数据与 AI技能

MongoDB, Redis, Cassandra, DynamoDB, and distributed database patterns for scalable applications

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Statistics, probability, linear algebra, and mathematical foundations for data science

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Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence.

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Best practices and guidelines for Apache Kafka event streaming and distributed messaging

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Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

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Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

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Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.

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Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms.

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You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.

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Data pipeline architecture, ETL/ELT patterns, data modeling, and production data platform design

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Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

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Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture

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Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.

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Performs numerical and symbolic mathematics using NumPy, SciPy, SymPy, and mpmath. Use when the user needs linear algebra, arrays, optimization, integration, ODEs, symbolic expressions, equation solving, or arbitrary-precision arithmetic.

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Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

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Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.

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Best practices for SciPy scientific computing, optimization, signal processing, and statistical analysis in Python

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SymPy is a Python library for symbolic mathematics that enables exact computation using mathematical symbols rather than numerical approximations.

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SQL query optimization, schema design, indexing strategies, and relational database mastery for production data systems

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Ensure data model/DB designs cover constraints, integrity, indexes, migrations, rollback, and operational impacts.

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Reviews Laravel migrations for destructive operations, change() dropping modifiers, locking index creation on large tables (PostgreSQL), and asymmetric down().

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Ensure designs define data flow, state ownership, consistency boundaries, and cross-boundary writes to prevent drift and incidents.

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Ensure architecture docs define RPO/RTO, failover paths, data consistency, and DR drillability.

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スキーマ/データ移行の安全性を framework 非依存で審査する。破壊的スキーマ変更・ロック誘発・backfill・ロールバック可逆性・expand-contract の段階適用を、prisma / typeorm / Rails / Django / Alembic / 生 SQL などに横断適用する。

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