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Taschenbuch. Zustand: Neu. Neuware - Build a semantic layer that gives BI tools, LLMs, and data agents the same governed business meaning.Giving an AI model access to a warehouse does not guarantee analytically correct answers. Valid SQL can still use the wrong metric, join at the wrong grain, duplicate revenue, misinterpret time, expose restricted data, or produce a different answer from the company dashboard.This practical guide shows how to move stable business logic out of prompts and ad hoc queries and into governed semantic models. You will learn how to design metrics that remain consistent across traditional analytics and AI systems, then implement and operate them with dbt MetricFlow, Cube Cloud, and Snowflake Semantic Views.- Model grain, entities, primary keys, joins, facts, dimensions, measures, and semantic contracts correctly- Prevent fanout, chasm traps, duplicate aggregation, unsafe distinct counts, and ratio errors- Build simple, ratio, derived, cumulative, and conversion metrics with governed time semantics- Implement semantic models with MetricFlow, Cube Cloud, and Snowflake Semantic Views- Prepare metrics for LLMs with descriptions, synonyms, AI context, verified queries, literal resolution, and domain routing- Connect semantic services to applications and agents through SQL, REST, GraphQL, SDKs, and MCP- Design governed MCP tools for metric discovery and semantic querying instead of unrestricted raw SQL- Combine structured analytics with document retrieval, search, and multi-step agent reasoning- Protect AI analytics with RBAC, row security, masking, tenant isolation, identity propagation, and least privilege- Defend against prompt injection, tool misuse, semantic model poisoning, data exfiltration, and unsafe write actions- Test metric behavior with semantic unit tests, paraphrase evaluations, regression suites, and cross-engine contract tests- Control caching, pre-aggregations, materializations, query fanout, latency, concurrency, and agent cost- Govern metric ownership, certification, versioning, deprecation, drift detection, and multi-platform synchronizationThe guide includes extensive SQL, YAML, Python, Shell, JSON, and GraphQL examples that connect semantic concepts to realistic implementation, testing, security, agent integration, and production operations.You will also learn how to build a production semantic trust chain so that transformations, metric definitions, execution engines, access policies, BI tools, and AI agents stay aligned around the same approved business definitions.Grab your copy today and build analytics systems where AI flexibility works on top of governed, testable, and consistent business semantics. …

Taschenbuch. Zustand: Neu. Neuware - Build a private, resilient smart home that keeps working locally across Matter, Thread, Zigbee, Wi-Fi, and Ethernet.Modern smart homes can become fragile when devices depend on cloud services, poorly planned radio networks, or confusing combinations of hubs, bridges, controllers, and protocols. This practical guide shows you how to design Home Assistant as a dependable local control system instead of a collection of disconnected devices.You will learn how the technologies actually fit together, how to choose the right hardware and integration path, and how to troubleshoot failures from the radio layer through IPv6, multicast discovery, Matter fabrics, and Home Assistant automations.- Choose between a Raspberry Pi 5 and x86-64 mini PC and build a reliable Home Assistant host with proper storage, cooling, power, Ethernet, and backups- Design a strong Zigbee mesh with coordinators, routers, parent relationships, channel planning, direct binding, groups, OTA updates, and coordinator migration- Deploy ZHA or Zigbee2MQTT with MQTT while understanding the tradeoffs between each architecture- Run OpenThread Border Router with a dedicated Thread radio and manage Operational Datasets, credentials, preferred networks, and multiple Border Routers- Commission Matter devices over Wi-Fi, Ethernet, and Thread while understanding QR setup, Bluetooth, PASE, CASE, fabrics, access control, and multi-admin sharing- Compare direct Zigbee integration, native vendor integrations, and Matter bridges without assuming the newest option always exposes the most features- Plan IPv6, mDNS, multicast, VLANs, firewalls, Docker networking, and 2.4 GHz coexistence so local discovery and routing remain reliable- Build mixed-protocol automations for lighting, occupancy, climate control, leak protection, locks, sensors, and other local devices- Use dedicated Zigbee and Thread radios instead of unreliable shared-radio shortcuts and diagnose USB interference, weak links, and power problems- Test internet outages, Home Assistant failures, radio loss, Border Router failover, backups, restores, and hardware migration before a real failure occursThe guide includes practical YAML, Shell, MQTT, Docker, and configuration examples that help you turn the architecture into a functioning local system and diagnose problems at the layer where they actually occur.Build a smart home you can understand, maintain, recover, and keep under local control. Grab your copy today. …