Master In Tableau
Unlock the power of data with our Tableau and  SQL Training in Gurgaon! This comprehensive course is designed for data enthusiasts and professionals seeking in-depth training in Tableau and SQL. Dive into the world of data visualization, harnessing the capabilities of Tableau, and mastering SQL for seamless data analysis.
Learn to leverage industry-leading tools such as SQL and Tableau, and understand how to extract actionable insights from complex datasets.
- English
- English, Hindi
Upcoming Batch Weekdays!!!
Starting from 19th April
09:00 am – 1:00 pm Weekends
Fully Interactive Classroom Training
- 90 Hours Online Classroom Sessions
- 11 Module 04 Projects 5 MCQ Test
- 6 Months Complete Access
- Access on Mobile and laptop
- Certificate of completion
65,000 Students Enrolled
What we will learn in data analytics course Gurgaon in palin
- Connection, Navigation, Data Sources
- Data Extraction, Data Prep
- Data Pre-Processing
- Exploratory Data Analytics
- Data Wrangling
- Data Cleansing
- Data Munging
- Statistics For Business Analytics
- Data Analytics
- Strategic Decisions Making
- Data Visualization
Exploring Master in Tableau Training in Gurgaon?
Learning both Tableau and SQL training can significantly enhance your skills as a data analyst, as they serve complementary roles in the data analysis process, training imparted by Palin Analytics Gurgaon will be the best fit as It is a powerful data visualization tool that allows you to create interactive and dynamic visualizations from your data. Tableau education makes it easy to explore and present insights in a visually compelling manner. It excels in visual analytics, enabling you to create a wide range of charts, dashboards, and reports. Tableau’s strength lies in its ability to convey complex insights through interactive visualizations.
In summary, learning Tableau and SQL equips you with a comprehensive skill set for data analysis. SQL helps you manage and manipulate data efficiently, while Tableau course empowers you to visually communicate insights, making you a well-rounded and effective data analyst.
Who can go for this
Want to discuss your roadmap to be a Data Scientist?
Are you interested in pursuing a career as a data analyst, it’s essential to create a roadmap that outlines the key steps and milestones along the way. Becoming a data analyst using Tableau and SQL involves acquiring a combination of technical and analytical skills. Join us for an inspiring conversation in our head office which is in gurgaon where we will deep dive into your own journey and discuss the clear cut roadmap to become a business analyst. Let’s start the journey to be a data scientist in the exciting world of data science together!
Advantages
Countless Batch Access
Industry Expret Trainers
Shareable Certificate
Learn from anywhere
Career Transition Guidance
Real-Time Projects
Industry Endorsed Curriculum
Interview Preparation Techniques
Class recordings
Course Mentor
Vinay mukund
- 10 + Batches
- 4.8 Star Rating
- 159 Students Trained
- 130+ Successfully Placed
Hi I am Vinay and I am super excited that you are reading this.
I’m thrilled to reach out to you as the lead trainer for our upcoming Business Analytics Mastery course. As someone passionate about the transformative power of data, I believe this program will not only enhance your skills but also open new doors to exciting opportunities in the world of business analytics.
From this course you will get to know how I combine my working knowledge, experience and qualification background in computer science to deliver training step by step. Â
what is Course Content of Master in Tableau Course in Palin Analytics Gurgaon
Module 1: Introduction to Excel for Analytics
Overview of Excel as an analytics tool
Importance of Excel in data analysis
Excel interface and basic navigation
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Module 2: Essential Excel Functions for Data Analysis
Understanding and using basic functions (SUM, AVERAGE, COUNT)
Working with mathematical and statistical functions
Text functions for data cleaning and manipulation
Logical functions (IF, AND, OR)
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Module 3: Data Import and Cleaning in Excel
Importing data from various sources (CSV, Excel, databases)
Data cleaning techniques and best practices
Handling missing data
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Module 4: Data Visualization in Excel
Creating basic charts (bar charts, line charts, pie charts)
Formatting and customizing charts
Using sparklines for trend analysis
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Module 5: PivotTables and PivotCharts
Introduction to PivotTables
Creating PivotTables for data summarization
Building PivotCharts for visual analysis
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Module 6: Advanced Excel Functions for Analytics
VLOOKUP and HLOOKUP for data retrieval
INDEX and MATCH functions
Advanced IF statements and nested functions
Using array formulas
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Module 7: Data Analysis with Excel Tables
Introduction to Excel Tables
Sorting and filtering data in tables
Using structured references
Module 1: Introduction to Databases and SQL
Understanding Databases
Definition and types of databases
Relational databases
Non-relational databases
Introduction to SQL
What is SQL?
