The ADF (Azure Data Factory) and Power BI combo refers to the integration of Microsoft’s Azure Data Factory, a cloud-based data integration service, with Power BI, a business intelligence and data visualization tool. This combo is highly valuable for organizations seeking to streamline data integration processes, centralize data management, and derive actionable insights from their data. It ensures that data is efficiently moved, transformed, and visualized, facilitating data-driven decision-making and business intelligence.
ADF & POWER BI COMBO Training in Pune/ Online
SQL +Azure Data Factory & Power BI
Duration of Training : 4 months
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
COURSE CONTENT :
For whom SQL is? :
IT or NON IT people can easily enter into leading Database Technology which is commonly used for all domain application software as back-end. There are so many reason to go ahead :
WEEK-01 :
Oracle 12c SQL :
SQL Basic
[1] Introduction to Oracle DB 12c
Oracle Database 12c: Focus Areas, Fusion Middle-ware, Oracle Cloud, Services, Deployment Methods, RDBMS, Data Model, ER Diagram, Relation DB Terminology, SQL Statements and Development Environment, HR Schema Tables, DB Documentation.
[2] Retrieving Data using SQL SELECT statement
Basic Select Statement, Arithmetic Expression, Defining Null values, Concatenation Operator & Literal, Duplicate Rows, Displaying table structure. Practice Overview.
[3] Restricting & Sorting Data
Use of Where clause, Character Strings & Date Data, Comparison, Logical, Range, Pattern, & Other operators, Rules Precedence, Order By Clause, Substitution variables. Practice Overview
WEEK-02 :
[4] Single Row Function & Customized Output
SQL function, Single Row Function, Character/Case Functions, Number Functions, Nesting Function, Date Functions etc. Practice Overview.
[5] Conversion & Conditional Expressions
Conversion Function, Implicit/Explicit Data Conversion, General Function with covering NVL, NVL2, NULLIF, COALESCE, Conditional Expression with Decode function and Case Expression. Practice Overview.
[6] Reporting Aggregated Data using Group Function
Usages of Group function, Nesting Group Function, Creating Group Data, Restricting group data using Having Clause. Practice Overview.
[7] Displaying Data from Multiple Tables using Join
Type of Joins, Explaining with Natural Join, Using Clause, On Clause, SQL 99 Syntax, Three-Way Join, Self Join, NonEqui Join, Inner Versus Outer Join, Cross Join etc. Practice overview.
WEEK-03 :
[8] Using Sub-queries to solve queries
Scenario to use Sub-query, Rules for Sub-queries, Type of Sub-queries, Single Row Sub-queries and Multi Row Sub-queries. Null value in Sub-query etc. Practice Overview.
SQL Advanced :
[9] Using Set Operator
Set Operator Rules, Covering Set Operator as UNION, UNION ALL, INTERSECT, MINUS etc. Practice Overview.
[10] Managing Tables using DML Statements
Data Manipulation Language, Covering INSERT, UPDATE, DELETE & DB Transaction control using COMMIT, ROLLBACK, SAVEPOINT. Use of For update clause in SELECT Statement.
[11] Introduction to Data Definition Language
Database Object, Naming Rules, Various Data Types, CREATE TABLE statement, Constraint guidelines, Defining constraints as NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY & CHECK etc. ALTER TABLE, DROP TABLE Statement. Create Table using Sub-query. Practice Overview.
WEEK-04 :
[12] Introduction to Data Dictionary Views
Data Dictionary Structure, How to use Data Dictionary, USER_OBJECTS, ALL_OBJECT, USER_CONSTRAININTS. TABLE Information, Column Information etc. Practice overview.
[13] Creating Sequence, Synonyms & Indexes
Importance of Sequence, Synonyms & Indexes. Defining Sequence, Synonyms & Indexes & DROP statement etc. Practice overview.
[14] Creating Views
What’s View? Advantage of Views, CREATE Simple & Complex views, Rules for performing DML operation on views. Modifying & Removing a view etc. Practice Overview.
[15] Retrieving Data by using Sub-Query
Multiple Column Sub-query, Column Comparison, Pair & Non Pair Sub-queries, Scalar Sub queries, Co-related Sub-queries, Use of WITH clause. Practice Overview.
COURSE SUMMARY :
This Certification course has been designed by our certified professional for Beginners’ and Professionals. Want to become the master in Azure data Factory and would like to certify. This is a Real-time scenario based certification and Industry Endorsed course. A cloud-based data integration service allows creating data-driven workflows in the cloud. You can create and schedule data-driven workflows.
You will learn Introduction to Azure Data Factory, Basics of data Flows, Data flow scenarios, Data life cycle, Azure data lake storage, How to implement non-relational Data Stores, Data distribution and partitions, Data Lake Storage, Data Security with Azure Data Factory, Azure Databricks, how to Implement integration runtime, Mapping Data Flows, Azure Stream Analytics, Azure Log Analytics, how to Monitoring Data Factory pipelines, Azure Databricks, and Stream Analytics, Troubleshoot data partitioning bottlenecks, how to manage the data lifecycle.
Introduction to Cloud Computing and Azure data Factory :
Implement non-relational data stores :
Implement relational data stores :
Manage Data Security :
Develop batch processing solutions :
Develop streaming solutions :
Monitor relational and non-relational data sources :
Monitor data processing :
Monitoring Data Factory pipelines
Azure Databricks
Stream Analytics
Configuring alerts in Azure Monitor
Auditing by using Azure Log Analytics
Optimize Azure data solutions :
COURSE CONTENT
Data Transformations :
Data Modelling :
Visualizing your Data :
Working with PBI Service :
Working with Excel :
Organization Packs, Security and Groups :