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Centre of Computer Education
Data Analytics Training in Kolkata
science career.
2) Learn Python, analyze and visualize data with Pandas
Matplotlib and Scikit.
3) Create robust predictive models with advanced statistics.
4) Leverage hypothesis testing and inferential statistics for
sound decision-making
Grow Your Data Analytics Skills
The name Data Analytics refers to the act of analyzing datasets in order to derive conclusions from said data. For businesses, the data they collect might be historical data or new information gathered for a specific project. Moreover, the data used can consist of information about an audience’s demographics, interests, behaviors, and more.
In simple terms, a Data Analyst is a person who converts numbers into insights that a business can benefit from. These numbers can come from a variety of sources like sales figures, fixed business costs, advertising rates, market share, customer churn rate, and so on. The bigger the organization, the bigger the numbers and the more acute the need for data analysis or data science. All this can get extremely complicated for the untrained eye. This is where a Data Analytics professional steps in and brings in order and simplicity. He captures the data, aggregates it, wrangles with it, and converts it into a format that is easy to visualize and report. At the end of the day, getting the right data analytics training and becoming a successful data analyst means you will be able to convert data into pure gold for any digitally driven organization!
Need for Data Analytics Training in Kolkata
Data analytics techniques enable a business to take raw data and uncover patterns to extract valuable insights. As a result, data analysis helps companies make informed decisions, create a more effective marketing strategy, improve customer experience, streamline operations, among many other things.
We all know that Data Science is booming and so is data analysis. Put simply, a data analyst is assigned with the goal of helping organizations to make better business decisions. This can fall under the purview of cutting down costs, increasing the returns coming from marketing initiatives, advising the management on entering new geographies, making newer product launches, and so on and so forth. You might not be aware that a data analyst in a large organization can even play a role that is specific to what he does in the organization. So a data analyst in a Fortune 500 company may go by the name of a financial analyst, sales analyst, operations analyst, marketing analyst, and so on.
Course Curriculum
Module 1 - SQL
- Concept of RDBMS
- Datatypes
- Operators
- Create Database
- Select Database
- Rename Database
- Show Database
- Drop Database
- Create Tables ,
- Show Tables
- Rename Tables
- Alter Tables
- Drop Tables
- Delete Tables
- Truncate Tables.
- Sql Queries on Insert
- Select , Update , Delete , Sorting Results
- SQL Views on Create , Update , Rename , Drop
- Sql Operators – Where Clause , Distinct Clause , Order By Clause , Group By Clause , Having Clause , AND & OR
- Inner Join
- Left Join
- Right Join
- Full Join
- Cross Join
- Union vs Join
- One-to-One Relationship
- One-to-Many Relationship
- Many-to-Many Relationship
- Many-to-One Relationship
SQL Keys –
- Primary Key
- Foreign Key
- Alternte Key
- Composite Key
- Unique Key
SQL Functions –
- Date
- String
- Aggregate
- Numeric
- Statistical
- Logical
Quick Contact Form
Module 2 - Python
- Introduction to Python
- Variables
- Data Types
- Numbers
- Casting
- Python String
- Booleans
- Operators
- Loops in Python
- Functions in Python
- Python List
- Tuples
- Sets
- Dictionaries
- Data Frame
- Lambda function
- Arrays in Python
- Python Class/Objects
- Python Inheritance
- File Handling with Python
- Use of Numpy
- Use of Pandas for Data Analysis
- Matplotlib Python Intro
- Matplotlib Pyplot
- Matplotlib Plotting
- Matplotlib Markers
- Matplotlib Line
- Matplotlib Labels
- Matplotlib Grid
- Matplotlib Subplots
- Matplotlib Scatter
- Matplotlib Bars
- Matplotlib Histograms
- Matplotlib Pie Charts
Module 2 - Basic & Advanced Excel For Analytics
- Formulas and Functions: Introduction to Excel formulas , and basic functions (e.g., SUM, AVERAGE, MAX, MIN etc) & Basic Formatting.
- Cell Referencing: Understanding absolute and relative cell references.
- Sorting and Filtering: Sorting data in Excel and using filters to view specific data.
- Charts and Graphs: Creating simple charts and graphs to visualize data.
- Advanced Functions: Learning more advanced functions (e.g., VLOOKUP, HLOOKUP, INDEX-MATCH, CHOOSE , SUMIF, IFERROR , OFFESET).
- Data Analysis Tools: Utilizing data analysis tools like PivotTables, PivotCharts, and Data Validation.
- Conditional Formatting: Applying conditional formatting to cells based on specific criteria.
- Advanced Charting: Creating advanced charts and customizing chart elements.
- Data Import and Export: Importing data from external sources and exporting Excel data to other formats.
- Macros and VBA: Introduction to recording and running macros, as well as using Visual Basic for Applications (VBA) for automation.
- Advanced PivotTable Techniques: Using slicers, timelines, and calculated fields in PivotTables and Creation of Dynamic Dashboard.
Module 4 - Tableau For Data Visualization
- Connecting to Excel, CSV Text Files
- Add Worksheets
- Rename Worksheets
- Save & Delete Worksheets
- Re-order Worksheets
- Custom Data View
- Extracting Data
- Fields Operations
- Data Joining
- Data Blending
- Data Calculations
- Aggregate Calculations
- User Calculations
- Table Calculations
- Logical Calculations
- String Calculations
- Number Calculations
- Iterating Conditions
- Basic Sorting
- Basic Filtering
- Quick Filters
- Context Filters
- Condition Filters
- Filter Operations
- Bar Chart
- Line Chart
- Pie Chart
- Scatter Plot
- Bubble Chart
- Box Plot
- Tree Map
- Bump Chart
- Gantt Chart
- Histogram
- Tableau Dashboard
- Tableau Formatting
- Tableau Forecasting
- Tableau Trend Lines