Excelerate: The Business Analytics Sprint

Route: /courses/excelerate/

Status: Working content draft for review
Purpose: Content architecture, copy direction, SEO starting points, and page-level placeholders
Source basis: WINNOW learning catalogue and Debojyoti Biswas profile documents supplied for the project
Important: Claims, dates, pricing, batch schedules, testimonials, placement outcomes, institutional clients, and certifications must not be published unless verified and approved.

Page purpose

Convert visitors who have an identified need in this subject area by clearly explaining the programme, expected capability, curriculum depth, learner fit and next step.

SEO starting point

Primary topic: Excel business analytics course

Starting keyword batch

SEO caution: Validate volumes and search intent before finalising metadata. Avoid competing with the Courses overview page for broad terms.

Tentative content hierarchy

  1. Hero
  2. Why this programme exists
  3. Who it is for
  4. What you will be able to do
  5. Programme structure and learning approach
  6. Curriculum
  7. Prerequisites and course fit
  8. Instructor credibility
  9. FAQ
  10. Enquiry CTA

Draft page content

Hero

Foundation Track · Excel for Business Analytics

Excelerate: The Business Analytics Sprint

Every business still runs on spreadsheets, but most people use only a fraction of what Excel can do. Excelerate moves from cleaning and organising raw data through advanced calculations, dashboards, optimisation, statistics and automation.

12 live sessions
Format: Live & hands-on
Cadence: Weekly

Primary CTA: Discuss Course Fit
Secondary CTA: View Curriculum

[CONFIRM: session duration, cohort size, online/offline availability, next batch date, fees]

Why this programme

The page should frame the course around a practical capability gap, not around software features alone.

Suggested copy:

Every business still runs on spreadsheets, but most people use only a fraction of what Excel can do. Excelerate moves from cleaning and organising raw data through advanced calculations, dashboards, optimisation, statistics and automation.

The objective is not to cover every possible feature or technique. WINNOW’s broader philosophy is to identify what matters in real work, teach it in a coherent sequence, and remove avoidable noise.

Who this is for

[CONFIRM: whether students/freshers are a primary audience for this specific programme]

What you should be able to do afterwards

Build automated workflows, interactive dashboards and practical analytical models in Excel, turning raw exports into information stakeholders can act on.

Use a short capability list beneath this paragraph. Pull only from the curriculum and avoid unsupported employability claims.

[CONTENT NOTE: Convert curriculum items into 4 to 6 observable capabilities. For example, “clean and combine messy datasets” is stronger than “understand data cleaning”.]

How the programme works

Current source material supports:

[CONFIRM: assignments, office hours, recordings, mentoring, assessments, certificate, community access]

Curriculum

Session 01: Introduction & Business Analytics Foundation

Need for Business Analytics · Types of Analytics · Excel as a Business Analytics Tool

Session 02: Data Cleaning & Preparation

Sort, Filter & Group Data · Text to Columns & Data Validation · Remove Duplicates & Clean Data

Session 03: Formulas & Conditional Formatting

Formula Fundamentals · Logical Functions · Conditional & Custom Formatting

Session 04: Lookup & Reference Functions

VLOOKUP & HLOOKUP · INDEX & MATCH · Combining Lookup Functions

Session 05: Advanced Calculations Fundamentals

Creating Advanced Calculations · Grouping & Summarising Data · Sorting, Filtering & Slicers

Session 06: Advanced Calculation Techniques

Custom Calculations · Calculated Fields & Items · Summary Charts

Session 07: Dashboard Design & Basic Charts

Principles of Dashboard Design · Creating Basic Charts · Dashboard Layout & Storytelling

Session 08: Advanced Charts & Interactivity

Specialised Charts · Form Controls for Interactivity · Developer Tab Essentials

Session 09: What-If Analysis & Optimisation

Goal Seek & Scenario Manager · Solver for Optimisation · Data Tables

Session 10: Statistical Analysis

Descriptive Statistics with Analysis ToolPak · Distributions, Covariance & Correlation · Regression Analysis

Session 11: Macro Automation

Recording & Using Macros · Creating Macros & Subroutines · Automating Repetitive Workflows

Session 12: Final Projects

E-Commerce Sales Dashboard · Restaurant Tips Analysis · Insights & Presentation

Prerequisites and course fit

[CONTENT REQUIRED: final prerequisite statement]

Content guidance:

Instructor

Short trust block:

Debojyoti Biswas brings 19 years of experience across analytics, model risk, AI governance and Generative AI risk and control, with professional experience spanning Wells Fargo, Citi, IBM, Genpact and Infosys.

Link: /instructor/

[APPROVE: exact designation wording and use of employer logos]

FAQ placeholders

  1. Who is this course for?
  2. What prior knowledge do I need?
  3. Is the programme online, offline, or hybrid?
  4. How long is each session?
  5. Will sessions be recorded?
  6. What software or accounts will I need?
  7. Is there a project or capstone?
  8. Will I receive a certificate?
  9. What is the fee?
  10. When is the next cohort?

Do not publish placeholder answers.

Final CTA

Not sure whether Excelerate is the right starting point?

Discuss your current experience, goals and available time before choosing a programme.

CTA: Discuss Course Fit

[CONFIRM: WhatsApp, form, email or scheduling link]

Content/asset requirements