Tableau Desktop · Calculations · LOD · Dashboards
Tableau Training in Bangalore — LOD Expressions, Dashboards & Data Storytelling
Build Tableau views that answer a business question, then control their calculation grain, interaction and publishing—not just their colours.
- Duration
- 20 live hours
- Core skills
- Calculations, LOD and dashboards
- Output
- Interactive decision-focused workbook
- Delivery
- Live online or corporate onsite
What is the Tableau Training course?
Tableau Training is a 20-hour instructor-led course for analysts and BI teams. Participants connect and structure data, build appropriate views, create calculated fields and table calculations, use FIXED, INCLUDE and EXCLUDE level-of-detail expressions, and assemble an interactive dashboard. The course concludes with publishing and review decisions for Tableau Public, Server or Cloud as appropriate to the delivery environment.
Is this the right course for you or your team?
Who it is for
- Analysts beginning with Tableau
- Reporting teams that need stronger calculated fields and LOD skills
- BI practitioners improving dashboard design
- Teams publishing through Tableau Server or Cloud
Situations it fits
- The team can make charts but struggles with analytical calculation
- Granularity changes produce confusing results
- Dashboards contain many sheets but no clear reading path
- Publishing permissions and refresh ownership are unclear
Prerequisites
- Comfort working with tabular data
- No prior Tableau required for the full route
- Tableau Desktop or agreed authoring access installed before labs
- Advanced-only delivery assumes basic chart and filter familiarity
The business problems this course addresses
The course focuses on the analytical and design decisions that separate a useful dashboard from a collection of charts.
| Task | The usual problem | What participants practise |
|---|---|---|
| Choosing a view | The default chart does not match the comparison or relationship. | Choose visual form from the business question and data type. |
| Calculating at the right level | The view and the required metric use different granularity. | Use table calculations or an appropriate LOD expression and test filter behaviour. |
| Building interaction | Users cannot move from summary to explanation. | Design parameters, actions, tooltips and drill paths around the audience’s questions. |
| Publishing responsibly | A workbook is shared without clear data access or refresh ownership. | Document permissions, extracts, schedules and the owner of each source. |
What participants will be able to do
Practise the skills below through course exercises, then check the results and explain how you would apply them to your work.
Build appropriate views
Select and construct charts based on comparison, distribution, relationship, composition or geography.
Create calculations
Use calculated fields, parameters and table calculations for business metrics and comparisons.
Control analytical grain
Apply FIXED, INCLUDE and EXCLUDE LOD expressions and predict how filters affect them.
Design dashboard interactions
Use actions, tooltips and navigation to support a clear analytical path.
Communicate a finding
Arrange views and annotations into a concise narrative for a defined audience.
Plan publication
Identify workbook, permission, extract and refresh decisions for the selected Tableau environment.
Applied to each team’s real work
Business analysts
Performance dashboards, segment comparisons and exploratory analysis.
Customer and marketing analysts
Cohorts, acquisition, retention, campaign and journey views.
Operations analysts
Throughput, service levels, geography, exceptions and trend monitoring.
BI teams
Reusable calculations, governed sources, Server or Cloud publication and handover.
Author, calculate and publish in the environment you use
The authoring labs use Tableau Desktop or an agreed equivalent. Publication depends on the learner or client environment.
Tableau Desktop
by TableauCore authoring environment for views, calculations and dashboards.
- Connecting and exploring data
- Calculated fields and LOD expressions
- Dashboard construction
- Used in
- All core labs and the final dashboard.
- What to verify
- Check aggregation, granularity and filter order rather than assuming the visible result is correct.
Tableau Server or Cloud
by TableauHands-on publication requires suitable client or learner access
Publishing, access, sharing and refresh environment.
- Workbook publication
- Permission planning
- Extract and refresh discussion
- Used in
- Publishing walkthrough when suitable access exists.
- What to verify
- Licensing, site roles, permissions and source connectivity depend on the organisation.
20 hours · 20 live hours
Detailed curriculum
4 modules, each pairing short instruction with guided practice. Sequence and examples can be adjusted after the training-needs discussion; the core outcomes stay the same.
Session 14 hours Foundations and analytical views
- Connections, fields and the marks card
- Dimensions, measures, discrete and continuous fields
- Core chart selection and filtering
Practical activityBuild and explain a three-view performance dashboard.
Session 25 hours Calculated fields, table calculations and parameters
- Conditional, date and string calculations
- Running totals, percent-of-total and period comparisons
- Parameters and dynamic metric selection
Practical activityCreate a KPI scorecard with user-controlled measures.
Session 36 hours LOD expressions and advanced analysis
- FIXED, INCLUDE and EXCLUDE
- Filter order and granularity
- Cohort, first-event and customer-level metrics
Practical activitySolve analytical questions where the calculation grain differs from the view.
