Description
The Data Analyst course takes a deep dive into the essentials of data analysis, concentrating on practical skills and real-world application. With the aid of programs like Excel, SQL, and Python, you will become an expert in data manipulation, exploration, and visualization. The course covers data cleaning, statistical analysis, and machine learning basics, enabling you to uncover insights and drive business decisions. You’ll also learn to create compelling visualizations and reports, ensuring your findings are clear and impactful. The goal of this course is to give you the tools you need to succeed in a data analysis career.
Key Features
Expert Trainers
We are a team of 7 + Years of Industry Experienced Trainers, who conduct the training with real-time scenarios. The Trainers follow the Project-Based Learning Method in the Interactive sessions.
Mock Interviews and Preparations
Boost your confidence with mock interviews and thorough preparations, equipping you with the skills needed to ace your next job opportunity.
Live Projects
Learning journey through real-life industry projects, sponsored by top companies across various sectors, ensuring hands-on experience that prepares you for success.
Course Completion Certificate
After completing this course, receive a Fusion Training Institute certificate to boost your resume and advance your career!
Tools Used in This Course
Advance Excel            Python        Sql            Power Bi         TableauÂ
Future of Data Analytics with Power BI
   ₹4.2 LPA to ₹15 LPA         Â
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 Job Opportunities                    
Future Analytics
An data analyst who is working          According to the data of IBM                   In the coming next few yearswith Power BI can get around           the data analytics industry                     a large proportion of firms₹4.2 LPA. And an experienced          will produce approximately                    will start using public clouddata analyst can earn almost            2,720,000 new jobs in the coming years.        services for storing their data.
₹15 LPA.                              coming years.
The data analytics with Power BI course is for students who wish to acquire in-depth knowledge of data analytics, data visualization, and Power BI. In this training program, you will learn how to transform/visualize data with the help of Power BI. You will also learn to create detailed reports and dashboards with Power BI. After this course, students can work in different roles like:
- Data Analyst
- Data Scientist
- Power BI Developer
- Finance Analyst
- Business Intelligence Analyst
The students who complete the data analytics with Power BI course are presented with various job opportunities in the Power BI and data analytics industry. This is because of the value that a data analyst and Power BI developer adds to a company via his/her services. This is why many firms continuously keep looking for skilled data analysts and Power BI developers for their organizations. Moreover, companies don’t even shy away from paying handsome remuneration to data analysts and Power BI developers for their services.
According to the data of IBM, the data analytics industry will produce approximately 2,720,000 new jobs in the coming years.
Ample opportunities are available for professionals who wish to pursue their careers in data analytics and the Power BI industry. For example, you may work as a data scientist.
By the year 2023, a large proportion of firms will start using public cloud warehousing services for storing their data.
The CAGR of the data analytics market is expected to be 25% for the next two years
Advance Excel
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- Creation of Excel Sheet Data
- Range Name, Format Painter
- Conditional Formatting, Wrap Text, Merge & Centre
- Sort, Filter, Advance Filter
- Different type of Chart Creations
- Auditing, (Trace Precedents, Trace Dependents)Print Area
- Data Validations, Consolidate, Subtotal
- What if Analysis (Data Table, Goal Seek, Scenario)
- Various Simple Functions in Excel(Sum, Average, Max, Min)
- Real Life Assignment work
- Restoring data to original order after performing sorting
- Subtotal, Multi-Level Subtotal
- Consolidation With Several Worksheets
- Printing of Raw & Column Heading on Each Page
- Workbook Protection and Worksheet Protection
- Specified Range Protection in Worksheet
- Data Table
- Advance use of Data Tables in Excel
- Reporting and Information Representation
- Pivot Table
- Slicer with Pivot Table & Chart
- Generating MIS Report In Excel
- Advance Functions of Excel
- Lookup & Reference Function
- Logical Functions & Date and Time Functions
- Functions for Calculation Depreciation
- Advance Python
- Installation and Working with Python
- Understanding Python variables
- Understanding the Python blocks.
- Python Comments, Multiline Comments.
- Understating the concepts of Operators
- Variables, expression condition and function
- Global and Local Variables in Python
- Packing and Unpacking Arguments
- Byte objects vs. string in Python
- Declaring and using Numeric data types
- Using string data type and string operations
- Understanding Non-numeric data types
- Understanding the concept of Casting and Boolean.
- Statements if, else, elif
- How to use nested IF and Else in Python
- Loops and Control Statements.
- Jumping Statements Break, Continue, pass
- Looping techniques in Python
- How to use Range function in Loop
- Programs for printing Patterns in Python
- How to use if and else with Loop
- Use of Switch Function in Loop
- Elegant way of Python Iteration
- How to use nested Loop in Python
- Use If and Else in for and While Loop
- Examples of Looping with Break and Continue Statement
- How to use IN or NOT IN keyword in Python Loop.
- Arguments in a function Required, Default, Positional, Variable-length
- Write an Empty Function in Python pass statement.
- Lamda/ Anonymous Function
- Scope and Life Time of Variable in Python Function
- Nested Loop in Python Function
- Recursive Function and Its Advantage and Disadvantage
- Organizing python codes using functions
- Organizing python projects into modules
- Importing own module as well as external modules
- Random functions in python
- Programming using functions, modules & external packages
- Map, Filter and Reduce function with Lambda Function
- More example of Python Function
- List Append & Extend using + and Keyword
- List related Keyword in Python
- List having Multiple Reference
- String Split to create a List
- List Comprehension and Nested Comprehension
- Accessing Elements in Tuple
- TupleBuilt in Function (Length, Sort)
- Dict Access (Accessing Dict Values)
- Dict Add or Modify Elements
- Dict Keys (Updating, Removing and Iterating)
- Dict useful methods (Pop, Pop Item, Str , Update etc.)
