Skip to content
PROGRAM 36 · TEAM TRAINING

AI & Data for Data & MIS Teams

Stop copy-pasting reports. Build reports that update themselves.

8 sessions3 modules4 hands-on projects3 days · 9 am–5 pmCertificate on completion
CHOOSE A FORMAT
Request a proposalSee the curriculum

Who this course is for

  • MIS officers, data analysts and reporting executives
  • Business intelligence and dashboard developers
  • Planning, performance and monitoring teams
  • MIS teams in banks, NBFIs, RMG, telecom, FMCG, NGOs and government projects

What your team will be able to do

  • Write and test Excel formulas, Power Query steps and SQL with AI help
  • Turn monthly reports that take days into refreshable reports that take minutes
  • Write management commentary that explains the numbers, not just repeats them
  • Deploy four working automations for your own MIS function
How it runs

3 days at your office, 8 sessions

Three sessions a day plus a hands-on build lab every afternoon. Day 3 ends with capstone presentations.

Day 1

9:00 am – 5:00 pm

AI chatbots for MIS work

9:00–10:30S1Prompt engineering for MIS
10:30Tea break
10:45–12:15S2SQL, formulas & code with AI
12:15Lunch & prayer
1:00–2:30S3Report commentary & stakeholder requests
2:45–4:30LABBuild lab: SQL library and data dictionary on your files
4:30–5:00Q&A and day recap

Day 2

9:00 am – 5:00 pm

Analysis, then the first two builds

9:00–10:30S4Formulas & MIS data cleaning
10:30Tea break
10:45–12:15S5MIS analytics & management narrative
12:15Lunch & prayer
1:00–2:30S6Projects 01 & 02: Assistant and alerts
2:45–4:30LABBuild lab: dashboard, assistant and alerts on your data
4:30–5:00Q&A and day recap

Day 3

9:00 am – 5:00 pm

Last two builds and the capstone

9:00–10:30S7Project 03: Report & data access requests
10:30Tea break
10:45–12:15S8Project 04: Source file validation
12:15Lunch & prayer
1:00–3:00LABCapstone build clinic
3:15–4:30LABCapstone presentations
4:30–5:00Certificates and next steps
Group: 10–40 people from one organisationSame content and projects in both formatsBangla delivery with English technical termsEvery session ends with a deliverable
Curriculum

8 sessions, one build in each

3 modules · 8 sessions · 4 hands-on projects

PART 1AI Chatbots for MIS WorkSessions 1–3

Chatbot Landscape & Tool Selection

  • Gemini, ChatGPT, Claude, Copilot and DeepSeek: strengths for MIS work (SQL and formula writing, data dictionaries, report commentary, long technical documents)
  • Free vs paid tiers; a workflow that needs no international payment card
  • Bangla vs English output quality; when to draft in English and translate
  • Which tool for a long document, which for a formula, which for a polished letter

Prompt Engineering Fundamentals

  • What a prompt is; why the same question gives different answers
  • The four-part structure: role, context, task, output format
  • Role prompting: act as an MIS analyst, BI developer, SQL reviewer or data quality officer
  • Controlling output: length, tone, language, table or bullet format

Advanced Prompting Techniques

  • Few-shot prompting: teaching the model with examples of your own MIS work
  • Step-by-step reasoning for multi-part tasks such as reconciling two systems that give different totals for the same month
  • Constraint prompting: what to include, what to exclude, what to never assume
  • Chained prompts: breaking a monthly MIS pack (extract → clean → reconcile → analyse → comment → distribute) into a sequence of smaller steps

Iteration & Prompt Library Building

  • Why the second prompt matters more than the first; refining instead of restarting
  • Diagnosing a bad output: vague instruction, missing context or wrong tool
  • Building reusable prompt templates for repeated MIS tasks
  • Testing a prompt before it goes into daily use

Data Privacy & Verification Discipline (Core)

  • What must never be pasted: customer-level records, account and NID numbers, database connection strings and passwords, unreleased financial results, staff salaries
  • Anonymising data before prompting; safe vs unsafe MIS use cases
  • Hallucination awareness; verifying every figure, date, name and legal reference
  • The verification rule: AI drafts, a person checks before anything leaves the building
DELIVERABLEa personal prompt library of 10 templates for your repeated MIS tasks.
PART 2MIS Data Analysis in Excel & Google SheetsSessions 4–5
PART 3Applied Projects: AI Assistants & AutomationSessions 6–8
Applied projects

Four automations, running in your organisation

01Session 6

Data Definitions & Report Assistant

Report users and new analysts ask what a KPI means and get an answer from your data dictionary and report specifications, with the section cited.

