Data Governance - sgml/signature GitHub Wiki

Data Loss Prevention

API How to Recover from Data Loss After Middleware Downtime (Sequenceless CSV Recovery) Prevent Dupe Example CSV Row Example Idempotency Key Idempotency Mapping
Cookies Re‑authenticate users and rebuild sessions from identity provider CSV exports; order irrelevant Unique session IDs; invalidate old tokens session_id,abc123,user_id,42,issued,2026-01-17T17:05Z idemp:cookies:abc123 session_id → user_id
CORS Import CSV of authorized origins; apply policies regardless of row order Request IDs checked against audit trail request_id,789,origin,https://example.com,status,allowed idemp:cors:789 request_id → origin
WebAuthn Re‑issue challenges from CSV of credential bindings; verify against identity store Nonce values ensure one‑time use user_id,42,challenge_nonce,xyz456,verified,true idemp:webauthn:xyz456 challenge_nonce → user_id
WebRTC Re‑establish sessions using CSV of peer metadata; renegotiate without relying on sequence Sequence numbers embedded in rows prevent replay stream_id,12,packet_seq,345,timestamp,2026-01-17T17:06Z idemp:webrtc:12:345 stream_id + packet_seq → timestamp
WebSockets Replay missed messages from CSV broker dump; process by ID not order Message IDs enforce uniqueness message_id,555,channel,updates,payload,order_shipped idemp:websocket:555 message_id → payload
Server‑Sent Events Resume streams using CSV of events with IDs; replay by ID rather than sequence Event IDs skip duplicates event_id,999,type,notification,data,new_comment idemp:sse:999 event_id → data
Fetch API Re‑apply operations from CSV logs; reconcile against backend ground truth Idempotency keys prevent duplication op_id,1234,method,POST,resource,/orders,status,success idemp:fetch:1234 op_id → resource
Service Workers Re‑fetch authoritative assets listed in CSV; order irrelevant Checksums validate uniqueness asset_id,css001,version,2.0,checksum,sha256:abcd1234 idemp:sw:css001:sha256:abcd1234 asset_id + checksum → version
Web Payments API Re‑submit transactions from CSV export; reconcile against processor records Transaction IDs enforce one entry txn_id,pay777,amount,49.99,currency,USD,status,completed idemp:payment:pay777 txn_id → amount + currency
Webhooks Replay webhook deliveries from CSV provider dump; verify signatures per row Signature validation and idempotency keys webhook_id,gh123,event,push,repo,myrepo,signature,sha256:efgh5678 idemp:webhook:gh123 webhook_id → event + repo

Documentation

DataRails

DATABASE DOCUMENTATION TOOLKIT (1996 EDITION)

This guide outlines how to consolidate modular database documentation into a physical, reproducible format using tools available in 1996. It supports traceability, institutional memory, and operational hygiene.

A. ARTIFACT TYPES

A1. UML DIAGRAMS

  • Multiple diagrams showing how different parts of the database relate
  • Printed on letter-size paper, organized by domain or subsystem

A2. SPREADSHEETS

  • Tables listing schema details: table names, data types, constraints, relationships
  • Printed in landscape format for readability
  • Include version and author in footer

A3. PDF SNAPSHOTS

  • Printed versions of database structure at key points in time
  • Used for archival reference and compliance

A4. REFERENCE MATERIALS

  • Dictionary: defines technical terms
  • Glossary: explains domain-specific language
  • Thesaurus: maps synonyms and related concepts

A5. CHANGE LOG

  • Printed log of updates: who made them, when, and why
  • Includes timestamps, initials, and reason for change

B. BINDER STRUCTURE

B1. TAB DIVIDERS

  • Use labeled tabs for each artifact type:
    • "Diagrams"
    • "Schema Tables"
    • "Snapshots"
    • "Glossary"
    • "Change Log"

B2. COVER SHEETS

  • Each section begins with a versioned cover sheet:
    • Title
    • Version number
    • Date
    • Responsible author

B3. PAGE FOOTERS

  • Every page includes:
    • Document ID
    • Revision number
    • Section code (e.g., A2 for Spreadsheets)

C. CROSS-REFERENCING

C1. MASTER INDEX

  • Printed index at the front of the binder
  • Lists all sections and page numbers

C2. REFERENCE CODES

  • Use internal references like:
    • "See Table 3.2 in Schema Tables"
    • "Refer to Diagram D4 in Section A1"

D. DISTRIBUTION & REDUNDANCY

D1. PHYSICAL COPIES

  • Maintain two binders:
    • One active copy for daily use
    • One archival copy in secure storage

D2. TEAM ACCESS

  • Photocopy key sections for individual binders
  • Use interoffice mail or courier for remote teams

D3. UPDATE MEMOS

  • Include printed memos with update instructions
  • Note affected sections and version changes

E. UPDATE PROTOCOL

E1. DOCUMENTATION STEWARD

  • Assign one person to manage updates and binder integrity

E2. REQUEST FORMS

  • Use printed forms to submit documentation changes
  • Include reason, affected section, and proposed revision

