43. Trade states and the lifecycle state machine.m4a
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Brochure - ETRM Data Engineering & Analytics_DurgaAnalytics.pdf
Sample_ch01_why_data_modeling_DurgaAnalytics.pdf
ETRM-Demo App.png
ETRM_Demo_App_video.mp4
ETRM-Demo App (Module Labs & Full Source Code)
Guide, Labs & Full Source Code.zip
ETRM-Demo-Complete_DurgaAnalytics.pdf
Contents-ETRM-Demo App.png
01 Data Modeling for ETRM Systems
1. Why data modeling is the foundation of every ETRM system.m4a
2. Entities, attributes, and relationships in trading data.m4a
3. Primary keys, surrogate keys, and natural keys for trades.m4a
4. Normalization to third normal form, and when to stop.m4a
5. The canonical trade entity and its core attributes.m4a
6. Instruments, products, and contract templates.m4a
7. Counterparties, legal entities, and hierarchies.m4a
8. Books, portfolios, strategies, and desks.m4a
9. Locations, delivery points, and geography.m4a
10. Currencies, units of measure, and conversions.m4a
11. Temporal modeling_ business date vs system date.m4a
12. Slowly changing dimensions for reference data.m4a
13. Bitemporal modeling_ valid time and transaction time.m4a
14. The dimensional model_ facts and dimensions for ETRM.m4a
15. Star schema vs snowflake for trading marts.m4a
16. Grain, additivity, and semi-additive P&L facts.m4a
17. Data types, precision, and the cost of rounding.m4a
18. Constraints, referential integrity, and data contracts.m4a
19. Modeling for change_ extensibility without migrations.m4a
20. From logical model to physical schema and DDL.m4a
Module_01_data_modeling_for_etrm_systems_DurgaAnalytics.pdf
Module 01 - Data Modeling for ETRM Systems.mp4
Module 01 - Data Modeling for ETRM Systems.chapters.txt
02 Reference & Master Data Management
21. Reference, master, and transactional data distinguished.m4a
22. Why bad static data is the root of most ETRM incidents.m4a
23. The golden record and single source of truth.m4a
24. Instrument master_ identifiers and cross-references.m4a
25. Counterparty master and the legal-entity hierarchy.m4a
26. Product and commodity taxonomies.m4a
27. Holiday calendars and business-day conventions.m4a
28. Location, hub, and delivery-point reference data.m4a
29. Curve definitions and market-data reference.m4a
30. Survivorship rules and match-merge logic.m4a
31. Data stewardship, ownership, and governance.m4a
32. Versioning static data and effective dating.m4a
33. Change management and four-eyes approval.m4a
34. Data-quality rules, scorecards, and thresholds.m4a
35. Validation gates before data reaches trading.m4a
36. Distributing reference data_ APIs vs replication.m4a
37. Caching, consistency, and staleness trade-offs.m4a
38. Auditability and lineage for static data.m4a
39. Integrating external vendors and feeds.m4a
40. Designing a reference-data service end to end.m4a
Module_02_reference_and_master_data_management_DurgaAnalytics.pdf
Module 02 - Reference & Master Data Management.mp4
Module 02 - Reference & Master Data Management.chapters.txt
03 Trade Lifecycle & Instrument Modeling
41. The trade lifecycle as a sequence of data events.m4a
42. Deal capture_ what is recorded and when.m4a
43. Trade states and the lifecycle state machine.m4a
44. Instrument modeling_ forwards, futures, and swaps.m4a
45. Options, structures, and optionality in data.m4a
46. Physical vs financial trade representation.m4a
47. Legs, schedules, and cash-flow generation.m4a
48. Fixings, resets, and floating-price mechanics.m4a
49. Amendments and the audit of what changed.m4a
50. Novation and assignment as data operations.m4a
51. Termination, unwind, and early settlement.m4a
52. Rollovers and their lifecycle impact.m4a