Session 45 hours Dashboard design and publishing
- Layout, hierarchy and accessibility
- Filter, highlight and navigation actions
- Server or Cloud publishing and refresh decisions
Practical activityBuild, review and present an interactive executive dashboard.
Need a learning plan around your goals?
Share your experience, stack and goals. The proposal sets out the suitable modules.
Exercises and practical outputs
Participants first answer an analytical question, then justify the calculation and design choices behind the view.
How every module runs
Question
Define the comparison, level of detail and audience.
Calculate
Choose a basic, table or LOD calculation and test its behaviour.
Design
Build a readable view and interaction path.
Publish
Document access, refresh and ownership decisions.
Exercises use representative, non-sensitive examples. Outputs are produced during the workshop for practice and review; anything participants keep is their own working material.
A correct-looking report can still be wrong
Every course treats data quality, calculation review and access control as part of the analytical workflow—not as an optional final check.
Check the current product documentation and your organisation’s data-handling rules before applying these workflows.
Use approved data
Use public, synthetic, sanitised or organisation-approved datasets. Remove personal and confidential fields before using external AI services.
Trace every number
Reconcile row counts, totals, filters, joins and time periods against the source before a report supports a decision.
Review generated logic
Read formulas, DAX, SQL, calculated fields and Python generated with AI. Test boundary cases instead of trusting fluent output.
Publish with controls
Confirm permissions, refresh ownership, data classification and reviewer responsibility before sharing a workbook or dashboard.
How the course is tailored and delivered
Private programmes are adapted around the reports, datasets, tool versions and decisions participants handle at work. Public cohorts use neutral practice data so people from different organisations can work safely.
From first conversation to evaluation
Map the work
Identify participant roles, current skill level, recurring reports and the decisions the training should support.
Confirm the environment
Check software versions, licences, database access, security rules and whether client data may be used in exercises.
Shape the labs
Choose representative datasets and outputs, then set the depth of formulas, modelling, visualisation or code.
Practise and review
Participants build during the session, explain their choices and use a review checklist before presenting the result.
Delivery formats
Public live-online cohort
Best for: Individuals and small teams following a published cohort schedule
Instructor-led sessions run on Zoom with notes, assignments, lab instructions and recordings in the Technovids LMS. Recording access lasts three months after the cohort.
Private corporate programme
Best for: Teams that want their own datasets, reporting standards and delivery calendar
Delivered live online or onsite. Scope, participant count, exercises, materials, support and commercials are confirmed in the written proposal.
Delivery modes
Live online
Interactive instructor-led sessions with screen sharing, guided practice and review. Public cohorts are hosted through Zoom and the Technovids LMS.
Onsite for corporate teams
Delivered at the client location with the same practical curriculum, using approved or sanitised organisational data where appropriate.
Practical training, with people doing the work
A selection of Technovids instructor-led sessions. The photographs show delivery environments, not results attributed to a particular course or client.
Photo 1 of 10: Hands-on session 
Photo 2 of 10: Group photo 
Photo 3 of 10: Hands-on session 
Photo 4 of 10: Group photo 
Photo 5 of 10: Classroom session 
Photo 6 of 10: Group photo 
Photo 7 of 10: Computer-lab session 
Photo 8 of 10: Group photo 
Photo 9 of 10: Classroom session 
Photo 10 of 10: Group photo
Course details at a glance
The published course parameters on one page. Final scope, dates and fees are confirmed in the written proposal.
Discuss your training goals| Course | Tableau Training |
|---|---|
| Duration | 20 live hours, with depth adjusted to starting level and publication scope |
| Audience | Analysts, reporting teams, BI developers and dashboard owners |
| Prerequisite | Comfort with tabular data; prior Tableau not required for the full route |
| Tools | Tableau Desktop; Server, Cloud or Public only where appropriate and available |
| Delivery | Public live online; private live online or onsite |
| Assessment | Calculation labs and an interactive dashboard presentation |
The trainer assigned to your programme
Technovids assigns a trainer whose technical depth and delivery experience fit the agreed curriculum and audience.
Pankaj Rana
Co-founder & Lead Instructor, Technovids Consulting
Pankaj is a co-founder and the lead instructor at Technovids Consulting. His programme work spans practical AI adoption, AI engineering, evaluation, responsible production AI, data analytics and corporate learning design, with an emphasis on hands-on exercises connected to workplace tasks.
Expertise:
- Practical AI adoption
- Prompting and evaluation
- Responsible AI
- Corporate learning design
Junaid Khateeb
AI & Machine Learning Trainer, Strategist and Consultant
Junaid is an AI and machine-learning trainer, strategist and consultant with more than 22 years of training experience. His work combines enterprise AI education, business-centred adoption, responsible AI practices and applied solution design, helping professional audiences connect AI concepts to real organisational needs.
