Data Analytics Courses In Pune
Empower your Career with the Best Data Analytics course
Comprehensive & Competitive Assessments | Qualified & Experienced Data Analytics Trainers | Focus on Practical Learning
Fuel Your Ambition with Expert Guidance
Course Includes
Projects
Assignments
Lifetime Access
Certificate
(Course Completion)
Interview Preparation
(DSA and Soft skills training)
100% Placement Assistance
Data Analytics Course Overview
A Data Analytics Course is a structured educational program designed to provide individuals with essential skills and knowledge for analyzing and interpreting complex datasets. Data Analytics Certification course covers a comprehensive range of topics, including data collection methods, data cleaning techniques, exploratory data analysis, statistical analysis, and data visualization. Participants learn how to utilize various tools and software such as Excel, SQL, Python, and R to process and analyze data effectively. The curriculum typically includes practical exercises and case studies, allowing students to apply theoretical concepts to real-world scenarios. By the end of the course, students are equipped to transform raw data into actionable insights that can drive informed business decisions.
For those just starting out, beginner data analytics courses are specifically designed to introduce fundamental concepts and tools. These entry-level courses provide a solid foundation in data analytics, covering basic techniques and methodologies. They are ideal for individuals new to the field, offering a step-by-step approach to understanding data analysis processes. Whether available online, in-person, or through hybrid formats, these beginner courses cater to a wide range of learners and are a great starting point for anyone looking to enter the data analytics profession.
Why Start a Career in Data Analytics?
Embarking on a career in data analytics course offers a multitude of compelling reasons, driven by the field’s growing importance and broad applicability across industries. As businesses and organizations increasingly rely on data-driven decision-making, the demand for skilled data analysts continues to surge. This demand creates numerous opportunities for professionals to enter a field that is not only dynamic but also critical to strategic operations. Data analytics professionals play a pivotal role in transforming raw data into actionable insights, enabling organizations to make informed decisions that enhance efficiency, drive growth, and foster innovation. By starting a career in data analytics, individuals position themselves at the forefront of a transformative industry that is reshaping the way businesses operate and compete.
For those just starting out, beginner data analytics courses are specifically designed to introduce fundamental concepts and tools. These entry-level courses provide a solid foundation in data analytics, covering basic techniques and methodologies. They are ideal for individuals new to the field, offering a step-by-step approach to understanding data analysis processes. Whether available online, in-person, or through hybrid formats, these beginner courses cater to a wide range of learners and are a great starting point for anyone looking to enter the data analytics profession.
One of the primary motivations for pursuing a career in data analytics is the field’s impressive growth trajectory and job security. As companies across sectors—such as finance, healthcare, technology, and marketing—become increasingly data-centric, the need for experts who can interpret and leverage data is escalating. This rising demand translates into a wealth of career opportunities and competitive salaries for skilled professionals. Additionally, data analytics offers a diverse range of roles and specializations, from data science and machine learning to business intelligence and data visualization, allowing individuals to explore different aspects of the field based on their interests and strengths. The field also provides opportunities for continuous learning and professional development, as technological advancements and evolving data practices continually shape the landscape. By starting a career in data analytics, individuals not only tap into a high-demand profession but also gain the chance to make significant contributions to organizational success and innovation.
Who Can Do a Data Analytics Course?
A data analytics course is designed to be accessible to a diverse range of individuals, regardless of their prior experience or academic background. Beginners interested in the field can start with beginner data analytics courses that cover fundamental concepts and tools, providing a solid foundation for those new to data analysis. For professionals seeking a career change, such as those from finance, marketing, or engineering, data analytics certification courses offer specialized training to pivot into data-centric roles effectively. Additionally, students from related disciplines like computer science or statistics can enhance their skills with data analytics training to broaden their career prospects.
Professionals looking to upskill or enhance their current roles can also benefit from data analytics education. For example, business managers, marketers, and project managers can gain valuable insights into data interpretation, helping them make better decisions and improve strategies. Entrepreneurs and small business owners can leverage insights from data analytics courses to understand market trends and customer behavior, driving informed business decisions and growth. Overall, data analytics courses are tailored to accommodate various needs, equipping individuals with the knowledge and skills applicable across different sectors and job roles.
Career Opportunities for Data Analysts
A career in data analytics opens up a wide range of exciting opportunities across various industries, thanks to the increasing reliance on data-driven decision-making. Data analysts are in high demand due to their ability to transform raw data into actionable insights. Here are some key career opportunities within the field:
- Business Intelligence Analyst:
- Role: Analyzes business data to provide strategic insights, often using skills learned in data analytics courses.
