Data Analytics

Learn DATA ANALYTICS with Crystalspiders Institute

SQL Development

Python Programming with Analytics

Power BI Analytics

With SQL, we can query the data that we need and do so efficiently, playing into the strengths of the database engine. We will be able to rapidly work on any relational databases by understanding SQL. SQL is worth learning because it's not only simple to learn, but it also continues to be a highly in-demand skill. Most of the professionals who wish to work as Data Analyst, Data Engineer, Data Scientist, Database Developer, ETL Developer (BI Developer), Report Developer, Test Engineer, Performance Engineer and/or Business Analyst, they should learn and get some extent of experience in SQL to continue day to day work

Power BI Analytics

Python Programming with Analytics

Power BI Analytics

We strongly believe that the data is very crucial asset for any organization that aims at effectively operating in the digital world. Power BI and Analytics have opened the door to entirely new possibilities. Our Power BI and Analytics training helps you to get practical and hands on experience in extracting the data and transform it into most valuable insights. We learn and practice on automate and optimize day to day operations and the business processes.

We discuss the following key con concepts as part of our Power BI & Analytics training

Various types of data source connections and data sets
Perform the manual analysis to understand the summaries
Extract the data from various sources, transform it and load it into Power BI desktop
Build various visuals based on the available data sets
Build various visuals based on the category of available data and customers interest
Schedule the reports to perform auto refresh
Deploy the visuals into Power BI Service
Transform the data by using Power BI Query editor
Understand and build the relationships among the data sets
Apply format changes and filters against the visual reports
Use the DAX expressions for various requirements

Python Programming with Analytics

Python is a popular high-level, general-purpose programming language. In 1991, Guido van Rossum invented it, and the Python Software Foundation continued to develop it. Programmers may communicate their ideas in less lines of code because to its syntax, which was developed with readability of code as a primary focus.

Python is a programming language that facilitates faster work and more effective system integration.

We discuss the following key con concepts as part of our Python programming training.

Learn the fundamentals of the Python programming language and its uses.
Discover how to set up and install the Python environment on various operating systems. Gain an understanding of and make use of Python modules to improve functionality and code reuse.
Gain proficiency in Python programming to effectively automate repetitive chores.
Get practical Python experience for for Data Analytics.
Learn the best practices for writing clear, efficient, and maintainable Python code.
Learn about the principles of Data Analytics and how to use Python to manage data resources.
To maintain reliable scripts and applications, get proficient in debugging and troubleshooting Python projects.
With advice on complex Python subjects and developer suggestions, get ready for real-world situations.

Professional Trainers

Learn from the best instructors and resources from anywhere in the world via our Online training programs.
Our trainers are available 24*7 regardless of their location.

Cohort Based Learning

Professional Trainers

Learn with an accomplished group of peers and build your network.
Our technical blogs address most of the frequent questions and/or issues
Gain hands on industry and functional knowledge.

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Professional Trainers

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Resume Build
Mock Interviews
FAQs preparation
Placement Assistance
Soft copy materials
Provide Software's
Course completion certificate

Module 1: Introduction of SQL, RDBMS, Software's and Tools

History of SQL
What is the Transact SQL and PL/SQL?
Understand the difference in MS SQL Server database and Oracle database!
SQL Server Versions and Editions
SQL Server Management Studio Tool
SQL Developer Tool
DBeaver Tool
DB Visualizer Tool
Toad Tool

Module 2: DB Objects and SQL Commands

Different Types of Objects in RDBMS databases
What is the purpose of Table object?
Understand Different terminologies like Columns, Rows, Data & Attributes
SQL Commands
Different data types in SQL
DDL - Data Definition Language (CREATE, ALTER & DROP)
DML - Data Manipulation Language (INSERT, UPDATE & DELETE)
TCL - Transaction Control Language (BEGIN TRAN, COMMIT, ROLLBACK & SAVEPOINT)
DCL - Data Control Language (GRANT & REVOKE)
DRL - Data Retrieval Language (SELECT)

