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DPDP Insights › Central government: ministries and departments › Data and analytics head

DPDP for the Data and analytics head in Central government

Reviewed by InfraVeritas360 ResearchFirst published Last reviewed

Sources: DPDP Act, 2023 and DPDP Rules, 2025 (MeitY) · MeitY · MeitY · MeitY · SFLC.in summary

Scheme dashboards, MIS reports and analysis draw on the same beneficiary data the scheme collects, often in larger copies than anyone else holds.

Written for: Data and analytics head, Central government: ministries and departments. Open this seat in the interactive tool

What is different here

Using scheme data to monitor and improve the scheme generally fits its purpose. Sharing it with researchers, other departments or private parties needs a written basis. Section 17(2) allows exemption for research, archiving or statistics only where it is notified, so do not assume it.

The first four things to sort out

  1. Check the purpose of each analysis against the scheme's purpose.
  2. Use masked or aggregated data by default.
  3. Show counts, not names, on public dashboards.
  4. Give every analysis copy a period in the retention schedule.

A worked example

Data and analytics head

A research institute asks for beneficiary-level data

  1. Day 1The data unit receives a request for three years of beneficiary records for an impact study.
  2. Week 1The nodal officer checks the basis. No exemption is notified for this use, and the scheme guidelines do not cover sharing with researchers.
  3. Week 2The unit offers tables by district and year, with no names or IDs.
  4. AfterAn MoU records the purpose and the tables shared, and notes that no individual records were given.

Evidence kept

  • Request
  • Basis check
  • Aggregated tables
  • MoU

Most research questions can be answered with counts instead of names.

What others in the sector usually do. Some MIS teams now publish district-level counts instead of beneficiary-level lists.

Where it usually goes wrong, by organisation type

Organisation typeHotspots
Ministry of Ports, Shipping and Waterways and its officesPort entry passes with ID copies held by many parties; Seafarer records shared with training institutes and agencies; Terminal operator systems outside the ministry's direct control
Ministry of Road Transport and Highways and its officesBulk or API access by private entities; Accident and challan data; Toll and FASTag transaction data with vendors
Ministry of Chemicals and Fertilizers and its departmentsAadhaar authentication at retailer PoS devices; Farmer purchase data visible to companies and dealers; Kendra operators holding prescriptions and customer details
Other line ministries and departmentsBeneficiary lists published or shared in spreadsheets; System integrators with admin access; Grievance records with personal details
Citizen portals and DBT schemesAadhaar numbers stored outside a data vault; Bulk beneficiary data sent to states by email; Dashboards showing names and amounts publicly
Regulators and statutory bodiesOrders and filings published with personal details; Complaint data shared with regulated entities; Investigation files on shared drives

10 questions the Data and analytics head asks, answered in full

How should scheme systems handle Aadhaar numbers?

Short answer: Vault, mask, never publish

Use Aadhaar only where a law or notification allows it, store the number only in an Aadhaar Data Vault, show it masked on screens and in reports, and never publish it. Core biometric information must never be shared. Authentication devices at the field level need vendor and operator controls.

What the law says

Aadhaar Act Sections 7 and 29 and UIDAI rules, with DPDP Section 8(5). Section 8(5) · Rule 6 · Section 7

Steps
  1. Find every place Aadhaar numbers are stored.
  2. Move them to a vault with reference keys.
  3. Mask on screens, reports and files.
  4. Check PoS and field device vendors.
  5. Log access to the vault.
Evidence to keep
  • Vault design
  • Masking evidence
  • Access logs
Common mistakes
  • Aadhaar in spreadsheets
  • Full numbers on dashboards
  • Field operators keeping copies

Can we share data with states, banks or other ministries?

Short answer: Yes, with a written basis, minimum fields and a log

Yes, where the scheme or a law needs it, through a written MoU or order that sets the purpose, the fields, security and retention. Share the minimum, through logged channels, and record each transfer. Bulk sharing with private parties needs a clear legal basis and should mask personal details where possible.

What the law says

Section 7 bases, Section 8(1) for processors, Section 8(5) for safeguards. Section 7 · Section 8(1)–(2) · Section 8(5) · Rule 6

Steps
  1. List every outgoing data flow.
  2. Write an MoU or order for each.
  3. Cut fields to the minimum.
  4. Use logged channels.
  5. Review flows yearly.
Evidence to keep
  • Flow register
  • MoUs
  • Transfer logs
Common mistakes
  • Email attachments
  • Full data when counts would do
  • No MoU

Can we use customer data for analytics and models?

Short answer: Yes, within the purpose or with consent

Yes, where the use fits the purpose people were told, or you have consent for it. Improving the service people signed up for usually fits. Selling insights, profiling for third parties or targeting children does not. Mask or aggregate wherever the question allows, and give analysis copies their own deletion date.

