Implementing SQL Data Warehouse (SSIS) training course imparts core skills on the implementation of data warehouse platform for supporting a BI solution. Participants enrolled for this SQL Data Warehouse certification will learn to create the data warehouse with Microsoft-sql-server-2016-training-certification">SQL Server 2016 and Azure SQL Data Warehouse. The course also covers the Implementation of ETL using Integration Services, validation and cleansing of data using Data Quality Services and Master Data Services.
Implementing SQL Data Warehouse course is ideal for database professionals, BI developers, and professionals who are responsible for creating BI solutions in an enterprise environment.
SSIS is an ETL tool that performs various operations like loading the data based on need, executes data related calculations and defines a workflow for the process and tasks.
There are three types of data warehouse:
Classroom Training*Duration : 5 Days
Fee : Online : $1,700 (1-on-1)†, London : £4,500 (1-on-1)†, Dubai : $2,600 , India : $1,800
Instructor-Led Online TrainingDuration : 5 Days
Fee : $1,700
Duration : 5 Days
Fee : On Request
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Give an edge to your career with Microsoft certification training courses. Students can join the classes for 20767: SSIS Training for Implementing a SQL 2016 Data Warehouse (SSIS) at Koenig Campus located at New Delhi, Bengaluru, Shimla, Goa, Dehradun, Dubai & Instructor-Led Online.
Microsoft SSIS (SQL Server Integration Services) is a business intelligence tool that is designed to make data migration easier. The main objective of SSIS is to analyze and cleanse data and run extract, transform and load (ETL) processes for data warehousing.
SSIS package configuration is referred to the settings that help us modify a property without opening the package. This is possible due to the fact that the configuration is stored somewhere outside the code that makes up the SSIS package.
Some of the prominent differences between SSIS and SSRS are:
An SQL Server Data Warehouse is a kind of central repository used for storing heterogeneous data related to the purposes of analysis and reporting. It consolidates, standardizes and organizes the data for better decision making.
There are 7 important steps that one follow to build a robust data warehouse:
A database is an organized collection of data. On the other hand, a data warehouse is a kind of database (or group of databases) created to store, filter, retrieve and analyze huge volumes of data. The basic approach these days is to store data from all the databases into a data warehouse which enables one time analysis and visualization on the complete bulk of data.
A data warehouse is a repository of large volume of operational and customer-related data imported from other databases. This ensures analysis of data in a more holistic way. For example, from a business point of few, a data warehouse might include customer information, website details, mailing lists, comment cards and employee information including time cards, demographic data and salary information.
The major benefits of a data warehouse include:
The features of a data warehouse include:
Data warehousing is applicable to a whole lot of sectors including banking, finance, consumer goods, government and education, healthcare, hospitality, insurance, services, telephone and transportation, among many others.
The data warehouse tools help build enterprise data solutions to fetch information from the data easily and quickly in the cloud. Here is a list of the most popular data warehouse tools: