouse centralizes and consolidates large amounts of data from multiple sources. Its analytical capabilities allow organizations to derive valuable business insights from their data to improve decision-making. Over time, it builds a historical record that can be invaluable to data scientists and business analysts. Because of these capabilities, a data warehouse can be considered an organization’s “single source of truth.”

Data warehouses offer the overarching and unique benefit of allowing organizations to analyze large amounts of variant data and extract significant value from it, as well as to keep a historical record.

A typical data warehouse often includes the following elements:

A relational database to store and manage data
An extraction, loading, and transformation (ELT) solution for preparing the data for analysis
Statistical analysis, reporting, and data mining capabilities
Client analysis tools for visualizing and presenting data to business users
Other, more sophisticated analytical applications that generate actionable information by applying data science and artificial intelligence (AI) algorithms, or graph and spatial features that enable more kinds of analysis of data at scale.

Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights. Your data may be an Excel spreadsheet, or a collection of cloud-based and on-premises hybrid data warehouses. Power BI lets you easily connect to your data sources, visualize and discover what’s important, and share that with anyone or everyone you want.

Power BI consists of several elements that all work together, starting with these three basics:

A Windows desktop application called Power BI Desktop.
An online SaaS (Software as a Service) service called the Power BI service.
Power BI mobile apps for Windows, iOS, and Android devices.

Course Curriculum

Chapter 1: Microsoft SQL Server Setup

Lecture 1: Introduction

Lecture 2: Please Read

Lecture 3: What is SQL Server

Lecture 4: SQL Server Editions

Lecture 5: Hardware | Software Requirements

Lecture 6: SQL Server Download

Lecture 7: SQL Server Installation

Lecture 8: Install SSMS

Lecture 9: SQL Server Configuration Manager

Lecture 10: Connecting SSMS to SQL Server

Lecture 11: Database Concepts

Chapter 2: Installing Sample Databases

Lecture 1: Installing Adventureworks 2014

Lecture 2: Installing Adventureworks 2016

Lecture 3: Installing AdventureworksDW 2016

Lecture 4: Installing World Wide Importers

Lecture 5: Installing World Wide ImportersDW

Lecture 6: SQL Server Data Files

Chapter 3: Microsoft Visual Studio Setup

Lecture 1: What is Visual Studio

Lecture 2: Minimum Installation Requirements

Lecture 3: Installing Visual Studio

Lecture 4: visual Studio workloads

Lecture 5: Install SQL Server Data Tools

Lecture 6: Installing SSDT Templates

Chapter 4: Introduction to Data Warehousing

Lecture 1: What is Data Warehouse

Lecture 2: Data Warehouse vs Enterprise Data Warehouse

Lecture 3: Data Warehouse Vs Database

Chapter 5: Data Warehouse Requirements

Lecture 1: Hardware Requirements

Lecture 2: Enabling SQL Server Agent

Lecture 3: Database Configurations

Lecture 4: FTDW Sizing Tool ( Already Downloaded)

Lecture 5: FTDW Sizing Tool

Chapter 6: Designing a Data Warehouse

Lecture 1: Logical Design of Data Warehouse

Lecture 2: Physical Design of Data Warehouse – Part 1

Lecture 3: Physical Design of Data Warehouse -Part 2

Lecture 4: Designing Dimension Tables

Chapter 7: Creating an ETL Solution

Lecture 1: What is ETL

Lecture 2: What is SSIS

Lecture 3: Introduction to ETL with SSIS

Lecture 4: Creating a new SSIS Project

Lecture 5: Exploring Source Data : Part 1

Lecture 6: Exploring Source Data : Part 2

Chapter 8: Implementing Control Flow & Data flow in an SSIS Package

Lecture 1: Introduction to control flow: Part 1

Lecture 2: Introduction to control flow: Part 2

Lecture 3: Implementing data flow – Part 1

Lecture 4: Implementing data flow – Part 2

Chapter 9: Debugging and Troubleshooting SSIS Packages

Lecture 1: Debugging SSIS Package : Part 1

Lecture 2: Debugging SSIS Package : Part 2

Lecture 3: Logging SSIS Package Events

Lecture 4: Handling errors in an SSIS Package

Chapter 10: Implementing an Incremental ETL Process

Lecture 1: Introduction to incremental ETL Process

Lecture 2: Extracting modified data: Part 1

Lecture 3: Extracting modified data: Part 2

Lecture 4: Extracting modified data: Part 3

Lecture 5: Extracting modified data: Part 4

Lecture 6: Loading modified data: Part 1

Lecture 7: Loading modified data: Part 2

Lecture 8: Working with changing dimensions

Chapter 11: Deploying and Configuring SSIS Packages

Lecture 1: Integration services catalogs

Lecture 2: Deploying SSIS Solutions

Lecture 3: Execute a package with SQL Server Agent

Lecture 4: Configuring advanced SSIS Settings

Chapter 12: Enforcing Data Quality in Data Warehouse

Lecture 1: Installing Data Quality Services

Lecture 2: Cleansing data with data quality services

Lecture 3: Find duplicate data : Part 1

Lecture 4: Find duplicate data : Part 2

Lecture 5: Using data quality services in SSIS data flow

Chapter 13: Consuming Data in a Data Warehouse

Lecture 1: Introduction to Business Intelligence

Lecture 2: Creating a new SSRS Project in VS 2019

Lecture 3: Using SSRS in Data Warehouse: Part 1

Lecture 4: Using SSRS in Data Warehouse: Part 2

Lecture 5: Creating a new SSAS Project

Lecture 6: Data Analysis with SSAS : Part 1

Lecture 7: Data Analysis with SSAS : Part 2

Chapter 14: Microsoft Power BI Setup

Lecture 1: Office 365 Setup

Lecture 2: What is Power BI

Lecture 3: What is Power BI Desktop

Lecture 4: Installing Power BI Desktop

Lecture 5: Power BI Desktop Tour

Chapter 15: Power BI Overview

Lecture 1: Power BI Overview : Part 1

Lecture 2: Power BI Overview : Part 2

Lecture 3: Power BI Overview : Part 3

Lecture 4: Components of Power BI

Lecture 5: Building blocks of Power BI

Lecture 6: Exploring Power BI Desktop Interface

Lecture 7: Exploring Power BI Service

Instructors

Bluelime Learning Solutions
Making Learning Simple

Rating Distribution

1 stars: 3 votes
2 stars: 3 votes
3 stars: 16 votes
4 stars: 28 votes
5 stars: 40 votes

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