From your seat: Data and analytics head. Check the purpose before each new analysis. Purpose decides whether you need consent.
What the law says

Section 4 needs a lawful basis for each purpose. Section 6 needs specific consent. Section 9 bars behavioural monitoring of children. Section 8(3) asks for accuracy when data drives decisions. Section 4 · Section 6 · Section 9 · Rules 10, 12 · Section 8(3)

Steps
  1. Write the question and the data needed.
  2. Check the purpose people were told.
  3. Mask or aggregate by default.
  4. Get consent for uses outside the purpose.
  5. Set a deletion date for the copy.
Evidence to keep
  • Purpose checks
  • Data specifications
  • Retention entries
Common mistakes
  • Using all data because it is there
  • Analysis copies with no end date
  • Profiling children

How do we build privacy into a new product or system?

Short answer: Four questions at design, then build the basics in

Ask four questions at the design stage: what personal data, why, for how long, and who sees it. Then build in what the Act assumes: a notice, consent where needed, role-based access, logs of record views, a way to delete, and a way to answer requests. Adding these after launch costs far more.

From your seat: Data and analytics head. Work with masked or aggregated data wherever the question allows.
What the law says

Sections 5 to 12 assume systems that can show notices, record consent, limit access, log, delete and answer requests. Section 5 · Rule 3 · Section 6 · Section 8(5) · Rule 6 · Section 8(7) · Rule 8 · Sections 11–14 · Rule 14

Steps
  1. Add the four questions to design templates.
  2. Drop data you do not need.
  3. Build access roles and record-view logs.
  4. Build deletion and request export.
  5. Register the system in the inventory at launch.
Evidence to keep
  • Design review records
  • Inventory entries
  • Deletion tests
Common mistakes
  • Privacy review only at launch
  • Collecting 'in case we need it'
  • No delete function

Do we need a Data Protection Impact Assessment?

Short answer: Required only for SDFs; good practice for high-risk changes

By law, only Significant Data Fiduciaries must do a yearly impact assessment. For everyone else it is good practice for high-risk changes: new tracking, profiling, large data sharing, children's data or moving data abroad. A short assessment before the change is cheaper than fixing it later.

From your seat: Data and analytics head. Profiling and automated decisions deserve an assessment.
What the law says

Section 10 and Rule 13 require a yearly impact assessment for Significant Data Fiduciaries. Section 10 · Rule 13 · Section 9 · Rules 10, 12 · Section 16 · Rule 15

Steps
  1. Define what counts as a high-risk change for you.
  2. Use a two-page template.
  3. Record the data, purpose, risks and safeguards.
  4. Get the DPO's view before approval.
  5. Keep it with the project record.
Evidence to keep
  • Assessment template
  • Completed assessments
  • DPO views
Common mistakes
  • Treating it as paperwork after launch
  • A 40-page template nobody completes
  • No trigger list

Do we process children's data, and what changes if we do?

Short answer: Check every channel; children often appear where you least expect

Anyone under 18 is a child under the Act. For a child's data you need verifiable consent from a parent or lawful guardian, and you must not track, behaviourally monitor or show targeted ads to children. Some classes and purposes are exempt under Rule 12 and the Fourth Schedule, for example healthcare to the extent needed to protect the child's health, and educational institutions for their educational work.

From your seat: Data and analytics head. No behavioural monitoring of under-18s.
Example in Central government

Scholarship, nutrition and school schemes involve children; Fourth Schedule exemptions may apply to some purposes.

What the law says

Section 9 sets the duties. Rule 10 explains how to verify the parent. Rule 12 and the Fourth Schedule list the exemptions. Section 9 · Rules 10, 12 · Section 6

Steps
  1. Find where children's data enters: customers, dependants, interns, visitors, scholarships, app sign-ups.
  2. Decide whether an exemption in the Fourth Schedule applies to that purpose.
  3. Where none applies, add an age question and a parent-consent step.
  4. Switch off tracking and targeted ads for under-18 users.
  5. Record the decision for each channel.
Evidence to keep
  • Channel-by-channel note on children's data
  • Parent-consent records
  • Ad and tracking settings
Common mistakes
  • Assuming 'we are B2B, so no children'
  • Using the age 13 or 16 from foreign laws
  • Treating a tick-box from the child as parental consent

How long can we keep personal data?

Short answer: For the legal or business period, then erase

Keep data for as long as its purpose needs, or as long as a law requires, and then erase it. Every organisation must keep personal data and logs for at least one year under Rule 8(3). Write a retention schedule by record type, with the law or reason against each period.

From your seat: Data and analytics head. Analytics copies often outlive the source. Give them their own period.
Example in Central government

Record retention schedules under public records rules decide periods.

What the law says

Section 8(7) asks for erasure when the purpose is over, unless a law requires retention. Rule 8(3) sets a one-year minimum for personal data, traffic data and logs. Section 8(7) · Rule 8 · Section 8(5) · Rule 6

Steps
  1. List the record types you hold.
  2. Write the period for each, with the law, regulator rule or business reason.
  3. Set a trigger for the period to start: end of relationship, date of transaction, exit date.
  4. Automate deletion where you can; for paper, schedule shredding.
  5. Keep a deletion log.
Evidence to keep
  • Retention schedule approved by Legal
  • Deletion log
  • Shredding or disposal certificates
Common mistakes
  • 'Keep everything forever' because storage is cheap
  • Deleting before the legal minimum
  • Forgetting email, shared drives and backups

Where does personal data live in our organisation?