Module 3: Different Types of Operators

Different Types of Operators in RDBMS databases
Understand the query logical processing in SQL
Comparison Operators (<, >, <=, >=, =, !=, <>)
Logical Operators (NOT, AND, OR)
Wildcard Search Operators (%, _, ^, [] )
Combine Data Set Operators (UNION ALL, UNION, INTERSECT, EXCEPT & MINUS)

Module 4: Normalization Forms, Keys and Relationships

Different Types of Normal Forms
Normal Form 1 Rules
Normal Form 2 Rules
Normal Form 3 Rules
Understand the concept of Key in a Dataset
Different types of Keys
Super Keys, Candidate Keys & Primary Key in a Table
Understand the Parent and Child table's
Different types of Relationships
One to One Relationship
One to Many Relationship
Many to Many Relationship

Module 5: Different Types of Constraints

Different types of constraints
Understand business rules in a dataset
NULL & NOT NULL constraints
Default constraints
Check constraints
Primary key constraints
Foreign key constraints
Unique key constraints

Module 6: Joins

Different types of joins
Rules and recommendations to join datasets
Inner join
Outer Joins - Left Join / Left Outer Join
Outer Joins - Right Join / Right Outer Join
Outer Joins - Full Join / Full Outer Join
Cross join & Cartesian product
Self join
Equi join
Update & delete the data from a table by using joins

Module 7: Built-in Functions

Different types of functions
Variables in SQL

String functions:
Sub string function, character index function, length function, left function, right function, trim function, upper & lower functions, replace & stuff functions, and reverse function, concat function, convert function...etc

Date time functions:
Getdate function, dateadd function, datepart function, month/year/day functions, datediff function...etc
Display the date with different formats by using convert function

NULL functions:
Isnull function, coalesce function, nullif function, and iif function

Aggregate functions:
Sum function, avg function, min function, max function, count function
Understand the Group by clause

Windowing functions:
Row number function, Rank function & Dense Rank function

Module 8: Sub Queries

Understand the main purpose of Sub Query

Different types of outputs return by a sub query
Scalar output, Multi values output & Table valued output
Dynamic value in WHERE claus

Different types of sub queries
Non correlated sub query and correlated sub query
Derived Table (Sub query in FROM clause)
Column expression (Sub query in SELECT class)
Usage of EXIST & NOT EXIST keywords
CTEs

Module 9: Ordering data sets, avoid duplicate data, fetch sample data

OORDER BY clause
DISTINCT keyword
FETCH keyword
TOP keyword
OFFSET keyword

Module 10: Different types of tables and columns

Local temporary tables
Global temporary tables
Table variables
Identity columns
Sequence objects

Module 11: Control flow statements

BEGIN...END block
IF...ELSE block
GOTO label
WAITFOR command
CASE in SELECT & WHERE clauses
WHILE Loops
CURSORs
TRY & CATH blocks
THROW
RETURN

Module 12: Merge and Triggers

Data synchronization by using MERGE statemet
Understand the purpose of Triggers in SQL
INSERTED & DELETED table's
Triggers for INSERT, UPDATE & DELTE operations
Data synchronization by using Triggers
Maintain history & audit data by using Triggers
Control the DML operations against tables by suing Triggers
INSTEAD OF triggers

Module 13: Views and Functions

Implement the views for different requirements
Different types of functions
Scalar & Table Values functions
Implement functions with input parameters

Module 14: Transactions with Error/Exception Handling

Characteristics of a transaction
Atomicity, consistency, isolation, durability
Understand the error handling and store error message in error logs
Use TRY & CATCH blocks
Commit and rollback the transactions.
Behavior of a transaction

Module 15: Implement Stored Procedures

Dynamic SQL statements
Understand the usage of stored procedures
Stored procedure with IN and OUT parameters
Stored procedures with default parameter values
Include error handling mechanism inside stored procedure
Stored procedures to process new data to the database
Stored procedures to process updates across multiple tables
Implement stored procedures to archive the data from tables
Implement stored procedures to pure the data from tables
Implement stored procedures to process the business rules