53. Give-ups, allocations, and block trades.m4a
54. Exercise, expiry, and delivery events.m4a
55. Corporate actions and contract adjustments.m4a
56. Lifecycle events and downstream recalculation.m4a
57. Idempotency and replaying lifecycle events.m4a
58. Modeling exotic and structured trades.m4a
59. Lifecycle integrity checks and reconciliation.m4a
60. A queryable trade-history data model.m4a
Module_03_trade_lifecycle_and_instrument_modeling_DurgaAnalytics.pdf
Module 03 - Trade Lifecycle & Instrument Modeling.mp4
Module 03 - Trade Lifecycle & Instrument Modeling.chapters.txt
04 FpML & Trade Representation
61. Why a standard trade representation exists.m4a
62. FpML in the trade-messaging landscape.m4a
63. XML, namespaces, and schema fundamentals.m4a
64. The FpML document structure and root elements.m4a
65. Parties, trade headers, and identifiers.m4a
66. Product architecture in FpML.m4a
67. Representing swaps and swap streams.m4a
68. Representing options and optionality.m4a
69. Commodity products in FpML.m4a
70. Schedules, calculation periods, and adjustments.m4a
71. Business centers and day-count conventions.m4a
72. Validating FpML against the XSD.m4a
73. XPath and querying trade documents.m4a
74. Mapping FpML to your canonical model.m4a
75. Round-tripping_ canonical back to FpML.m4a
76. Versioning and schema evolution.m4a
77. Confirmation, matching, and messaging flows.m4a
78. Common FpML pitfalls and malformed messages.m4a
79. Performance_ streaming large FpML batches.m4a
80. Building an FpML ingestion pipeline.m4a
Module_04_fpml_and_trade_representation_DurgaAnalytics.pdf
Module 04 - FpML & Trade Representation.mp4
Module 04 - FpML & Trade Representation.chapters.txt
05 Market Data, Curves & Time-Series
81. Market data as the fuel for valuation and risk.m4a
82. Quotes, fixings, and observation data.m4a
83. Time-series data models and storage.m4a
84. Bitemporal market data_ as-of and observation date.m4a
85. Forward curves_ concepts and construction.m4a
86. Bootstrapping a curve from instruments.m4a
87. Interpolation methods and their trade-offs.m4a
88. Seasonality in energy and commodity curves.m4a
89. Volatility surfaces and their representation.m4a
90. Correlation matrices and their data model.m4a
91. Interest-rate and discount curves.m4a
92. FX curves and cross-currency mechanics.m4a
93. Curve versioning and point-in-time retrieval.m4a
94. Handling gaps, spikes, and bad ticks.m4a
95. Market-data validation and quality control.m4a
96. Snapshotting curves for end-of-day.m4a
97. Intraday vs end-of-day market data.m4a
98. Storage formats_ columnar and compression.m4a
99. Serving curves to valuation at scale.m4a
100. A production curve pipeline end to end.m4a
Module_05_market_data_curves_and_time_series_DurgaAnalytics.pdf
Module 05 - Market Data, Curves & Time-Series.mp4
Module 05 - Market Data, Curves & Time-Series.chapters.txt
06 Position & P&L Data Models
101. From trades to positions_ aggregation logic.m4a
102. Position keeping and the position data model.m4a
103. Netting, offsetting, and gross vs net.m4a
104. Exposure by book, desk, and counterparty.m4a
105. Mark-to-market and revaluation mechanics.m4a
106. The P&L data model and its grain.m4a
107. Realized vs unrealized P&L.m4a
108. Daily P&L and the change explanation.m4a
109. P&L attribution_ price, volume, and time.m4a
110. Greeks and sensitivity data.m4a
111. Delta, gamma, vega storage and aggregation.m4a
112. New-trade and amendment P&L effects.m4a
113. Carry, roll, and theta decomposition.m4a
114. FX effects and base-currency conversion.m4a
115. Reconciliation to the trade blotter.m4a
116. Break analysis and P&L integrity checks.m4a
117. Intraday P&L and estimate vs actual.m4a
