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Welcome to HCL GUVI

Hey there! Welcome to HCL GUVI—Grab Your Vernacular Imprint—where tech learning is easy, fun, and curated specially for you. Incubated by IIT Madras & IIM Ahmedabad in 2014 and now part of HCL Group, we're making quality tech education accessible to all.

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KPIs and Dashboard Planning

Lesson 3: KPIs and Dashboard Planning

What is a KPI?

A key performance indicator is a metric selected to monitor progress toward an important objective.

  • A metric becomes a KPI because of its decision-making role, not just because it can be counted.
  • Good KPIs are SMART: Specific, Measurable, Achievable, Relevant, Time-bound.

Metric type

Description

Example

Lagging indicatorMeasures outcomes after they happenMonthly revenue, churn rate
Leading indicatorSignals future outcomesTrial sign-ups, pipeline value
Vanity metricLooks good but doesn't guide decisionsTotal page views with no context
Actionable metricDirectly linked to a decisionCheckout abandonment rate

Define each KPI

Use a KPI definition template so everyone calculates it the same way:

Field

Example: Conversion rate

NameVisitor-to-order conversion rate
Business meaningShare of visitors who place an order
CalculationOrders ÷ unique visitors × 100
Unit%
Time periodWeekly, Monday–Sunday
Data sourceWeb analytics + orders table
Refresh frequencyDaily at 6 AM
OwnerE-commerce manager
ExclusionsInternal traffic, test orders, bots
Target≥ 3.0%

"Active user" can mean very different things across products (logged in? performed a key action?), so define it before comparing teams or months.

Example

Online shop dashboard:

KPI

What it tells you

RevenueOverall commercial performance
Conversion rateHow well traffic turns into orders
Average order valueBasket size
Order countVolume
Refund rateProduct or expectation problems
Delivery time (median, P90)Customer experience

Together, these show both commercial performance and customer-experience issues.

How to plan a dashboard

Step

Action

1. AudienceWho uses it? (executives, managers, operations)
2. DecisionsWhat will they decide using it?
3. KPIsPick 3–7 metrics that support those decisions
4. LayoutMost important KPIs top-left; trends next; breakdowns below
5. ContextAdd comparisons: vs target, vs last period, vs same period last year
6. FiltersOnly those that answer real questions (date, region, product)
7. TestHave real users try it; fix confusion

Dashboard vs report:

Dashboard

One-off report

Monitors ongoing performanceAnswers a specific question
Refreshes automaticallyStatic snapshot
Many users, repeated useA specific audience, used once
Standard KPIsCustom analysis and narrative

Common mistakes

  • Too many metrics: dozens of numbers hide what matters.
  • Vanity metrics with no link to a goal.
  • No comparison: a number with no target or previous period lacks meaning.
  • Too many filters: users get lost.
  • Unclear definitions: different teams interpret the same KPI differently.

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Data Analytics Tutorial

Data Analytics Tutorial

MODULE 1 : Foundations of Data Analytics
lessonIntroduction - Foundations of Data Analytics
lessonWhat is Data Analystics
lessonTypes of Data Analytics
lessonThe Data Analytics Workflow
lessonData Types, Sources, and Structure
lessonTurning a Business Request into an Analytical Question
MODULE 2 : Spreadsheets and Practical Data Handling
lessoniIntroduction - Spreadsheets and Practical Data Handling
lessonUnderstanding Spreadsheet Structure
lessonFormulas and Cell References
lessonEssential Functions for Analysis
lessonSorting, Filtering, and Data Validation
lessonLookups and Pivot Tables
MODULE 3 : SQL for Data Analytics
lessonSQL for Data Analytics - Introduction
lessonDatabases and Your First SQL Query
lessonFiltering, Sorting, and Limiting Results
lessonAggregate Functions and GROUP BY
lessonJoining Related Tables
lessonCASE, Subqueries, and CTEs
MODULE 4 : Python for Data Analytics
lessonPython for Data Analytics Introduction
lessonPython Basics for Analysts
lessonConditions, Loops, and Functions
lessonReading and Inspecting Data with pandas
lessonCleaning and Transforming Data
lessonGrouping, Summaries, and Visualisation
MODULE 5 : Statistics for Data Analytics
lessonStatistics for Data Analytics Introduction
lessonDescriptive Statistics
lessonDistributions, Percentiles, and Outliers
lessonSampling and Uncertainty
lessonHypothesis Testing and Confidence Intervals
lessonCorrelation, Regression, and Causation
MODULE 6 : Data Visualization Reporting and Dashboards
lessonData Visualisation, Reporting, and Dashboards Introduction
lessonChoosing the Right Chart
lessonVisual Design and Avoiding Misleading Charts
lessonKPIs and Dashboard Planning
lessonBuilding Reports in BI Tools
lessonPresenting an Insight and Recommendation
MODULE 7 : Exploratory Data Analysis and Data Cleaning
lessonExploratory Data Analysis and Data Cleaning - Introduction
lessonStarting an Exploratory Data Analysis
lessonMissing Values and Their Meaning
lesson Duplicates, Inconsistent Labels, and Data Types
lesson Outliers and Validation Rules
lessonA Reproducible Cleaning Pipeline
MODULE 8 : Business Product and Marketing Analytics
lessonBusiness, Product, and Marketing Analytics Introduction
lessonSales and Revenue Analytics
lessonCustomer Retention and Churn
lessonMarketing Funnel and Campaign Analytics
lessonProduct Analytics and User Journeys
lessonOperational Analytics and Root-Cause Investigation
MODULE 9 : Advanced Analytics - Forecasting and Machine Learning Basics
lessonAdvanced Analytics, Forecasting, and Machine Learning Basics - Introduction
lessonForecasting and Time-Series Basics
lessonRegression and Classification
lessonClustering and Segmentation
lessonModel Evaluation and Choosing Metrics
lessonOverfitting, Leakage, and Responsible Modelling
MODULE 10 : Data Workflows - Warehousing and Professional Practice
lessonData Workflows, Warehousing, and Professional Practice - Introduction
lessonOperational Databases and Data Warehouses
lessonETL, ELT, and Data Pipelines
lessonAutomation, Scheduling, and Monitoring
lessonDocumentation, Version Control, and Collaboration
lessonPrivacy, Governance, and Ethical Practice
MODULE 11 : Final Lesson: Bringing It All Together
lessonFinal Lesson: Bringing It All Together