SQL history and evolution
Importance of SQL in the industry
Module 2: Basic SQL Commands
SELECT statement
Retrieving data from a single table
Filtering data using WHERE clause
Sorting data using ORDER BY clause
INSERT, UPDATE, DELETE statements
Adding, modifying, and deleting data
Data integrity considerations
Module 3: Data Types and Operators
Common SQL data types
Working with text, numeric, and date data
Arithmetic and comparison operators
Module 4: Advanced Querying
JOIN operations
INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
Cross join and self-join
Subqueries
Nested queries
Correlated subqueries
Set operations
UNION, INTERSECT, EXCEPT
Module 5: Data Filtering and Aggregation
GROUP BY clause
HAVING clause
Aggregate functions (SUM, AVG, COUNT, MIN, MAX)
Module 6: Data Modification
Transactions
COMMIT and ROLLBACK statements
Constraints (PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK)
Module 7: Views and Indexes
Creating and managing views
Indexes and their impact on performance
Module 8: Stored Procedures and Functions
Creating stored procedures
Input and output parameters
User-defined functions
Module 9: Database Security
User roles and permissions
GRANT and REVOKE statements
Securing sensitive data
Module 10: Best Practices and Optimization
Writing efficient queries
Indexing strategies
Query optimization techniques
Module 11: Introduction to NoSQL Databases
Overview of NoSQL databases
Contrasting SQL and NoSQL
Module 12: Case Studies and Real-world Applications
Analyzing real-world scenarios
Building practical solutions with SQL
Module 1: Introduction to Tableau
Overview of Tableau
Understanding the Tableau interface
Connecting to data sources
Data source considerations and best practices
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Module 2: Data Preparation and Cleaning in Tableau
Importing and cleaning data
Managing metadata
Joins and relationships
Data blending
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Module 3: Basic Visualization Techniques
Creating basic charts (bar charts, line charts, scatter plots)
Building maps and geographic visualizations
Using size and color in visualizations
Dual-axis charts and combo charts
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Module 4: Intermediate Visualization Techniques
Working with calculated fields
Building hierarchies
Creating sets and groups
Trend lines and reference lines
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Module 5: Advanced Visualization Techniques
Advanced chart types (treemaps, heat maps, box plots)
Dashboard design principles
Storytelling with data
Interactive dashboards and actions
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Module 6: Data Analysis and Calculations
Aggregations and granularities
Window functions
Level of Detail (LOD) expressions
Table calculations
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Module 7: Mapping and Spatial Analysis
Geographic data in Tableau
Customizing maps
Spatial analysis and calculations
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Module 8: Integrating Tableau with Other Tools
Connecting Tableau with Excel, databases, and other data sources
Web data connectors
Tableau integration with R and Python
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Module 9: Data Security and Permissions
User roles and permissions in Tableau
Securing data in Tableau Server and Tableau Online
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Module 10: Tableau Server and Tableau Online
Deploying and managing Tableau Server
Publishing to Tableau Online
Collaboration and sharing in Tableau
What Our Students Say About Us
Data Analytcs Demo classes in Palin Analytics Gurgaon
We are dedicated to empowering professionals as well as freshers with the skills and knowledge which is needed to upgrade in the field of Data Science. Whether you’re a beginner or a professional, our structured training programs are well designed to handle all levels of expertise.
Are you ready to explore your Data Science adventure? Watch a live recorded demo video now and discover the endless possibilities way of teaching, way of handling queries. Awaiting for you at Palin Analytics!
FAQ's
SQL (Structured Query Language) is a popular language used for managing and manipulating relational databases. The difficulty of learning SQL depends on your previous experience with programming, databases, and the complexity of the queries you want to create. Here are a few factors that can affect the difficulty of learning SQL:
Prior programming experience: If you have experience with other programming languages, you may find it easier to learn SQL as it shares some similarities with other languages. However, if you are new to programming, it may take you longer to grasp the concepts.
Familiarity with databases: If you are familiar with databases and data modeling concepts, you may find it easier to understand SQL queries. However, if you are new to databases, you may need to spend some time learning the basics.
Complexity of queries: SQL queries can range from simple SELECT statements to complex joins, subqueries, and window functions. The complexity of the queries you want to create can affect how difficult it is to learn SQL.
Overall, SQL is considered to be one of the easier programming languages to learn. It has a straightforward syntax and many resources available for learning, such as online courses, tutorials, and documentation. With some dedication and practice, most people can learn the basics of SQL in a relatively short amount of time