118. Hypothetical and clean P&L for risk.m4a
119. Aggregation cubes and OLAP for P&L.m4a
120. A reconciling P&L pipeline end to end.m4a
Module_06_position_and_pandl_data_models_DurgaAnalytics.pdf
Module 06 - Position & P&L Data Models.mp4
Module 06 - Position & P&L Data Models.chapters.txt
07 Counterparty, Credit & Limit Modeling
121. Credit risk in trading, from the data up.m4a
122. The counterparty exposure data model.m4a
123. Current exposure and potential future exposure.m4a
124. Collateral, margin, and netting agreements.m4a
125. The legal-entity and credit hierarchy.m4a
126. Limit types_ notional, tenor, and PFE.m4a
127. The limit data model and hierarchy.m4a
128. Limit utilization and headroom computation.m4a
129. Pre-deal vs post-deal limit checks.m4a
130. Real-time limit checking architecture.m4a
131. Breach detection and escalation data.m4a
132. Wrong-way risk and concentration.m4a
133. Settlement risk and Herstatt exposure.m4a
134. Credit valuation adjustment data needs.m4a
135. Aggregating exposure across products.m4a
136. Graph models for entity relationships.m4a
137. Caching exposures for fast checks.m4a
138. Auditing limit changes and overrides.m4a
139. Stress testing exposure and limits.m4a
140. A limit-management service end to end.m4a
Module_07_counterparty_credit_and_limit_modeling_DurgaAnalytics.pdf
Module 07 - Counterparty, Credit & Limit Modeling.mp4
Module 07 - Counterparty, Credit & Limit Modeling.chapters.txt
08 Data Lake, Warehouse & Lakehouse
141. Why platform architecture decides analytics success.m4a
142. Data lake fundamentals and object storage.m4a
143. Data warehouse fundamentals and MPP.m4a
144. The lakehouse pattern and open table formats.m4a
145. Medallion architecture_ bronze, silver, gold.m4a
146. Batch vs streaming ingestion patterns.m4a
147. Schema-on-read vs schema-on-write.m4a
148. Partitioning, clustering, and file layout.m4a
149. Columnar formats_ Parquet and ORC.m4a
150. Open table formats_ Delta, Iceberg, Hudi.m4a
151. ACID transactions on the lake.m4a
152. Time travel and versioned data.m4a
153. The conformed layer and shared dimensions.m4a
154. Gold marts for position, P&L, and risk.m4a
155. Compute engines and separation of storage.m4a
156. Data governance and catalog integration.m4a
157. Cost, performance, and FinOps trade-offs.m4a
158. Security, access control, and row-level policy.m4a
159. Migration patterns from legacy warehouses.m4a
160. A reference ETRM lakehouse architecture.m4a
Module_08_data_lake_warehouse_and_lakehouse_DurgaAnalytics.pdf
Module 08 - Data Lake, Warehouse & Lakehouse.mp4
Module 08 - Data Lake, Warehouse & Lakehouse.chapters.txt
09 Event Sourcing & Audit Trail Design
Module_09_event_sourcing_and_audit_trail_design_DurgaAnalytics.pdf
Module 09 - Event Sourcing & Audit Trail Design.mp4
Module 09 - Event Sourcing & Audit Trail Design.chapters.txt
175. Change data capture from operational stores.m4a
168. Rebuilding state by replaying events.m4a
170. Idempotency and exactly-once semantics.m4a
169. Point-in-time state and temporal queries.m4a
165. Modeling trade events as immutable facts.m4a
179. Testing and validating an event-sourced system.m4a
161. Why trading systems need a perfect audit trail.m4a
162. State-oriented vs event-oriented persistence.m4a
166. Projections and building read models.m4a
173. Snapshots to bound replay cost.m4a
172. Ordering, partitioning, and consistency.m4a
176. Reconciling event streams and state.m4a
177. Compensating events and corrections.m4a
167. CQRS_ separating writes from reads.m4a
163. Events, commands, and the append-only log.m4a
178. Regulatory reconstruction and lineage.m4a
174. The audit trail as a first-class product.m4a