- Remove elements from a Set
- Remove elements from a Set
- Python Errors and Built-in-Exceptions
- Exception handing Try, Except and Finally
- Catching Exceptions in Python
- Catching Specic Exception in Python
- Renaming and Deleting Files in Python
- Python Directory and File Management
- List Directories and Files
- SQL Database connection using
- Creating and searching tables
- Reading and Storing cong information on database
- Programming using database connections
- Reading an excel le using Python
- Writing to an excel sheet using Python
- Python| Reading an excel le
- Python | Writing an excel le
- Adjusting Rows and Column using Python
- ArithmeticOperation in Excel le.
- Play with Workbook, Sheets and Cells in Excel using Python
- Creating and Removing Sheets
- Formatting the Excel File Data
- More example of Python Function
- Check Dirs. (exist or not)
- How to split path and extension
- How to get user prole detail
- Get the path of Desktop, Documents, Downloads etc.
- Handle the File System Organization using OS
- How to get any les and folders details using OS
- POWER BI
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- Building Blocks of Power BI
- Getting started with Power BI Desktop
- Introduction to Tools and Terminology
- Interacting with your Dashboards
- Sharing Dashboards and Reports
- Extracting data from various sources
- Connecting Power BI Desktop to our Data Sources
- Understanding Append Queries
- Pivoting and Unpivoting Columns
- Creating a New Group for our Queries
- Introducing the Star Schema
- Duplicating and Referencing Queries
- Creating the Dimension Tables
- Finishing the Dimension Table
- Introducing the another DimensionTable
- Duplicating Columns and Extracting Information
- Creating Conditional Columns
- Performing Basic Mathematical Operations
- Improving Performance and Loading Data into the Data Model
- Introduction to Modelling
- Cardinality and Cross Filtering
- Default Summarization & Sort by
- Creating Calculated Columns
- Creating Measures & Quick Measures
- Syntax, Functions, Context Options
- Measures and Calculated Columns
- ROW Context and Filter Context in DAX
- Operators in DAX – Real-time Usage
- Quick Measures in DAX – Auto validations
- In-Memory Processing DAX Performance
- How to use Visual in Power BI
- Creating Visualisations and Colour Formatting
- Scatter & Bubble Charts & Play Axis
- Tooltips and Slicers, Timeline Slicers & Sync Slicers
- Cross Filtering and Highlighting
- Visual, Page and Report Level Filters
- Hierarchies and Reference/Constant Lines
- Tables, Matrices & Conditional Formatting
- Drill through and Custom Report Themes
- Grouping and Binning and Selection Pane, Bookmarks & Buttons
- Data Binding and Power BI Report Server
- Why Dashboard and Dashboard vs Reports
- Conguring a Dashboard Dashboard Tiles, Pinning Tiles
- Quick Insights in Power BI
- Exploring live connections to data with Power BI
- Connecting directly to SQL Server
- Connectivity with CSV & Text Files
- Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel
- Introduction and Sharing Options Overview
- Publish from Power BI Desktop and Publish to Web
- Share Dashboard with Power BI Service
- Workspaces (Power BI Pro) and Content Packs (Power BI Pro)
- Print or Save as PDF and Row Level Security (Power BI Pro)
- Export Data from a Visualization
- Export to PowerPoint and Sharing Options Summary
- Understanding Data Refresh
- Personal Gateway (Power BI Pro and 64-bit Windows)
- Replacing a Dataset and Troubleshooting Refreshing
- SQL
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- Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
- SQL Server Features & Purpose
- Using Management Studio (SSMS)
- Conguration Tools & SQLCMD
- SQL Database Architecture
- Database Creation using GUI
- Database Creation using T-SQL scripts
- DB Design using Files and File Groups
- File locations and Size parameters
- Database Structure modications
- SQL Server Database Tables
- Table creation using T-SQL Scripts
- Naming Conventions for Columns
- Single Row and Multi-Row Inserts
- Table creation using Schemas
- SELECT queries and Schemas
- Use of WHERE, IN and BETWEEN
- Variants of SELECT statement
- ROWCOUNT and CUBE Functions
- Table creation using Constraints
- NULL and IDENTITY properties
- UNIQUE KEY Constraint and NOT NULL
- PRIMARY KEY Constraint & Usage
- CHECK and DEFAULT Constraints
- Naming Composite Primary Keys
- Disabling Constraints & Other Options
- Benets of Views in SQL Database
- Views on Tables and Views
- SCHEMA BINDING and ENCRYPTION
- Issues with Views and ALTER TABLE
- Common System Views and Metadata
- Common Dynamic Management views
- Working with JOINS inside views
- Indexing Table & View Columns
- Materializing Views (storage level)
- Composite Indexed Columns & Keys
- Indexes and Table Constraints
- Primary Keys & Non-Clustered Indexes
- Why to use Stored Procedures
- Types of Stored Procedures
- Use of Variables and parameters
- SCHEMABINDING and ENCRYPTION
- INPUT and OUTPUT parameters
- System level Stored Procedures
- Dynamic SQL and parameterization
- Types of Table Valued Functions
- SCHEMABINDING and ENCRYPTION
- System Functions and usage
- String and Operational Functions
- DML Triggers and Performance impact
- INSERTED and DELETED memory tables
- Data Audit operations & Sampling
- Database Triggers and Server Triggers
- Bulk Operations with Triggers
- Cursor declaration and Life cycle
- FORWARD_ONLY and LOCAL Cursors
- KEYSET Cursors with Complex SPs
- ACID Properties and Scope
- EXPLICIT Transaction types
- IMPLICIT Transactions and options
- AUTOCOMMIT Transaction and usage
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