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C-Cube

Centre of Computer Education

Join Master Training on Data Analytics in Kolkata

1) Get hands-on Python Training and accelerate your
Data Analytics Training career.

2) Master SQL required for Data Analytics Training

3) Get professional training on Basic & Advance Excel.
4) Learn the best of Tableau for Data Visualization.

5) Create reports and visualizations using Python ,Excel & Tableau.

Training Partners

Data Analytics Training in Kolkata

What is Data Analytics Training ?

Data Analytics Training takes raw data and turns it into useful information. It uses various tools and methods to discover patterns and solve problems with data. Data Analytics Training helps businesses make better decisions and grow in Kolkata and everywhere.

Companies around the globe generate vast volumes of data daily, in the form of log files, web servers, transactional data, and various customer-related data. In addition to this, social media websites also generate enormous amounts of data. Companies ideally need to use all of their generated data to derive value out of it and make impactful business decisions. Data Analytics Training is used to drive this purpose.
C-Cube provides comprehensive hands-on industry based Training on Data Analytics in Kolkata where students can learn the skills required to be a professional Data Analyst.

Need for Data Analytics Training

The demand for Data Analytics and Data Science , ML Training in Kolkata is growing rapidly due to the city’s expanding role as a technology and business hub in Eastern India. Companies in sectors like IT, finance, retail, healthcare, and e-commerce are increasingly relying on data-driven decision-making, making data analytics skills highly sought-after. Professionals with data analytics skills are essential for processing large volumes of data, identifying trends, and making strategic recommendations to help businesses stay competitive. Consequently, the availability of training in data analytics allows individuals in Kolkata to acquire valuable skills for these high-demand roles, including data analysis, machine learning, and data visualization.

The demand for data analytics courses in Kolkata is growing as businesses rely more on data to make decisions. Learning through a detailed training program helps individuals understand how to collect, organize, and interpret data to solve real-world problems. With industries like IT, finance, and healthcare needing skilled professionals, a data analytics learning course can open doors to exciting career opportunities. Whether it’s for beginners or advanced learners, a data insights workshop equips you with tools and techniques to work with data effectively, making it a valuable skill in today’s job market.

Ways to use Data Analytics

1. Improved Decision Making: Data Analytics Training eliminates guesswork and manual tasks. Be it choosing the right content, planning marketing campaigns, or developing products. Organizations can use the insights they gain from data analytics to make informed decisions. Thus, leading to better outcomes and customer satisfaction.

2. Better Customer Service: Data analytics Training allows you to tailor customer service according to their needs. It also provides personalization and builds stronger relationships with customers. Analyzed data can reveal information about customers’ interests, concerns, and more. It helps you give better recommendations for products and services.

3. Efficient Operations: With the help of Data Analytics Training, you can streamline your processes, save money, and boost production. With an improved understanding of what your audience wants, you spend lesser time creating ads and content that aren’t in line with your audience’s interests.

4. Effective Marketing: Data Analytics Training in Kolkata gives you valuable insights into how your campaigns are performing. This helps in fine-tuning them for optimal outcomes. Additionally, you can also find potential customers who are most likely to interact with a campaign and convert into leads.

What does this Course Offer ?

Course Highlights

Topics Covered

Internship & Certification

Mode of Training

Course Highlights

Topics Covered

Internship & Certification

Mode of Training

Course Curriculum

Module 1 - Python

Level -1

Level- 2

Level - 3

Quick Contact Form

Module 2 - SQL

Level -1 - Introduction to SQL

Level- 2 - SQL Queries

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

Level - 3 - SQL Joins

Level - 4 - SQL Relationships

One-to-One Relationship
One-to-Many Relationship
Many-to-Many Relationship
Many-to-One Relationship

Level - 5 - SQL Types of Keys

Primary Key
Foreign Key
Alternate Key
Composite Key
Unique Key

Level - 6 - SQL Functions

Module -3 - Excel

Level -1 - Basic Excel

Getting Started with Excel

Excel Interface Overview: Ribbon, toolbar, workbook, worksheet basics
Creating and Saving Workbooks: Starting a new workbook, saving options
Basic Navigation: Moving between cells, worksheets, and using shortcuts
Entering Data: Typing and editing text, numbers, dates, and special characters
Basic Formatting: Changing font, color, cell alignment, and styles

Basic Formulas and Functions

Basic Arithmetic Operations: Addition (+), subtraction (-), multiplication (*), division (/)
AutoSum Function: SUM for adding values quickly
Basic Functions: MIN, MAX, AVERAGE, COUNT, COUNTA
Relative vs. Absolute References: Using $ for fixed cell references
Basic Date Functions: TODAY, NOW, YEAR, MONTH, DAY

Data Entry and Editing

Copy, Cut, and Paste: Moving and duplicating data
AutoFill and Flash Fill: Filling series, dates, and patterns automatically
Undo and Redo: Correcting mistakes quickly
Find and Replace: Searching for data and replacing it

