1 : Introduction to Database (what is database & sql & create table syntax & insert data into it)

2 : SQL Datatypes (Number,Char,varchar2,Date,Interval data type)(default value concept)

3 : Data integrity constraints (Not null,Unique,primary,check,foreign)

4 : DDL commands(create,alter,Drop,comment,truncate,Rename) & DML(Insert,update,delete) commands & TCL commands(commit,Rollback)

5: SQL Operators (Arithmetic,Relational,logical,In,Between,Like,||,Is Null,Is Not Null)

      NVL & NVL2 & Coalesce

6 & 7 : Aggregate Functions(Min,max,sum,count) & window functions (dense_rank(),rank(),row_number())

      Group By & Having Clause & Order By

      Trunc & round function

8: Subqueries (scaler,multi valued,multi column,nested subquery)

9: Introduction to joins (inner,left,right,full outer,cross,self)

10: Joins questions

11: Joins questions

12: string functions(substr,Instr,lower,upper,replace,ltrim,rtrim,distinct)   

13: Case statement & CTE & Index &Set operators(Union,union all,minus,intersect)

       SQL optimization techniques

       Fact & dimension tables

       Star schema &snowflake schema

14: SQL Interview questions

1 : Introduction to Linux

     -Overview of Linux and its History

     -File system structure

     -Introduction to the terminal

    -Basic Commands (date,cal,uname,ls,who,echo,file,last,tree)

2: Commands

– Vi editor

– Cat, tac, rev, touch, mkdir, rmdir, rm, cp, mv, cd, head, tail, more

3 : Commands

– diff, gzip, gunzip, tar, Soft link, Hard link , wc, pipe, cut, paste, tr, sort, uniq, split

4 : Commands

– grep, sed, Chmod, umask, chown, find, ping,df,du

1: Introduction to Python

      Installating python and setting up the development environment

2: Data Types in Python Part 1

3: Data Types in Python Part 2

4: Data Types in Python Part 3

5: Operators in Python

      Input function

6 , 7 & 8: Control Statements

      -if statement

      -if .. else statment

      -if ..elif..else statment

      -while loop

      -for loop

      -break statment

      -continue statment

      -pass statment

9: Functions in Python

      -In built & user defined functions

10: Modules, Packages and libraries

11: Special Type of functions

12: Regular expression

       date and time modules

13: Python programs practice

14 & 15: Pandas library in python

• 1: Hadoop intro

         Hadoop vs Spark

         Spark Architecture

  2: Rdd introduction

         Transformations

         Spark internal work flow

  3: Rdd ,map, flatmap, filter, ReduceBykey, groupBykey

         DAG,Rdd Lineage

  4: Rdd to dataframe

         Dataframe intro

         SparkSession vs SparkContext

         csv data process

  5: Spark Built in functions part 1

  6: Spark Built in functions part 2

  7: Spark date functions & windows functions

  8: Spark json data processing in detail

  9: Spark procces pandas & data cleaning

  10: Spark process avro, parquet, orc in dpeth

          Avro vs Parquet vs Orc file formats.

  11: Spark Jdbc, oracle, mysql data process

  12: Handling currepted records scenarios in details (Data Cleaning)

  13: Data Migration

          Spark Submit

  14: Handle incremental data (Merge Upsert Concept in spark)

  15: Spark performance tuning part 1

  16: Spark performance tuning part 2

  Day 17: Spark Scenario based Interview Questions

• Configure management groups

• 1: Introduction to Azure Cloud

           – Overview of cloud computing and azure

          – Understanding Azure services and solutions

          – Creating an Azure Account and subscription

  2: Azure Virtual Machine

  3: Azure Storage

           Blob Storage

           ADLS Gen2

  4: Azure Database

  5: Azure Synapse

  6 to 8: Azure Databricks & Azure Devops    

         -All the deployment Activities from building notebook to publish.

         -Azure Key Vault

  9 to 14: Azure Data Factory (ADF)

           Activities:

          -Copy Activity

         -GetMetadata Activity

         -ForEach Activity

        -Lookup Activity

        -If Condition

        -Delete Activity

        -Debug Until Activity

        -Execute Pipeline Activity

       -Notebook Activity

  15: Azure Scenario Based Interview questions

1: History and Introduction to Snowflake.

• Snowflake history
• Introduction to virtual warehouses, databases, and schemas

2: Snowflake architecture and account creation.

• Snowflake architecture
• Setting up a Snowflake account and environment
• Steps to create a Snowflake account

3: Data Loading

• Loading data into Snowflake from various sources:
• Explanation of supported file formats (CSV, JSON, Parquet, etc.).
• Using Snowflake’s COPY INTO command to load data from cloud storage or local files.

4: Data Modeling

• Introduction to structured, semi-structured, and unstructured data.
• Creating tables and schemas in Snowflake:
• Syntax for creating databases, schemas, and tables.

5: Querying Data

• Writing SQL queries in Snowflake to retrieve and manipulate data:
• Basic SQL syntax for querying tables, filtering rows, and selecting columns.
• Performing simple calculations and transformations using SQL functions (joins, window functions).

6: Data Transformation

• Introduction to Snowflake’s data transformation capabilities using SQL:
• Overview of data transformation tasks such as filtering, aggregating, and sorting data.
• Understanding the role of SQL in ETL (Extract, Transform, Load) processes.

7: Security and Access Control

• Managing users, roles, and privileges in Snowflake:
• Creating and managing users, roles, and permissions.

8: Monitoring and Optimization

• Overview of performance optimization techniques for data loading, querying, and data modeling.
• Zero copy cloning
• Internal stage/ external stage
• Overview of Snowpipe
• Introduction to Snowflake’s documentation and online resources.