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#Snowflake Data Analyst 

Snowflake Data Analyst refers to using the Snowflake Data Cloud platform for business intelligence and advanced analytics. It enables seamless integration with top BI tools like Power BI, Tableau, and Looker for real-time data reporting. BI professionals use it for building dashboards, KPIs, and interactive reports from massive datasets. Mastering Snowflake BI leads to roles like BI Developer, Data Analyst, and Snowflake Reporting Specialist.

Power BI SQL School Modules

Training Schedules

S NoTime (IST, Mon - Fri)Start Date
16 AM - 7 AMAug 6th
28 PM - 9 PMAug 18th
Snowflake Data Analyst Training Highlights

Snowflake Data Analyst
Training Course Contents:

Module 1 : Microsoft SQL (TSQL)

Ch 1: SQL SERVER INTRODUCTION

  • Database Introduction
  •  Types of Databases
  •  Need for & ETL, DWH
  •  BI Implementations
  •  SQL Server Advantages
  •  Version, Editions of MSSQL
  •  Data Analyst Job Roles

Ch 2: SQL SERVER INSTALLATIONS

  • SQL Server 2019, 2017
  • SSMS Tools Installation
  • Database Engine (OLTP)
  • SCM, Configuration Tools
  • Instance Types, Uses
  • Authentication Modes
  • Collation, File Stream

Ch 3: SQL BASICS – 1

  • Need for Databases, Tables
  • Need for SQL Commands
  • DDL, DML & DQL Statements
  • Database Creation @ GUI
  • Data Operations @ GUI
  • Session ID, SQL Context
  • DB, Tables, Data @ SQL

Ch 4: SQL BASICS – 2

  • DDL Variants in MSSQL
  • DML Variants in MSSQL
  • INSERT & INSERT INTO
  • SELECT & SELECT INTO
  • Basic Operators in SQL
  • Special Operators in MSSQL
  • ALTER, ADD, TRUNCATE, DROP

Ch 5: Data Imports, Schemas

  • Data Imports with Excel
  •  ORDER BY & UNION
  • UNION ALL For Sorting Data
  •  Creating, Using Schemas
  •  Real-world Banking Database
  •  Table Migrations @ Schemas
  •  2 Part, 3 Part & 4 Part Naming

Ch 6 : Constraints, Index Basics

  • Need for Constraints, Keys
  •  NULL, NOT NULL, UNIQUE
  •  Primary Key & Foreign Key
  •  RDBMS and ER Models
  •  Identity Property, Default
  •  Clustered Index, Primary Key
  •  Non Clustered Index, Unique

Ch 7: Joins & Views Basics

  • JOINS: Purpose. Inner Joins
  • Left / Right / Full Outer Joins
  • Cross Joins, Query Tuning
  • Creating & Using Views
  • DML, SELECT with Views
  • RLS : WITH CHECK OPTION
  • System Views & Metadata

Ch 8: Functions(UDF), Data Types

  • Using Functions in MSSQL
  •  Scalar Value Functions
  • Inline & Multiline Functions
  • Date & Time Functions
  • String, Aggregate Functions
  • Data Types : Integer, Char, Bit
  • SQL Variant, Timestamp, Date

Ch 9: Stored Procedures,Models

  • Stored Procedures & Usage
  • Creating, Testing Procedures
  • Encryption, Deferred Names
  • SPs for Validations, Analysis
  • System SPs, Recompilation
  • Normal Forms & Types
  • Data Models, Self-References

Ch 10: Triggers, Temp Tables

  • Need for Triggers
  • DDL & DML Triggers
  • Using Memory Tables
  • Data Replication, Automation
  • Local & Global Temp Tables
  • Testing & Using Temp Tables
  • SELECT .. INTO & Bulk Loads

Ch 11: DB Architecture, Locks

  • Planning VLDBs : Files, Sizing
  • Filegroups, Extents & Types
  • Log Files : VLF, Mini LSN
  •  Table Location, Performance
  • Schemas, Transfer, Synonyms
  • Transactions Types, Lock Hint
  •  Query Blocking Scenarios

Ch 12 : Cursors & CTEs, Links

  • Cursors : Realtime Use
  • Fetch & Access Cursor Rows
  • CTEs for SELECT, DML
  • CTEs: Scenarios & Tuning
  • Linked Servers, Remote Joins
  • Linked Servers: MSDTC, RPC
  • Tuning Remote Queries

Ch 13: Merge, Upsert & Rank

  • Need for Merge in ETL
  • Incremental Loads with SQL
  • MERGE and RANK Functions
  • Window Functions, Partition
  • Identify, Remove Duplicates