Basic Formatting Techniques

Cell Formatting: Number, date, currency, and percentage formats
Conditional Formatting: Highlighting cells based on criteria
Borders and Shading: Enhancing cell visibility and organization
Adjusting Row Height and Column Width: Customizing sheet layout

Basic Charts and Visualization

Introduction to Charts: Types of charts (column, bar, line, pie)
Creating Simple Charts: Selecting data and inserting charts
Formatting Charts: Titles, legends, labels, colors
Basic Data Visualization Tools: Sparklines, data bars, color scales

Data Sorting and Filtering

Sorting Data: Sorting alphabetically, by number, or date
Filtering Data: Using filters to view specific data
Custom Sorting and Filtering Options: Sorting by multiple columns, filtering by conditions

Basic Data Validation and Protection

Data Validation Basics: Creating dropdown lists, restricting data entry
Error Alerts: Customizing error messages for invalid data
Basic Protection: Locking cells and protecting sheets to prevent editing

Introduction to Pivot Tables

Creating a Simple Pivot Table: Organizing and summarizing data
Pivot Table Fields: Row, column, value, and filter fields
Basic Pivot Table Customization: Sorting, filtering, and formatting in Pivot Tables

Basic Printing and Page Layout

Print Setup: Page orientation, scaling, and print area selection
Headers and Footers: Adding titles, page numbers, and dates
Print Preview: Reviewing layout before printing
Page Layout Adjustments: Margins, fit to page, repeating headers

Basic Excel Tips and Tricks

Keyboard Shortcuts: Common shortcuts for efficiency (e.g., Ctrl + Z, Ctrl + C, Ctrl + V)
Freeze Panes and Split Window: Keeping headers visible while scrolling
Basic Troubleshooting: Common error messages and how to resolve them
Introduction to Templates: Using built-in templates for specific tasks

Level- 2 - Advance Excel

Advanced Formulas & Functions

Lookup and Reference Functions: VLOOKUP, HLOOKUP, INDEX, MATCH, INDIRECT
Logical Functions: IF, AND, OR, IFERROR, IFS, SWITCH
Text Functions: CONCATENATE, TEXTJOIN, LEFT, RIGHT, MID, FIND, SUBSTITUTE
Math & Statistical Functions: SUMIF, SUMIFS, COUNTIF, COUNTIFS, AVERAGEIF, AVERAGEIFS
Date & Time Functions: DATE, TODAY, NETWORKDAYS, EOMONTH, YEAR, MONTH, DAY, DATEDIF, TIME
Dynamic Array Functions: FILTER, SORT, UNIQUE, SEQUENCE, SORTBY
Financial Functions: NPV, IRR, PMT, FV, PV

Data Analysis Tools

Pivot Tables: Creating, modifying, grouping, and summarizing data
Pivot Charts: Visualizing Pivot Table data, customizing, using slicers
Data Tables: One-variable and two-variable data tables
Goal Seek and Solver: Optimization and “what-if” analysis
Scenario Manager: Creating, editing, and analyzing scenarios
Data Validation: Dropdown lists, input restrictions, error messages

Data Visualization

Charts and Graphs: Line, bar, pie, area, scatter, combo charts, waterfall, funnel
Conditional Formatting: Rules, icons, color scales, and data bars
Sparklines: Inserting and customizing mini charts within cells
Advanced Charting Techniques: Dynamic charts, combo charts, custom charts
Interactive Dashboards: Using slicers, form controls, and hyperlinks for interactivity

Data Cleaning and Transformation

Text to Columns: Splitting data into separate columns
Remove Duplicates: Identifying and removing duplicate entries
Flash Fill: Automatic pattern recognition for data entry
Power Query: Importing, cleaning, and transforming data from different sources
Error Handling: IFERROR, ISERROR, ISNUMBER, and troubleshooting techniques

Power Pivot and DAX (Data Analysis Expressions)

Power Pivot Basics: Adding data models, relationships, creating measures

Module 4- Tableau

Level -1 - Introduction to Tableau

Overview of Tableau and its capabilities
Installation and setup
Tableau interface overview (shelves, data pane, toolbar)

Level- 2 - Connecting to Data

Data sources and connections (Excel, SQL, CSV, etc.)
Live vs. Extract connections
Data joins and blending
Managing and editing data connections

Level - 3 - Data Preparation and Cleaning

Data types and data roles
Renaming, grouping, and splitting fields
Pivoting data and performing calculations
Using data interpreter and data preparation tools

Level - 4 - Data Visualization Basics

Creating basic charts (bar, line, pie, scatter)
Working with marks, filters, and dimensions
Using shelves (rows, columns, color, size, label)
Sorting, grouping, and drilling down data

Level - 5 - Calculated Fields and Table Calculations

Creating calculated fields
Basic arithmetic, logical, and string functions
Using level of detail (LOD) calculations
Understanding table calculations and quick table calculations