164. The event store and its data model.m4a
180. An event-sourced ETRM core end to end.m4a
171. Event schemas and evolution with Avro.m4a
10 Streaming & Real-Time Risk
Module_10_streaming_and_real_time_risk_DurgaAnalytics.pdf
Module 10 - Streaming & Real-Time Risk.mp4
Module 10 - Streaming & Real-Time Risk.chapters.txt
186. Windowing_ tumbling, sliding, and session.m4a
181. Why real-time changes what a desk can see.m4a
189. Joining trade and market-data streams.m4a
196. Fault tolerance and checkpointing.m4a
184. Stream processing vs batch processing.m4a
187. Event time vs processing time.m4a
200. A real-time risk pipeline end to end.m4a
199. Reconciling streaming with batch truth.m4a
197. Serving real-time data to dashboards.m4a
194. Backpressure and flow control.m4a
188. Watermarks and handling late data.m4a
198. Latency budgets and performance tuning.m4a
190. Maintaining live positions in a stream.m4a
185. Stateful stream processing and local state.m4a
182. Streaming fundamentals and the log abstraction.m4a
183. Producers, consumers, topics, and partitions.m4a
193. Exactly-once processing guarantees.m4a
192. Streaming limit checks and breach alerts.m4a
191. Real-time revaluation on market moves.m4a
195. Scaling and rebalancing consumers.m4a
11 Real-Time Dashboards & Analytics
Module_11_real_time_dashboards_and_analytics_DurgaAnalytics.pdf
Module 11 - Real-Time Dashboards & Analytics.mp4
Module 11 - Real-Time Dashboards & Analytics.chapters.txt
204. Aggregation for interactive drill-down.m4a
211. Latency, caching, and perceived speed.m4a
213. Time-travel and as-of views in the UI.m4a
203. Semantic models and metric definitions.m4a
205. OLAP cubes and pre-aggregation.m4a
219. Reconciling the screen to the books.m4a
208. Position and exposure view design.m4a
215. Handling scale_ thousands of positions.m4a
217. Embedding analytics and self-service.m4a
210. Alerting, thresholds, and notifications.m4a
214. Visualization choices for risk data.m4a
202. The serving layer between data and screen.m4a
207. WebSockets and live data to the browser.m4a
212. Consistency between dashboard and source.m4a
220. A production trading dashboard end to end.m4a
206. Real-time push vs polling architectures.m4a
201. What makes a trading dashboard trustworthy.m4a
218. Observability of the dashboard pipeline.m4a
209. P&L views and attribution drill-down.m4a
216. Access control and data entitlements.m4a
12 Straight-Through Processing (Capstone)
Module_12_straight_through_processing_capstone_DurgaAnalytics.pdf
Module 12 - Straight-Through Processing (Capstone).mp4
Module 12 - Straight-Through Processing (Capstone).chapters.txt
233. Reconciliation at every handoff.m4a
229. The event-sourced backbone of STP.m4a
239. Governance, controls, and audit across STP.m4a
222. The end-to-end flow from capture to settlement.m4a
235. Orchestration and workflow control.m4a
237. Failure handling and dead-letter design.m4a
224. Integrating trade capture and the lifecycle model.m4a
223. Designing the STP pipeline as connected stages.m4a
231. Exception management and the repair queue.m4a
226. Feeding market data and curves into valuation.m4a
227. Computing position and P&L in the flow.m4a
225. Wiring in reference and master data validation.m4a
236. Observability, tracing, and SLAs.m4a
238. Settlement, confirmation, and downstream feeds.m4a
221. What straight-through processing means and why it matters.m4a
232. Straight-through rates and manual-touch metrics.m4a
240. The complete STP reference implementation.m4a
234. Idempotency and safe reprocessing.m4a
230. Streaming versus batch stages in the pipeline.m4a
228. Embedding credit and limit checks inline.m4a