Ch 14: Grouping & Cube

  • Group By & HAVING
  • Cube, Rollup & Grouping
  • Joins with Group By
  • 3 Table, 4 Table Joins
  • Query Execution Order

Ch 15: Self Joins, Excel Analysis

  • Self Joins & Self References
  •  UNION, UNION ALL
  •  Sub Queries with Joins
  •  IIF, CASE, EXISTS Statements
  •  Excel Analytics, Pivot Reports

Module 2: Snowflake

Ch 1: Introduction to Snowflake

  • Database, DWH Introduction
  • OLTP, OLAP and DWH
  • Data Warehouse Advantages
  • Cloud DWH Implementations
  • IaaS, PaaS & SaaS Concepts
  • Snowflake Cloud Intro
  • Snowflake: SaaS Platform
  • Snowflake Advantages

Ch 2: Snowflake Concepts

  • Snowflake Account (Cloud)
  • Snowflake Components
  • Snowflake Editions, Credits
  • Web UI & Snow Sight
  • Snowflake Editions
  • Snowflake Storage
  • Virtual Private Edition (VPS)
  • Snowflake Pricing

Ch 3: Architecture, Warehouse

  • Compute Architecture
  • Shared Disk Architecture
  • Nodes and Clusters
  • CPU & Memory in Clusters
  • Database Query & Data Cycle
  • ColumnStore,Virtual Warehouse
  • Classic UI with Snowflake
  • Massively Parallel Processing

Ch 4: Snowflake DB & Tables

  • DB Objects and Hierarchy
  • Worksheet Parameters
  • DB Creation with Snowflake
  • Snowflake Tables and Usage
  • Retention Time, Connections
  • Permanent, Transient Types
  • CREATE TABLE AS SELECT
  • ALTER, DROP & UNDROP

Ch 5: Time Travel, Recovery

  • Time Travel in Snowflake
  • Continuous Data Protection
  • Invoking Time Travel Feature
  • Timestamp, Offset, Query ID
  • Data Recovery, TIMESTAMP
  • OFFSET in Real-world
  • Fail Safe and UNDROP
  • Transient Tables, Real-time

Ch 6: Schemas and Session Context

  • Schema Creation Usage
  • Permanent, Transient Schemas
  • Managed Schemas in Snowflake
  • Invoking Schemas & Cloning
  • Snowflake Workspaces
  • Session Context & Schema
  • Query and History Tab in GUI
  • Data Loading with GUI

Ch 7: Constraints & Data Types

  • Constraints & Validations
  • NULL, NOT NULL Properties
  • Keys & Constraints, Usage
  • Inline, Out Of LineConstraints
  • Table Constraints, Use
  • ENFORCED Constraints
  • DEFERRED, IMMEDIATE
  • Snowflake Data Types

Ch 8: Snowflake Cloning

  • Cloning with Snowflake
  • Zero Copy, Schema Cloning
  • Real-time Cloning
  • Snapshot, Metadata
  • Permissions for Cloning
  • Accessing, Clone
  • Storage & Metadata Layer
  • Real-time Considerations

Ch 9: Snowflake Procedures

  • Procedures and Functions
  • SQL and JavaScript & CALL
  • Transactions & Injection
  • sqlText:command
  • Cursoring Data and Operations
  • Dynamic DML with SPs
  • Working with Loops
  • RETURN, RETURNS Statements

Ch 10: Security Management

  • Security with Snowflake
  • Users & Roles in Snowflake
  • Privileges and Groups
  • Organization, Account, Users
  • Creating, Using Roles, Users
  • System Defined Roles Usage
  • Role Hierarchy, Dependency
  • RBAC & DAC in Real-time

Ch 11: Snowflake Transactions

  • Transaction ACID Properties
  • Implicit, Explicit and Auto
  • Durability and Data Storage
  • current_transaction() Usage
  • to_timestamp_ltz and Usage
  • Failed Transactions with SPs
  • Transactions and SPs
  • Scoped & INNER Transactions

Ch 12: Snowflake Streams & Audits

  • Snowflake Streams & Usage
  • Streams and DML Auditing
  • Snapshot Creation, Offset
  • METADATA Options & Streams
  • Auditing DML Operations
  • Data Flow & Snowflake Streams
  • Streams on Transient Tables
  • Time Travel with Stream Tables

Ch 13: Snowflake Tasks, Partitions

  • Tasks, Serverless Compute
  • Tasks Tree: Root and DAG
  • Tasks Schedules and RESUME
  • User & Snowflake Managed
  • CRON Syntax with Tasks
  • Virtual Warehouse Concepts
  •  Multi Cluster Warehouse
  • Auto Scale Options, Billing