Level - 6 - Formatting Visualizations

Adding titles, captions, and tooltips
Working with colors, fonts, and formatting
Customizing axes and labels
Using shapes and icons in visualizations

Level - 7 - Interactivity in Dashboards

Building dashboards and stories
Adding interactivity with actions (filter, highlight, URL)
Customizing dashboard layout and design
Using device layouts for mobile and desktop

Level - 8 - Data Analysis and Analytics

Adding trend lines, forecasts, and reference lines
Clustering and outlier detection
Using parameters for dynamic analysis
Analyzing data with Tableau Prep

Eligibility Criteria

Best Suited For

IT Professionals
Marketing Professionals
Recent Graduates

Skills & Technology Covered

IIT Bombay Certification for Python

Spoken Tutorial is a multi-award winning educational content portal. Here one can learn various Free and Open Source Software all by oneself. Our self-paced, multi-lingual courses ensure that anybody with a computer and a desire for learning, can learn from any place, at any time and in a language of their choice. All the content published on this website are shared under the CC BY SA license.

Our courses are simple and easy to follow even for a beginner but they also meet the growing needs of the learner. Our engaging digital content ensures that learning happens at all levels – Basic, Intermediate and Advanced. Our content mandates side-by-side practice thereby ensuring that learners are actively learning.

Central Govt. Certification for
Diploma in Data Analytics

National Board of Computer Education is a multi-award winning educational content portal. All the courses are launched after an initial survey. The courses fulfill the requirement of the students. To gain professional qualification, certification and extra classes in career orientation and self-development. After completion of each module the performance of the students is monitored through regular tests to develop their skills. That the students should appear successfully. In the Job market and handle the situation confidently.Our students are employed in reputed organization both in India and Abroad. The key to success in ensuring quality training by the experts. Provide education for the rural youth enabling him to play a part of the global development.

Financial Analytics FAQs

What is Financial Analytics ?

Financial analytics or finance analytics refers to the tools and processes used to observe datasets and get insights into an organization’s financial performance. It provides valuable details about an organization’s financial data that helps make strategic decisions to improve its overall performance. When it comes to enterprise performance management and business intelligence, financial analytics significantly influences all aspects of the business. It plays an important role in the evaluation of profits, answering business-related queries, and future business forecasting.

Financial analytics provides meaningful analysis of a company’s financial report that helps its shareholders, stakeholders, and management make appropriate decisions. This is done by combining internal financial data with external data from social media, demographics, and big data sources. It shapes business strategy through reliable and factual insight rather than intuition.

What are the eligibility requirements for Financial Analytics course ?

You must meet the following requirements to be admitted to the Data Science and ML Course :

A bachelor’s degree/ Class 12 passed with a grade point average of at least 50%.
Understanding the fundamentals of coding and Accounts.

What are the types of Financial Analytics ?

Client Profitability Analytics distinguishes between clients who generate revenue for a company and those who do not.
Product Profitability Analytics refers to evaluating each product individually rather than determining overall profitability at a company.
Cash-flow Analytics predicts cash flow using the working capital ratio and cash conversion cycle.
Predictive Sales Analytics include forecasting sales using correlation analysis or past trends.

What are the benefits of Financial Analytics course ?

Fraud Detection and Prevention
Financial institutions use machine learning tools to identify unusual consumer behaviors. This helps banks respond quickly to reduce losses for both businesses and consumers. For example, with the rise of cybercrime, many banks have implemented algorithms to detect fraudsters from their unusual activities and put an end to their activity.
Predictive Analytics and Planning
The algorithms of predictive analytics use various data, such as customers’ past payment records, current financial strength, market conditions, and so on, to predict whether a customer will pay on time or not. This type of data helps the companies identify doubtful debts and debtors so they can mark their books accordingly.
Staying Competitive
The technological revolution is affecting every business and motivating them to outperform the competition. Financial analytics tools are versatile, automated, and can be integrated easily with existing systems. Business users can improve their efficiency and focus on the core task that requires cognitive skills.

What is the scope of Financial Data Analytics ? ?

The scope of a financial reporting analyst’s work is wide-ranging and involves working with a variety of financial data, including budgets, forecast models, and financial ratios. They may also be responsible for monitoring and analyzing market trends in order to inform business decisions

What skills can be learnt from Data Science & ML course ?

Critical technical skills you will need when working in financial analytics include a range of accounting skills, such as bookkeeping, technical analysis, forecasting, and budgeting. Software and tools like Excel and other spreadsheets are also critical in record keeping and analysis. You may use various skills depending on where you work and the individual or organization’s goals. More specific technical skills include:

Who can learn or go for Financial Analytics Training ?

Anyone who is good with numbers, analytical, and a problem-solver can learn financial analytics. Some skills that are helpful for a career in financial analytics include:

Strong quantitative skills
Strong analytical skills
Strong computer skills
Good presentation skills
Good decision-making ability
Problem-solving ability
Adeptness in the use of logic
Detail oriented
Decent communication skills