Learn via Video Course

Data Analysis and Processing with Python using Pandas - Data Science Course Logo

Data Analysis and Processing with Python using Pandas - Data Science Course

5 hrs

Get in Touch For Details

Data Analytics Tutorial

MODULE 1 : Foundations of Data Analytics
lessonIntroduction - Foundations of Data Analytics
lessonWhat is Data Analystics
lessonTypes of Data Analytics
lessonThe Data Analytics Workflow
lessonData Types, Sources, and Structure
lessonTurning a Business Request into an Analytical Question
MODULE 2 : Spreadsheets and Practical Data Handling
lessoniIntroduction - Spreadsheets and Practical Data Handling
lessonUnderstanding Spreadsheet Structure
lessonFormulas and Cell References
lessonEssential Functions for Analysis
lessonSorting, Filtering, and Data Validation
lessonLookups and Pivot Tables
MODULE 3 : SQL for Data Analytics
lessonSQL for Data Analytics - Introduction
lessonDatabases and Your First SQL Query
lessonFiltering, Sorting, and Limiting Results
lessonAggregate Functions and GROUP BY
lessonJoining Related Tables
lessonCASE, Subqueries, and CTEs
MODULE 4 : Python for Data Analytics
lessonPython for Data Analytics Introduction
lessonPython Basics for Analysts
lessonConditions, Loops, and Functions
lessonReading and Inspecting Data with pandas
lessonCleaning and Transforming Data
lessonGrouping, Summaries, and Visualisation
MODULE 5 : Statistics for Data Analytics
lessonStatistics for Data Analytics Introduction
lessonDescriptive Statistics
lessonDistributions, Percentiles, and Outliers
lessonSampling and Uncertainty
lessonHypothesis Testing and Confidence Intervals
lessonCorrelation, Regression, and Causation
MODULE 6 : Data Visualization Reporting and Dashboards
lessonData Visualisation, Reporting, and Dashboards Introduction
lessonChoosing the Right Chart
lessonVisual Design and Avoiding Misleading Charts
lessonKPIs and Dashboard Planning
lessonBuilding Reports in BI Tools
lessonPresenting an Insight and Recommendation
MODULE 7 : Exploratory Data Analysis and Data Cleaning
lessonExploratory Data Analysis and Data Cleaning - Introduction
lessonStarting an Exploratory Data Analysis
lessonMissing Values and Their Meaning
lesson Duplicates, Inconsistent Labels, and Data Types
lesson Outliers and Validation Rules
lessonA Reproducible Cleaning Pipeline
MODULE 8 : Business Product and Marketing Analytics
lessonBusiness, Product, and Marketing Analytics Introduction
lessonSales and Revenue Analytics
lessonCustomer Retention and Churn
lessonMarketing Funnel and Campaign Analytics
lessonProduct Analytics and User Journeys
lessonOperational Analytics and Root-Cause Investigation
MODULE 9 : Advanced Analytics - Forecasting and Machine Learning Basics
lessonAdvanced Analytics, Forecasting, and Machine Learning Basics - Introduction
lessonForecasting and Time-Series Basics
lessonRegression and Classification
lessonClustering and Segmentation
lessonModel Evaluation and Choosing Metrics
lessonOverfitting, Leakage, and Responsible Modelling
MODULE 10 : Data Workflows - Warehousing and Professional Practice
lessonData Workflows, Warehousing, and Professional Practice - Introduction
lessonOperational Databases and Data Warehouses
lessonETL, ELT, and Data Pipelines
lessonAutomation, Scheduling, and Monitoring
lessonDocumentation, Version Control, and Collaboration
lessonPrivacy, Governance, and Ethical Practice
MODULE 11 : Final Lesson: Bringing It All Together
lessonFinal Lesson: Bringing It All Together

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Resources

Company

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HCL GUVI (Grab Your Vernacular Imprint) Geek Network Private Limited is a leading online learning and skills development company, incubated by IIT Madras and IIM Ahmedabad.

Established in 2014 and acquired by the HCL Group in 2022, HCL GUVI is dedicated to providing effective and high-quality learning and skilling programs that transcend language barriers in technology education. HCL GUVI today is trusted by over 4.8 million users, 20 languages and 2500+ corporate partners.

app storeplay store
Refer & Earn

HCL GUVI (Grab Your Vernacular Imprint) Geek Network Private Limited is a leading online learning and skills development company, incubated by IIT Madras and IIM Ahmedabad.

Established in 2014 and acquired by the HCL Group in 2022, HCL GUVI is dedicated to providing effective and high-quality learning and skilling programs that transcend language barriers in technology education. HCL GUVI today is trusted by over 4.8 million users, 20 languages and 2500+ corporate partners.

app storeplay storeRefer & Earn
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Terms and ConditionsPrivacy Policy

HCL GUVI Geek Network Pvt. Ltd.