Self-Service Analytics That Actually Scales
Most self-service pilots shine and then stall on the way to enterprise scale. A practical scaling plan: catalogue, certification, training, telemetry.
Articles from the BIART team on data management, business intelligence, cloud and banking technologies.
Most self-service pilots shine and then stall on the way to enterprise scale. A practical scaling plan: catalogue, certification, training, telemetry.
The three pillars of a modern big-data platform: open-table-format lakehouse, real-time streaming, vector stores. Design decisions for 2026.
Data quality is not a one-off project; it is a programme of measurement, ownership, thresholds and escalation. The framework that makes it operational.
What does analytics mean inside a modern bank? A practical 2026 reference covering layers, regulation, lakehouse, real-time and AI patterns.
In March 2026 the KVKK Board issued comprehensive guidance on AI applications. Alignment with the EU AI Act, explicit consent, automated decision-making and a practical LLM checklist.
Data quality is not an abstract goal — it is governed across six measurable dimensions: accuracy, completeness, consistency, timeliness, uniqueness, validity. Concrete metric formulas and the tooling around them.
PSD3 is maturing in Europe, Türkiye’s Open Banking is in its second year, Azerbaijan has published its own framework. The decisions banks must make on APIs, consent and real-time payments.
By 2026 AI agents have moved from demo to production. Five practical scenarios — from support triage to financial reconciliation — and the architecture decisions that matter.
When the central data team becomes the bottleneck, Data Mesh offers a way out through domain ownership and federated governance. Which organisations benefit, and which traps to watch.
With Snowflake, AWS and Databricks all backing it, Iceberg has become the de-facto standard for open table formats. End of vendor lock-in or new complexity?
Retrieval Augmented Generation grounds the LLM in the organisation's own knowledge base, reducing hallucination and giving every answer a traceable source. The three layers of a well-built RAG system.