- Responsibilities: Develops dashboards, performs data mining, and identifies trends and patterns.
- Data Scientist:
- Role: Uses advanced analytical techniques, such as those covered in data analytics certification courses, to interpret complex datasets.
- Responsibilities: Builds predictive models, conducts experiments, and delivers actionable insights for business strategies.
- Data Engineer:
- Role: Designs, constructs, and maintains data pipelines, skills typically covered in advanced data analytics courses.
- Responsibilities: Ensures data integrity, develops ETL processes, and manages large-scale data storage solutions.
- Market Research Analyst:
- Role: Specializes in analyzing market trends and consumer behavior, applying techniques from beginner data analytics courses.
- Responsibilities: Conducts surveys, analyzes market data, and prepares reports to guide marketing decisions.
- Financial Analyst:
- Role: Analyzes financial data to support investment decisions, using skills from both basic and advanced data analytics certification courses.
- Responsibilities: Performs financial modeling, forecasts performance, and evaluates risks.
- Healthcare Data Analyst:
- Role: Analyzes healthcare data to improve patient outcomes and support research, often trained through specialized data analytics courses.
- Responsibilities: Examines patient records, monitors healthcare trends, and helps with resource allocation.
- Operations Analyst:
- Role: Enhances efficiency and reduces costs by analyzing operational data, skills that are part of data analytics certification courses.
- Responsibilities: Identifies inefficiencies, develops improvement strategies, and supports operational planning.
- Product Analyst:
- Role: Focuses on product-related data to drive development and enhance user experience, using insights gained from data analytics courses.
- Responsibilities: Tracks product performance, analyzes customer feedback, and provides recommendations for improvements.
- Consultant:
- Role: Offers expert advice on leveraging data for business improvements, often utilizing skills from various data analytics certification courses.
- Responsibilities: Conducts data assessments, develops strategies, and advises on data-related projects.
The field of data analytics continues to expand, offering numerous career opportunities as more industries recognize the value of data-driven insights. Whether you are new to the field or looking to advance your career, data analytics courses and data analytics certification courses provide valuable training and open doors to various roles in the data analytics profession.
Why Choose a Data Analytics Course from ITView?
Opting for a data analytics course from ITView provides a comprehensive and supportive approach to advancing your career in data analytics. Our courses cover both foundational and advanced data analytics skills, incorporating the latest tools and techniques through a hands-on curriculum with real-world case studies. This ensures you gain practical experience and expertise in applying your knowledge effectively.
In addition to technical training, ITView prioritizes holistic career development. We offer soft skills training to enhance your communication, problem-solving, and teamwork abilities. Our dedicated team assists in creating an eye-catching CV and resume, conducts mock interviews to prepare you for real-world scenarios, and provides proactive placement assistance. With our 100% placement guarantee, we also facilitate direct calls for interviews with companies, ensuring you have ample opportunities to secure your desired role. Choosing ITView means not only acquiring essential data analytics skills but also receiving extensive support to launch a successful career in the field.
Confused about how to get a job? Start a career in data analytics. Contact us for detailed insights and get started today!
Data Analytics Certification Course Outline
Duration : 6 months
Sessions :
- Weekdays – 4 per week
- Weekends – 2 per week
Prerequisites :
- There is no such Prerequisites for this course.
- Basic computer knowledge will be advantage.
Database
Python
Advanced Excel
Tableau
PowerBI
Data Analytics Course Curriculum
MySQL Database (SQL)
- What is Data
- What is databases
- What is RDBMS
- Advantages of RDBMS
- Why RDBMS
- Users present in Database
- What is SQL
- Installing MYSQL
- Set up MYSQL Workbench Tool
- CREATE database, table
- Data types in SQL
- ALTER commands
- RENAME table
- DROP ,Truncate commands
- Comments in SQL
- Insert records in table
- Update the table records
- Delete the records from table
- Managing the record in table
- PRIMARY KEY constraints
- FOREIGN KEY constraints
- NOT NULL constraints
- UNIQUE constraints
- CHECK constraints
- DEFAULT
- Autoincrement
- Row Restriction WHERE clause
- Comparison Operators
- Logical Operators
- SQL Operators-LIKE IN NOT NULL
- DISTINCT
- ORDER BY
- Literals Concatenation
- What is a group function
- MIN MAX
- AVG SUM
- COUNT
- GROUP BY clause
- HAVING clause
- What is a Join
- Types of joins
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- SELF JOIN
- What is subquery
- Types of subquery
- Single row subquery
- Multiple row subquery
- Corelated subquery
- ALL ANY Operators
- What is Trigger
- Write a trigger in SQL
- Usage of Trigger
- Read excel data in SQL
Python Programming
- Why Python where to use it?