M.E. in Computer Engineering, specialising in Artificial Intelligence · author of programming books on Python, Java and C++
Expertise:
- Enterprise AI and ML training
- AI strategy and adoption
- Responsible AI
- Applied AI solution design
Pradeep Varadarajan
Technical Trainer & Curriculum Architect
Pradeep is a technical trainer and curriculum architect with more than 20 years of experience across enterprise technology, cloud infrastructure and advanced AI systems. He designs practitioner-focused programmes, labs and assessments covering AI, LLM systems, Python and machine learning, translating complex technical subjects into structured learning experiences.
Bachelor of Engineering in Electrical Engineering · instructor-led, virtual and blended delivery
Expertise:
- AI and LLM systems
- Curriculum architecture
- Python and machine learning
- Hands-on lab design
The final trainer assignment is confirmed with the cohort schedule or corporate proposal.
Updated
Organisations we have trained, and participant perspectives
Client relationships and permissioned participant feedback provide context on Technovids delivery. They are not promises of a specific learning or business outcome.
Organisations we have delivered training for
Practical training programmes delivered for learners, professionals and teams across AI, data, cloud, productivity and professional skills.
Participant experiences across workplace roles
What professionals found useful, practical and relevant to their day-to-day work.
- Gauraw DeshmukhData Engineer · Capgemini
Technovids AI training was very practical and well structured. The sessions helped me understand how AI concepts can be applied in real data engineering and business workflows, instead of only learning theory. The trainer explained the topics clearly with relevant examples, which made the learning experience valuable and easy to follow.
- PriyanshaSoftware Developer
The AI training from Technovids helped me gain a better understanding of Generative AI, prompt engineering, and practical AI use cases for software development. The course was clear, interactive, and focused on real-world applications. It gave me confidence to explore AI tools more effectively in my work.
- Sidda RajuData Engineer
Technovids delivered the AI training in a very practical and industry-relevant way. As a data engineer, I found the examples and hands-on discussions useful for understanding how AI can improve data workflows, automation, and decision-making. The sessions were well planned and easy to understand.
- Akshat KabraData Engineer
The AI training program by Technovids was insightful and professionally delivered. It covered important AI concepts in a simple and practical manner, with examples that connected well with data and analytics use cases. The sessions helped me build a stronger foundation in applying AI in real business scenarios.
- MangeshSoftware Engineer · Siemens
Technovids conducted the AI training in a very effective and engaging manner. The sessions were practical, easy to follow, and focused on how AI can be used in real software engineering and business workflows. It was a valuable program for understanding the current direction of AI adoption in the industry.
- ReshuSoftware Developer
Technovids AI training was a very useful learning experience. The course explained AI concepts in a practical way and showed how developers can use AI tools to improve productivity, problem-solving, and application development. The trainer's approach was simple, clear, and focused on industry use cases.
Common questions before planning this course
Answers about the published course. The written proposal records any agreed customisation, delivery details and commercials.
Are public cohorts available for Tableau Training?
Public cohorts are offered live online when dates are published. Submit an enquiry for the next available schedule. A date is not reserved until Technovids confirms the cohort in writing.
What is included for a public-cohort learner?
The Technovids LMS includes session notes, assignments, lab instructions and recordings for three months after the cohort. Completion requirements and the certificate process are explained at the start.
Is a completion certificate provided?
Yes. Learners who meet the stated completion requirements receive a Technovids completion certificate with a unique certificate ID that can be verified on the Technovids website. It is not a vendor certification.
Who provides the laptop, software and licences?
Participants use their own suitable laptop. The required software version, accounts and licences are confirmed before delivery. For private programmes, a sandbox or virtual machine can be scoped separately when needed.
Can the course be delivered for a corporate team?
Yes. The private version can use your approved datasets, reporting standards and business scenarios. Delivery may be live online or onsite, with scope and commercials confirmed in the proposal.
What is an LOD expression in Tableau?
A level-of-detail expression controls the granularity at which a value is computed. Tableau supports FIXED, INCLUDE and EXCLUDE forms. The course uses them when the required business metric is calculated at a different level from the visible chart.
Do I need Tableau Server or Cloud access?
No for the core authoring and calculation labs. Publishing is demonstrated or practised only when suitable Server, Cloud or Public access exists and the dataset is safe for that environment.
Is Tableau Public suitable for company data?
Not for confidential company data. Tableau Public publishes work publicly. Public-cohort exercises use neutral practice data, while private programmes follow the client’s approved publication environment.
Plan your next step with this course
Tell us whether you are enquiring for yourself or a team, which development tasks matter and what access you have. We will confirm suitable delivery options and commercial details in writing.