Ch 14: SnowSQL and Variables

  • SnowSQL Configurations
  • DDL, DML & SELECT
  • SnowSQL Command Line
  • Variables and Batch Process
  • DECLARE, LET, BEGIN & END
  • EXECUTE IMMEDIATE, FOR
  • Creating Virtual Warehouse
  • Writing Output to Files

Ch 15: Snowflake Partitions, Stages

  • Snowflake Partitions, Use
  • Micro Partition with DML, CDC
  • Cluster Key, Depth and Overlap
  • Internal Partition Types & Usage
  • List, Range and Hash Partitions
  • Snowflake Stages, Types
  • Internal and External Stages
  • COPY Command, Bulk Loads

Ch 16: Azure & External Stages

  • Azure Subscriptions
  • Azure Storage Account, BLOB
  • SAS: Shared Access Signature
  • Using SAS Key and FILE PATH
  • Azure Storage with BLOB
  • COPY INTO Command Usage
  • Snowflake Patterns & RegEx
  • File Formats: Creation, Usage

Ch 18: Realtime Case Study

Module 3: Power BI

Ch 1 : Power BI Introduction

  • Reporting Basics & Types
  • Interactive,Analytical Reports
  • Paginated Reports (RDL)
  • Power BI Eco System
  • Power BI Tools,Service,Server
  • Need for Power Query (M)
  • Need for DAX & Cloud

Ch 2: Power BI Basic Reports

  • Power BI Desktop Installation
  • Basic Report Design (PBIX)
  • Data View, Data Models
  • Data Points, Aggregations
  • Focus Mode, Spotlight, Exports
  • ToolTip, PBIX and PBIT
  • Visual Interactions & Edits

Ch 3 : Grouping, Hierarchies

  • Creating Groups in Power BI
  • Groups : Creation & Usage
  • Group Edits Options
  • Bins & Bin Size, Bin Count
  • Hierarchies: Creation, Use
  • Drill Down, Drill Up
  • Conditional Drill Down

Ch 4 : Visual Sync, Filters

  • Slicer & Single Select
  • Multi Select Options
  • Integer, Character Slicers
  • Visual Sync with Slicers
  • Filters: Visual, Page, Report
  • Drill Thru Filters & Usage
  • Basic, Top & Advanced
  • Clear Filter Options, Resets

Ch 5 : Bookmarks, Big Data

  • Bookmarks Creation & Usage
  • Visual Interactions, Bookmarks
  • Images : Actions, Bookmarks
  • Big Data Access with Power BI
  • Storage Modes: Direct Query
  • Import & Performance Impact
  • Formatting & Data Refresh
  • Summary, Date Time Formats

Ch 6 : Power BI Visualizations

  • Chart and Bar Visuals
  • Line and Area Charts
  • Maps, TreeMaps, HeatMaps
  • Funnel, Card, Multrow Card
  • PieCharts & Settings
  • Waterfall, Sentiment Colors
  • Scatter Chart, Play Axis
  • Infographics, Classifications

Ch 7 : Power Query Level 1

  • Power Query (Mashup)
  • ETL Transformations in PBI
  • Power Query Expressions
  • Table Combine Options
  • Merge, Union All Options
  • Table Transformations

Ch 8 : POWER QUERY LEVEL 2

  • Any Column Transformations
  • String / Text Transformations
  • Numeric Analytics & Mashup
  • Date Time Transformations
  • Add Column Transformations
  • Expressions and New Columns

Ch 9 : POWER QUERY LEVEL 3

  • Parameters in Power Query
  • Static Parameters, Defaults
  • Dynamic Dropdowns, Lists
  • Linking with Table Queries
  • Column From Examples
  • Step Edits, Type Conversions

Ch 10 : Power BI Cloud – 1

  • Power BI Cloud Concepts
  • Workspace Creation, Usag
  • Report Publish & Edits
  • Semantic Models in Realtime
  • Dashboard Creation, Usage
  • Clone, Share, Subscribe
  • Q&A, Lineage, Settings

Ch 11 : Power BI Cloud – 2

  • Data Gateways, Data Refresh
  • Data Source Configurations
  • Data Refresh & Scheduling
  • Gateway Optimizations
  • Semantic Model Optimizations
  • Report Optimizations
  • Dashboard Optimizations

Ch 12 : Power BI Cloud – 3

  • Power BI Apps, Shares
  • App Sections & Options
  • App Updates, Security
  • Excel Analytics
  • Data Explorer Option
  • Sharing, Subscriptions
  • Alerts, Metrics, Insights