- Features of Python
- Domains where Python is used
- Python environment Setup
- Discuss about IDE’s like IDLE, Pycharm
- How to work in an interactive shell.
- Identifiers, Keywords in Python
- Operators in Python
- Standard Project Set up
- Variables and Data Types
- Debugging Python Programs using debugger in Pycharm/pdb
- Taking User Input
- Decision or Conditional Statements
- Repeating or Looping Statements and Nested Statements
- break, continue and pass statements
- List with indexing slicing and its behavior
- Tuples its accessing and functions
- Strings accessing and its methods
- Set with only unique data and manipulation
- Dictionary and its functionalities
- How to create a Python function
- Return type functions
- Function with Parameters/Arguments
- Required/Positional arguments
- Keyword/Named Arguments
- Default Arguments
- Variable -length arguments
- Anonymous/Lambda functions
- Map() ,filter() and reduce()
- Iterators and Decorators
- What is a class, Structure of a class,
- Creating Object and Accessing the behavior ,attributes
- Constructors in Python
- Inheritance and its types
- Polymorphism-Overriding
- Abstraction Implementation Hiding
- Encapsulation data hiding
- What is an Exceptions
- How to handle exceptions
- using try….except…else
- Try-finally clause
- Python Standard Exceptions
- Create Custom exception/user defined
- Exceptions raise keyword
- What is a module in Python
- How to access built in Libraries
- Built in Libraries Math/Random Modules
- Describe Packages and directories
- How to import various modules from import statements
- When to use packages and directories
- Date and Time modules
- What are Regular Expressions
- The match and search Function
- Search and Replace feature using RE
- Meta characters with each symbols
- Create a Set for valid regular expression
- What is Multi Tasking?
- What is a thread?
- Thread Life cycle
- Creation of Thread in Python
- Start a thread
- Using Threading Module
- When to use files?
- Create files in Python
- Different file modes for reading, writing ,appending
- os modules for various functions
- Remove and rename a file
- Create directories and sub directories
- Current directory mode /remove directories
- Python MySQL Database Access
- Create Database Connection
- DML and DDL Operations with Databases
- Performing Transactions
- Handling Database Errors
- Disconnecting Database
Advance Excel
- What is Excel and use Excel
- Excel Ranges ,Selection of Ranges
- Conditional Statements
- Operators-Relational and Logical
- Pivoting the data
- Dynamic Array Formuales
- Time and date functions
- Formula based formatting
- Lookup and reference Functions
- Counting Rows and Columns
- Joining data with VLOOKUP
- Selecting List of Items with CHOOSE
- Common Excel Statistical Functions
- Counting Rows and Columns
- Excel Data Analysis-Data Visualization
- Visualizing Data with Charts
- Charts Elements and Chart Styles
- Data Labels
- Quick Layout
Tableau
- Buisness Intelligience Overview
- Introduction to Tableau
- Product Components
- Architecture
- Need of Data Visualization
- Data Connectors
- Data Model
- File Types
- Dimensions & Measures
- Show Me
- Installing Tableau
- Different Tableau versions and pricing
- Look and feel of dashboards created in Tableau
- Joins Supported in Tableau.
- Hierarchy
- Worksheet Options
- File Types
- Heap Map
- Tree Map
- Highlight table
- Symbol Map
- Filled Map
- Scatter Plot
- Data Source Filters
- User Filter overview
- Parameters
- Groups
- Sets Basic.
- Constant Sets
- Computed Sets
- IN Members-Out Members
- Combined Sets
- Aggregated& non Aggregated Values
- Adhoc Calculations
- Types of Calculations (Basic, Table, LOD)
- Calculated Fields
- ZN Function
- How to find No of occurrence of letters?
- Date Functions
- How to find no of days to ship?
- how to find month
- Type Conversions
- Logical Functions
- IIF Function
- User Functions
- Table Calculations
- First()
- Last()
- Index()
- Rank()
- Rank Dense()
- Rank Modified
- Rank Percentile
- Rank Unique
- Running Average
- Windows Functions
- Conditional Colouring using windows functions
- Difference between Normal Aggregation & Windows Aggregations
- Quick Table Calculations – Compute Using Table Across-Pane Across Etc.