Short answer: Start with one row per system

Usually in more places than anyone expects: core systems, email, shared drives, laptops, vendor systems, backups, test copies, spreadsheets and paper. A simple inventory, one row per system, is the base for every other duty.

From your seat: Data and analytics head. Register every data set and its source.
Example in Central government

Start from the scheme list and the systems behind each.

What the law says

Every duty in Sections 5 to 12 assumes you know where the data is. Rule 6 needs safeguards for each system, and Section 11 needs you to find the data when someone asks. Section 8(5) · Rule 6 · Sections 11–14 · Rule 14 · Section 8(7) · Rule 8 · Section 3

Steps
  1. List systems, then shared drives, email, spreadsheets and paper stores.
  2. For each one, note whose data, which items, purpose, owner, hosting location and vendors.
  3. Add copies: backups, test, analytics.
  4. Get each owner to confirm their rows.
  5. Update it whenever a system is bought or retired.
Evidence to keep
  • Data inventory
  • Owner confirmations
  • Change log
Common mistakes
  • A 200-column spreadsheet nobody finishes
  • Leaving out SaaS tools bought by departments
  • No owner for each row

What must a vendor contract say about personal data?

Short answer: Yes, every vendor that touches personal data

You stay responsible for what your vendors do with personal data. The contract should say what data they get, for what purpose, the security they must keep, how fast they must tell you about an incident, that sub-contractors need your approval, and how data is returned or deleted at the end.

From your seat: Data and analytics head. Analytics and cloud vendors receive large copies. Check their terms.
Example in Central government

System integrators, NIC, state agencies and field operators process data for the department.

What the law says

Section 8(1) keeps responsibility with you. Section 8(2) allows a processor only under a valid contract. Rule 6 asks for security terms in that contract. Section 8(1)–(2) · Section 8(5) · Rule 6 · Section 8(6) · Rule 7 · Section 8(7) · Rule 8

Steps
  1. List vendors who receive or can see personal data.
  2. Rank them by how much and how sensitive.
  3. Add a data-protection schedule to each contract, starting with the top ten.
  4. Ask for evidence: certificates, test results, deletion confirmations.
  5. Review the top vendors every year.
Evidence to keep
  • Vendor register
  • Signed data-protection schedules
  • Annual review notes
Common mistakes
  • Relying on the vendor's standard terms
  • No incident-notice time
  • No exit and deletion clause

The sections you will use most

Other rules that sit alongside DPDP

RuleWhat it saysWhat it means alongside DPDPSource
DPDP Act, Section 7(b) and 7(c) with Rule 5 and the Second ScheduleThe State may process personal data without consent to provide a subsidy, benefit, service, certificate, licence or permit, and to perform functions under law. Rule 5 asks that this processing follow the Second Schedule standards: lawful, for the stated use, limited to necessary data, accurate, kept only as long as needed, secured, and with a contact for questions and rights.Consent is not the basis for most scheme work. The standards are, and they need evidence.MeitY
DPDP Act, Section 17(4)For processing by the State, Section 8(7) (erasure) and Section 12(3) (erasure on request) do not apply, and where no decision affecting the person is made, Section 12(2) does not apply either.Retention follows public records rules rather than DPDP erasure. Security, accuracy, breach reporting and grievance duties still apply.MeitY
DPDP Act, Section 17(2)The Central Government may exempt notified instrumentalities for sovereignty, security, public order and related interests, and processing for research, archiving or statistics that does not lead to decisions about individuals.An exemption applies only if notified. Do not assume it.MeitY
RTI Act, Section 8(1)(j), as amended by DPDP Section 44(3) (in force 13 November 2025)Personal information is now exempt from disclosure under RTI, without the earlier public-interest test.Train CPIOs on the new wording; the amendment is being challenged before the Supreme Court, so watch for changes.SFLC.in summary
Public Records Act, 1993 and Public Records Rules, 1997Central government records may be destroyed only under approved record retention schedules.Erasure of personal data in files follows these schedules, since Section 17(4) lifts DPDP erasure for the State.National Archives of India
Aadhaar Act, 2016Section 7 allows Aadhaar for subsidies and benefits. Section 29 limits sharing of Aadhaar numbers and core biometric information. UIDAI asks entities storing Aadhaar numbers to keep them in an Aadhaar Data Vault.Scheme systems should store Aadhaar numbers only in a vault and show them masked.UIDAI
CERT-In Directions, 2022 and IT Act Section 70Report cyber incidents within six hours; keep ICT logs 180 days in India. Systems declared as protected systems under Section 70 come under NCIIPC.Ministries and their portals follow these in addition to DPDP.CERT-In
MeitY Email Policy and IT resources policy for GovernmentOfficial communication should use government email and approved resources.Personal email and chat apps for files with citizen data break both these policies and DPDP safeguards.MeitY
Guidelines for Indian Government Websites (GIGW)Government websites must carry standard policies, including a privacy policy.Update website privacy policies to DPDP notice standards with the contact person.MeitY / NIC
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