  1. INKPI definitions & data dictionary
  2. AIGrounded Gemini assistant
  3. OUTAnswer with the section cited
Built with Google AI Studio
02Session 6

Report Calendar & Return Alerts

Scheduled report deadlines, regulatory returns, MIS pack dates and licence renewals checked daily, with alerts 30, 15 and 7 days ahead.

  1. INReport calendar tracker
  2. RUNDaily Make scenario
  3. OUTAlert to the responsible owner
Built with Make · Sheets · Gmail
03Session 7

Report & Data Access Request Workflow

Report and data access requests routed to the requester's head, then the MIS lead, with a second approval for sensitive data.

  1. INReport & access request form
  2. RULESApproval routing script
  3. OUTLogged in the request register
Built with Apps Script · Forms
04Session 8

Source File Intake & Validation

Branch and field office files checked against the expected template and control totals, with missing offices flagged and only validated files loaded.

  1. INBranch & field report files
  2. AIGemini extraction & checks
  3. OUTValidated master dataset
Built with Gemini API · Drive

Capstone presentation

Each person presents one automation built for their own workplace.

Day 3 afternoon
Applied across every session

Responsible & Ethical AI in MIS

Fairness & Non-Discrimination

  • Where bias enters MIS decisions: data, wording, criteria and past patterns
  • Proxy discrimination: address, age, gender or background inferred indirectly

Privacy & Data Protection

  • Data minimisation: collect only what the decision requires
  • Retention and deletion of customer, staff and transaction data

Data Integrity & Honest Reporting

  • Never adjusting numbers to match what management hopes to see
  • Disclosing data gaps, estimates and known errors in every report

Accountability & Human Oversight

  • Human-in-the-loop by design: AI recommends, a named person decides
  • Who owns an AI-assisted decision when it is challenged

Workforce Impact & Your AI Use Policy

  • Talking to MIS teams about AI without triggering job-loss fear
  • Reskilling and role redesign as AI absorbs routine work
Outcomes

By the end, your team can

  • Choose the right AI tool and write prompts that work first time
  • Maintain a prompt library covering your repeated MIS tasks
  • Write and test SQL, Power Query and DAX with AI support
  • Turn manual monthly reports into refreshable, quality-checked reports
  • Write management commentary that explains what the numbers mean
  • Build and deploy automations with Make, Apps Script and the Gemini API
  • Apply fairness, transparency and privacy to every AI-assisted decision

And leaves with

A tested SQL query library and a data dictionary
A refreshable cleaning model with data quality checks
A management dashboard with commentary
A grounded data definitions & report assistant your colleagues can use
A report calendar & regulatory return alert engine that reaches the right owner
Four deployed automations running in your own organisation
A written AI use policy for your own MIS and data team

Tools your team will use

Chatbots
ChatGPTGeminiClaudeCopilotDeepSeek
Content
CanvaGammaCapCutGoogle Slides
Data
Microsoft ExcelGoogle SheetsPower Query
Workspace
GmailCalendarMeetFormsDrive
Automation & AI builds
MakeGoogle AI StudioApps ScriptGemini API
MIS tools
Power BISQL client (SQL ServerMySQL or PostgreSQL)Looker Studio

What participants need

  • A laptop with Excel and a Google account
  • Working Excel (Pivot Tables, lookups); basic SQL helps but is not required
  • One real work file to practise on from Session 2
  • No coding background required; free tiers only

How your team will learn

  • build-along classes (you work while the trainer works)
  • practise on your own workplace file, not dummy data
  • every session ends with a deliverable
  • Bangla delivery with English technical terms
  • recordings, prompt library and setup guides
  • certificate after capstone submission
Request a proposal

Bring this program to your MIS team

Tell us about your team. We reply within one working day with a plan built around your own documents and workflows.

  1. 1 · A short discovery call with your MIS lead
  2. 2 · We tailor examples to your masked files
  3. 3 · Offline at your office, or online live classes
Chat on WhatsApp
Request a proposal