- Calculation Assistance
- Table Functions
- Running Total Difference
- Percentage Difference
- Percent of Total Percentile
- Moving Average
- YTD Total
- Compound growth Rate
- Rank Methods- “Competition, Modified Competition, Dense”
- LOD Calculations-Fixed LOD
- Include LOD
- Exclude LOD with examples
- Include
- Exclude LOD
- What is specified dimension & what is view, dimension
- Page Shelf
- Analytics Window
- Constant Line
- Average Line
- Median with quartiles & Totals
- Model (Average with 95% CI, median with 95%, quartile, cluster)
- Custom (Reference Line, Reference Band, Distribution, Band) with examples
- Confidence Interval (CI)
- Clusters
- K-Means
- Clustering
- Forecasting
- 4 Factors of forecasting (Trend, Seasonality, Cyclic Fluctuations, Residues/Noise)
- Forecast Options
- Forecast Models
- Additive
- Multiplicative
- Quality
- Trend Line
- Types (Linear, Exponential, Logarithmic, Polynomial) Options(Linear, Exponential, Logarithmic, Polynomial Degree)
- Box plot
- Dashboards
- Purpose of Dashboard
- Actions
- Highlights
- Action URL
- Select
- Hover
- Menu in Actions with examples
- Device Preview
- Layout manager
- Layout Objects
- Horizontal Vertical
- Objects
- text
- Images Fixed and floating sheets Story
- Caption number dots, etc..
- Data Blending
- Data Blending Example
- Cross-Database Joins
- Data Extracts
- API Integration with tableau
- Javascript from embdedded Analytics Using
- Maps using groups
- Dual axis maps
- YTD MTD QTD Calculations
- How to calculate Last Year Sales
- Current Year Sales
- Current Year Sales
- Advanced Visualization
- Gant Chart Histogram
- Funnel Chart Traditional
- funnel chart Bump Chart
- Waterfall Chart Control Chart.
- . Tableau Online
- User Interface
- Publishing Workbooks
- Data Sources
- Scheduling
- Extract Refresh
- Creating Projects
- Creating Groups
- Users Assigning Permissions to users
- Subscriptions of reports.
- Tableau Online User Filter
- DataSource Filters
- PROJECT
- Dashboards
Power BI
- Introduction To Power BI
- Introduction to Data warehouse
- Data warehouse Tools
- What is Power BI?
- Power BI – Flow of Activity
- Building Blocks of Power BI
- Power BI – Primary Tools : Power Pivot, Power Query, Power View, Power Map, Power Q&A, Power BI Desktop
- PowerBI Desktop
- Power BI Desktop – Install
- Data Sources and Connections
- Connect to Data in Power BI Desktop
- How to use Query Editor in Power BI
- Advanced Data changes and transformation
- Views in Power BI Desktop
- Modeling Data – Manage Data Relationship, Create Calculated Columns, Optimize Data Models
- DataAnalysis Expressions (DAX)
- What is DAX?
- Data Types in DAX
- Calculation Types
- DAX Functions : Date and Time, Time Intelligence, Information, Logical, Mathematical, Statistical, Text, Aggregate Measures in DAX
- Table Relationships and DAX
- Data Visualization
- Why Data Visualization
- Practices for Data Visualization
- Reports in Power BI
- Charts in Power BI (Scatter, Waterfall, Funnel)
- Slicers
- Map Visualizations
- Gauges and Single Number Cards
- Custom Visualization
- What Are Custom Visuals?
- Office Store
- Downloading Custom Visuals
- Importing Custom Visuals in Power BI Report
- KPI Visuals
- Data Binding in Power BI
- Power BI Integration page and Integration
- Data Gateways
- Content packs
- Power BI Report Server
- Power BI Embedded
- Power BI Embedded Conceptual Model
- Workspace Collection
- Dashboard vs Reports
- Creating a Dashboard
- Dashboard Tiles
- Pinning Tiles
- Quick Insights with Power BI
- Power BI Publisher for Excel
- Power BI Q&A
- Power BI Q&A
- Dashboard
- Project
- Project Implementation
- Presentation on Projects
Soft Skills
- Introduction to Soft Skills
- Communication Skills
- Presentation Skills
- Time Management
- Body Language & Etiquettes
- Group Discussions & Interview Skills
- Preparation of CV
- Interview
- Intelligence Skills
- Emotional Intelligence Skills
- Life Skills
- Presentation on Soft Skills
- Body Language & Etiquettes
- Group Discussions & Interview Skills
- Personality Development
- What is personality
- Types of personality
- Elements of personality development
- Goal Settings
- Creativity
- Human Values
- Stress Management
- Workplace Etiquette
- Behavior at work
- Personal etiquette
- Using office utilities and resources
- Postures
- Gestures
- Eye contact
- Self Discovery
- Know yourself
- SWOT – Strength, Weakness, Opportunities, Threats
- Communication
- Verbal Language
- Written Communication
- Speech Clarity
- Modulation of Voice(Tone, Pitch)
- Listening Skills
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