Ch 13 : Report Server & DAX

  • Power BI Report Server
  • Report Database, TempDB
  • Web Service & Server URL
  • Paginated Reports (RDL)
  • Report Builder Tool Usage
  • DAX : Purpose, Realtime Use

Ch 14: DAX Level 2

  • DAX Measures Creation, Use
  • DAX Functions: IIF, ISBLANK
  • SUM, CALCULATE Functions
  • DAX Cheat Sheet : Examples
  • Quick Measures in Power BI
  • Running Totals, Filters

Ch 15 : DAX Level 3

  • Star Rating Calculations
  • Data Models & DAX
  • Star & Snowflake Schemas
  • Dimensions, Fact Tables
  • DAX Expressions & Joins
  • DAX Variables, Usage

Ch 16 : DAX Level 4

  • Dynamic Report with DAX
  • SELECTED MEMEBER
  • Time Intelligence with DAX
  • PARALLELPERIOD, DATE
  • DAX with Big Data
  • Big Data Analytics

Ch 17 : Realtime Project Phase 1

  • Project Requirement Spec
  • Understanding Data, Formats
  • Report Pattern Design
  • Report Design & Modelling
  • Power Query, DAX, Insights
  • Analytical Reports in Cloud

Ch 18 : Realtime Project Phase 2

  • Complete Project Solution
  • Project FAQs, Key Roles
  • Real-world Considerations
  • Power BI Admin Concepts
  • Resume Points, FAQs
  • PL 300 Exam Guidance

SQL SCHOOL

24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.

Snowflake Training FAQ's

What is Snowflake BI Job Role?

A Snowflake BI  leverages Snowflake’s cloud data platform to build scalable, secure, and high-performance data models for business intelligence and reporting.

🔑 Key Responsibilities:

  • Design and optimize data models in Snowflake

  • Integrate Snowflake with BI tools like Power BI, Tableau, or Looker

  • Write and manage SQL queries for data analysis

  • Develop ETL/ELT pipelines for data transformation

  • Ensure data quality, security, and performance

  • Collaborate with analysts and business teams

  • Automate reports and dashboards for insights

  • Monitor warehouse usage and cost optimization

What are the Job Roles of an Snowflake BI?

💼 Top Job Roles:

  1. BI Developer – Build reports and dashboards using data from Snowflake

  2. Data Analyst – Analyze and interpret Snowflake data for business insights

  3. Data Engineer – Design and maintain Snowflake-based data pipelines

  4. ETL Developer – Load, transform, and manage data within Snowflake

  5. Data Modeler – Create optimized data models in Snowflake

  6. SQL Developer – Write complex queries and procedures in Snowflake SQL

  7. Reporting Analyst – Deliver KPIs and visualizations using BI tools

  8. Cloud Data Specialist – Manage Snowflake performance, scaling, and storage

  9. Data Quality Analyst – Ensure accuracy and consistency of Snowflake datasets

  10. Analytics Consultant – Provide strategic insights using Snowflake and BI platforms and more..!

What does our Snowflake Training course contains?

The course is carefully curated with below module:
👉🏻Module 1: MSSQL & TSQL Queries
👉🏻Module 2: Snowflake
👉🏻Module 3: Power BI

Who can join this course?

  • Freshers looking to start a career in data or analytics

  • Working professionals wanting to shift to Python, Data Science, or ETL roles

  • Students from any background interested in tech and data

  • IT and Non-IT professionals aiming to upskill

  • Anyone with basic computer knowledge and a passion for learning

No prior coding experience is required. All concepts are taught from scratch

What training modes are available?

Option 1:        LIVE Online Training  (100% Interactive, step by step, assignments)

Option 2:        Self Paced Videos (100% practical, step by step with concept wise assignments)

You may choose any one of these options, same curriculum!

I (Trainer) shall be available for doubts and clarifications, assignment check and review.

Why should I choose SQL School for Snowflake BI training?

👉🏻 Every session is Practical, Step by Step with Concept wise FAQs !!

👉🏻 100% results with on-time practice.  Daily Tasks for every session.

👉🏻 Concept wise tasks be submitted before next class for Job Waiters / Starters.

👉🏻 Concept wise tasks due for submission by Weekends for Working Professionals.

Why Choose SQL School

  • 100% Real-Time and Practical
  • ISO 9001:2008 Certified
  • Concept wise FAQs
  • TWO Real-time Case Studies, One Project
  • Weekly Mock Interviews
  • 24/7 LIVE Server Access
  • Realtime Project FAQs
  • Course Completion Certificate
  • Placement Assistance
  • Job Support
  • Realtime Project Solution
  • MS Certification Guidance