E3. MONTHLY REVIEWS

  • Schedule monthly binder audits
  • Reprint and replace outdated sections

Roles

+-----------------------------+
|         CEO                |
|  - Sets governance vision  |
|  - Prioritizes compliance  |
|  - Favors Top-Down models  |
+-------------+--------------+
              |
              v
+-----------------------------+
|     Chief Data Officer      |
|  - Defines governance rules |
|  - Balances control vs agility |
|  - Coordinates Federated models |
+-------------+--------------+
              |
              v
+-----------------------------+
|     Data Architects         |
|  - Lineage-aware modeling   |
|  - Top-Down or Bottom-Up    |
|  - Document schema & flows  |
+-------------+--------------+
              |
              v
+-----------------------------+
|     Data Engineers          |
|  - Build ingestion pipelines|
|  - Often favor Bottom-Up    |
|  - Post-hoc documentation   |
+-------------+--------------+
              |
              v
+-----------------------------+
|     ML/Analytics Teams      |
|  - Use Adaptive governance  |
|  - Prioritize experiments   |
|  - Document features ad hoc |
+-------------+--------------+
              |
              v
+-----------------------------+
|     Business Analysts       |
|  - Interface with dashboards|
|  - Need readable lineage    |
|  - Rely on Federated clarity|
+-------------+--------------+
              |
              v
+-----------------------------+
|     IT Support / Ops        |
|  - Maintain infrastructure  |
|  - Enforce access controls  |
|  - Reference compliance docs|
+-------------+--------------+
              |
              v
+-----------------------------+
|         Janitor             |
|  - Main arbitor of security |
|  - Cleans up data mess      |
|  - Ultimate visibility      |
+-----------------------------+

Examples

National Student Clearinghouse:
  Description: The National Student Clearinghouse offers the NextGen API, allowing institutions to automate transcript ordering and delivery. This API provides a secure, real-time, automated approach to transcript ordering and electronic delivery between the Clearinghouse and your institution's student information system (SIS).
  API Documentation: https://help.studentclearinghouse.org/pdp/knowledge-base/submitting-data-files-through-api/
  GitHub Repository: https://github.com/NationalStudentClearinghouse

Bureau of Labor Statistics:
  Description: The Bureau of Labor Statistics (BLS) provides a Public Data API that allows developers to retrieve published historical time series data in JSON format or as an Excel spreadsheet. The API supports both GET and POST requests and is available in two versions: Version 2.0 (requires registration) and Version 1.0 (open for public use).
  API Documentation: https://www.bls.gov/developers/home.htm
  GitHub Repository: https://github.com/dsagher/Bureau-of-Labor-Statistics-API-Project

Tools

mit_license_tools:
  - name: "OpenRefine"
    description: "A powerful tool for working with messy data and improving its quality. It allows users to clean, transform, and enrich data through a user-friendly interface."
    url: "http://openrefine.org/"

  - name: "Data Quality Tool Kit (DQTK)"
    description: "A suite of tools for assessing and improving data quality, including data profiling, data cleansing, and data validation."
    url: "https://github.com/open-dq/data-quality-toolkit"

  - name: "Apache Griffin"
    description: "An open-source Data Quality framework that provides a comprehensive set of tools for data quality management, including data lineage, data quality measurement, and data quality monitoring."
    url: "https://griffin.apache.org/"

Videos

  1. Apache Atlas Introduction: Need for Governance and Metadata Management
  2. Installation & Configuration of Apache ATLAS Part 2
  3. Installation & Configuration of Apache ATLAS Part 1
  4. Data Governance using Apache ATLAS
  5. Apache Atlas: A Hands-on Course
  6. Apache Atlas Wiki

Prerequisites

data_governance_limits:
  data_quality: "Automation relies on high-quality data. Inaccurate or incomplete data can lead to errors and poor decision-making."
  complexity: "Data governance involves complex processes and policies, making automation difficult with diverse data sources and systems."
  human_oversight: "Human oversight is necessary for complex decision-making, exception handling, and ensuring compliance with regulations."
  integration: "Integrating automated tools with existing systems and processes can be challenging, especially with legacy systems."
  scalability: "Maintaining the scalability of automated governance tools as data volumes grow can be difficult."
  security: "Ensuring automated processes are secure and comply with data protection regulations is crucial."

Apache Atlas

Comparison Chart

Tool License Type Key Features
Apache Atlas Apache License 2.0 Metadata management, data lineage tracking, data cataloging
Amundsen Apache License 2.0 Data discovery, metadata management, collaboration tools
DataHub Apache License 2.0 Data cataloging, metadata management, data lineage tracking
Magda Apache License 2.0 Data cataloging, metadata management, data lineage tracking
Open Metadata Apache License 2.0 Metadata management, data cataloging, data lineage tracking
Egeria Apache License 2.0 Metadata management, data lineage tracking, data cataloging
Truedat Apache License 2.0 Data cataloging, metadata management, data lineage tracking

ENV

environment_variables:
  - METADATA_CLIENT_HEAP: "1024m"
  - JAVA_HOME: "/path/to/your/java"
  - LOG_DIR: "/path/to/your/logs"
  - METADATA_COLLECTOR_ENABLED: true
  - KNOX_ENABLED: true
  - LDAP_ENABLED: true
  - TLS_ENABLED: true
  - KERBEROS_ENABLED: true
  - METADATA_OPTS: "-Xmx1024m"

References