Module 16: Performance Tuning

Locks
Deadlocks
Heap and Cluster tables
Indexes - Clustered and NON-Clustered
Statistics
Execution plans and Query optimizer
Compress the tables
Add missing indexes to the tables
Logical partition of tables
Rebuild and Reorganize the indexes
Add the necessary indexes based on the SQL queries

Module 17: Export and Import the data

Export data from database to Excel, CSV, Text files, and other databases
Import the data from Excel, CSV, Text files to databases

Module 18: Security in SQL

Grant and Revoke the access to users
Different access roles in a database
Encrypt and Decrypt the data in a table by using Passwords

Module 19: Automation in SQL

Create and modify the jobs
Schedule the jobs to run as per the requirements

Module 20: Database backups and Restore

Database backup
Database restore from the backup

Module 1: Microsoft Power BI

Introducing Power BI
Real usage of Power BI
The building blocks of Power BI
Power BI Desktop & Service

Module 2: Understand the Data Analysis

Discuss the datasets, Raw data and Aggregated datasets
Analyze the data manually
Understand the complications in manual analysis
Practice the analysis work by using various datasets
Usage of the Power BI in converting the data into visuals

Module 3: Getting Data

Understand Power BI Desktop
Starts with Power BI Desktop
Connect tdata sources
Clean and transform the data with
the Query Editor
Advanced data sources and
transformations
Cleaning irregularly formatted data

Module 4: Modeling

Introduction to modeling the data
Manage data relationships
Create calculated columns
Optimizing data models
Create calculated measures
Create calculated tables
Explore the time-based data

Module 5: Visualizations (Part - I)

Introduction to visuals in Power BI
Create and customize simple
visualizations
Combination charts
Slicers
Map visualizations
Matrixes and tables
Scatter charts
Waterfall and funnel charts
Gauges and single-number cards

Module 6: Visualizations (Part - II)

Modify colors in charts and visuals
Shapes, text boxes, and images
Page layout and formatting
Group interactions among visualizations
Duplicate a report page
Show categories within data
Summarization and category options (Layer-order)
Visual hierarchies and drill-down
R integration in Power BI Desktop

Module 7: Exploring Data

Introduction to the Power BI service
Create and configure a dashboard
Data with natural language
Create custom Q&A suggestions
Share dashboards with to the Executives

Module 8: Organization/client Headers

Display visuals and tiles full-screen
Edit tile details and add widgets
Install and configure a personal gateway

Module 9: Various Data Sources

Upload CSV & Text data to Power BI
Upload Excel data to Power BI
Connect to RDBMS and Upload RDBMS data to Power BI
Extract the data from SSAS Cubles
Extract the data from Stored Procedures to Power BI
Import Power View and Power Pivot to Power BI
Connect OneDrive for Business to Power BI

Module 10: Publishing and Sharing

Introduction to content packs, security, and groups
Publish Power BI Desktop reports
Print and export dashboards and reports
Manually republish and refresh your data
Introducing Power BI Mobile
Create groups in Power BI
Build content packs
Use content packs
Update content packs
Publish to web

Module 11: DAX

Introduction to DAX
DAX calculation types
DAX functions
Using variables in DAX expressions
Table relationships and DAX
DAX tables and filtering

Module 1: An Introduction to Python

What can Python do?
Why Python?
Python Syntax compared to other programming languages
Python Install

Module 2: Beginning Python Basics

Print statement
Comments
Python Data Structures & Data Types
String Operations in Python
Simple Input & Output
Simple Output Formatting
Operators in python
Lists
Matrixes
Functions
Dictionaries

Module 3: Python Program Flow

Indentation
IF statement and its examples
WHILE loop
FOR loop
RANGE statement
Break &Continue

Module 4: Functions& Modules

Create your own functions
Functions Parameters
Variable Arguments
Scope of a Function
Function Documentations
Lambda Functions& map
Exercise with functions
Create a Module
Standard Modules

Module 5: Exceptions Handling

Exception handling with try
Handling Multiple Exceptions
Writing your own Exception

