Browse: T

Takats models how asymmetric incentives lead compliance officers to over-report suspicious activity, creating massive false positive volumes that overwhelm the AML system and reduce its effectiveness.

Infrastructure as Code patterns for data platforms: Terraform modules for Kafka clusters, Iceberg catalogs, dbt Cloud projects, and Dagster deployments. State management, CI/CD for infrastructure, and multi-environment strategies.

An argument for operating CI/CD pipelines with production discipline: observability, SLOs, capacity planning, and incident response for the build-and-release path. Treats the development pipeline as a first-class system whose downtime directly blocks engineering throughput.

ETFs have become the dominant vehicle for retail and institutional investing, with global AUM exceeding $15 trillion. This module covers the ETF creation/redemption mechanism (authorized participants, creation baskets, in-kind transfers), how ETF trading affects underlying securities, the role of market makers in ETF pricing, premium/discount dynamics, and 2025-2026 trends including the growth of active ETFs, fixed income ETFs, ETF options liquidity, and regulatory proposals around ETF transparency.

By July 2026, the streaming-first lakehouse (Lakestream) has become the dominant data architecture pattern. The default stack — Debezium for CDC, Kafka for transport, Flink for processing, Iceberg for storage — unifies real-time and batch workloads on a single copy of data. StreamNative's architecture achieves 95% cost reduction by eliminating separate streaming and batch storage. RisingWave collapses CDC, processing, and serving into one system. Flink CDC 3.6.0 delivers enhanced schema evolution for AI pipelines. Multimodal lakehouses (LanceDB) extend the paradigm to vectors, video, and audio.

Law, markets, and data as three layers of one governance system — a governance protocol running in years, an incentive layer running in seconds, and an information substrate running in real time. How the temporal mismatch between them produces regulatory lag, enforcement asymmetry, and feedback loops.

A data catalog is the central inventory of an organization's data assets, enabling discovery, governance, and collaboration. This module covers catalog architecture (metadata ingestion, profiling, classification, search), major platforms (DataHub, Atlan, Alation, Apache Atlas), and 2025-2026 trends including AI-powered automated cataloging, embedding-based semantic search, active metadata, and the convergence of cataloging with data quality and lineage tools.

This article surveys emerging directions in the mathematics of democracy. It uses three case studies --- voting theory, participatory budgeting, and deliberative democracy --- to highlight how contemp

How buy and sell orders meet like haggling at a farmers' market — and why the price of anything is just a public conversation in real time.

The analytics engineering discipline: how dbt and SQLMesh transformed the data workflow, the shift from ETL to ELT, analytics engineering best practices, and the evolving role between data engineering and data science.

The risk-based approach (RBA) is the core methodology of modern AML compliance. This article explains how institutions assess customer risk, segment their portfolios, and allocate resources proportionally.

The risk-based approach (RBA) is the cornerstone of modern AML compliance, requiring institutions to identify, assess, and mitigate money laundering risks proportionally. This module covers the FATF risk-based approach framework, risk assessment methodologies (inherent risk, control effectiveness, residual risk), customer risk scoring models, the calibration of CDD/EDD measures to risk levels, and 2025-2026 trends including automated risk scoring with machine learning, regulatory expectations for dynamic risk assessment, and the integration of RBA with broader enterprise risk management frameworks.

This paper reviews and combines findings from the fields of product and life-cycle analysis [36, 38], the usage of modern transformer- based large language models (LLM) [6], as well as on greenhouse g

AI model lifecycles are commonly understood as a series of technical and organizational processes. Yet once a model enters sustained use, subsequent changes can also affect established user practices

Budget-constrained advertisers commonly rely on two control mechanisms: pacing scales bids, whereas throttling randomizes participation. We prove that, in second-price auctions, these two different me

Trade-based money laundering (TBML) exploits the complexity of international trade transactions to move value across borders, estimated at $800B+ annually. This module covers TBML red flags (over/under-invoicing, phantom shipments, dual-use goods, repeatedly amended letters of credit), trade finance products (L/C, documentary collections, supply chain finance), TBML detection methods (rule-based indicators, anomaly detection on trade data, network analysis of trade parties), and 2025-2026 trends including digital trade platforms improving data quality, the use of AI to detect TBML patterns in bills of lading, and the convergence of TBML detection with sanctions screening for dual-use goods.

Explore trade-based money laundering techniques, sanctions screening frameworks, beneficial ownership transparency, and the 2026 regulatory landscape of geopolitical fragmentation.

TSMC begins volume production of 2nm chips, examining the technical milestones achieved, production yields, customer allocations, and implications for the global semiconductor supply chain and geopolitics.