Module 6: File Handling

File handling Modes
Reading Files
Writing & Appending to Files
Handling File Exceptions
The WITH statement

Module 7: Classes in Python

New Style Classes
Creating Classes
Instance Methods
Inheritance
Polymorphism
Exception Classes & Custom Exceptions

Module 8: Generators and iterates

Iterates
Generators
The Functions any and all
With Statement
Data Compression

Module 9: Data Structures and Search

List Comprehensions
Nested List Comprehensions
Dictionary Comprehensions
Functions
Default Parameters
Variable Arguments
Specialized Sorts
Binary Search

Module 10: JSON and CSV Modules

JSON Module
CSV Module

Module 11: Threading Date Time Regular Expressions

Program execution time
More methods on date/time
Map
Decorators
Regular expression - Split, Match, find all, substitute, Search methods
Threads ESSENTIAL - Class and threads, Multi-threading, Synchronization, Life cycle
Logging Module
Copy Module
Slicing

Module 12: Database

DB Connection and SSMS component
Creating Databases
DDL, DML, DRL operations and practice
Joins in SQL
Sub-Queries in SQL
String Functions
Datetime Functions
Aggregate Functions

Module 13: Data Analytics

Introduction to Analytics
Introduction to Pandas
Purpose and Create the Data frames
Series in Pandas
Operators in Data frames
Validation in Data frames
Extract the data
Display the data in various formats
Filtering the data
Query to evaluate the data
Data cleaning & Remove duplicates
Sorting the data
Usage of the Maps
Row and Column level functions
Indexing and sampling the data
Work with categorical data
Create Dummy variables
Read data from multiple files
Perform aggregations by Group by option
Transform, Cross table and Pivoting data
Handle missing data
Reshaping the data
Join, Merge the data
Concatenate the data
3rd party APIs

Module 14: Numpy

Introduction to NumPy
Perform the mathematical analysis

Module 15: Matplotlib

Introduction to Matplotlib
Build the visuals for different requirements

Module 16: SciKit

Introduction to SciKit library
Build the model for accurate predictions

Crystalspiders Institute

Professional Training in Data Analytics

REGULAR TRAINING STARTS

REGULAR TRAINING STARTS

REGULAR TRAINING STARTS

DURATION

REGULAR TRAINING STARTS

REGULAR TRAINING STARTS

TRAINING FEE

REGULAR TRAINING STARTS

TRAINING FEE

Learn DATA ANALYTICS with Crystalspiders Institute

SQL Development

Python Programming with Analytics

Power BI Analytics

Power BI Analytics

Python Programming with Analytics

Power BI Analytics

Python Programming with Analytics

Python Programming with Analytics

Python Programming with Analytics

Training Highlights

World-class learning with faculty-led & live classes

Professional Trainers

Professional Trainers

Professional Trainers

Cohort Based Learning

Professional Trainers

Professional Trainers

More Services

Professional Trainers

More Services

Programme Modules in SQL Development

Programme Modules in Power BI Analytics

Modules in Python Programming with Analytics

Contact Us

Crystalspiders Institute

Professional Training in Data Analytics

REGULAR TRAINING STARTS

REGULAR TRAINING STARTS

REGULAR TRAINING STARTS

DURATION

REGULAR TRAINING STARTS

REGULAR TRAINING STARTS

TRAINING FEE

REGULAR TRAINING STARTS

TRAINING FEE

Learn DATA ANALYTICS with Crystalspiders Institute

SQL Development

Python Programming with Analytics

Power BI Analytics

Power BI Analytics

Python Programming with Analytics

Power BI Analytics

Python Programming with Analytics

Python Programming with Analytics

Python Programming with Analytics

Training Highlights

World-class learning with faculty-led & live classes

Professional Trainers

Professional Trainers

Professional Trainers

Cohort Based Learning

Professional Trainers

Professional Trainers

More Services

Professional Trainers

More Services

Programme Modules in SQL Development

Programme Modules in Power BI Analytics

Modules in Python Programming with Analytics

Contact Us

Crystalspiders Institute

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