Databases & data skills.
2,987 databases & data skills, including azure-kusto, google-agents-cli-eval and paper-context-resolver, are listed on Ahel today. Each one has a page of its own that says what it does and whether Ahel can serve it in Claude, Claude Code, ChatGPT, Codex and Cursor.
Category: Databases & data
2,987 results · page 99 of 100
- View details
Drizzle ORMSkillDatabases & data
Expert guidance for Drizzle ORM including schema definition, queries, relations, migrations, TypeScript integration with SQLite/PostgreSQL, and Drizzle Studio. Use this when working with type-safe database operations, schema management, or ORM queries.
Ready to connect
- View details
dsSkillDatabases & data
ALWAYS use for ANY substantive empirical task whose output is a dataset, table, figure or number - \"analyze this data\", \"build the panel\", \"merge these datasets\", \"run the regression\", \"profile this dataset\", \"clean this file up for analysis\", \"make me a summary table\", \"pull the data
Ready to connect
- View details
flyway-consolidateSkillDatabases & data
Analyze and consolidate Flyway SQL migrations into clean, domain-grouped CREATE TABLE migrations for pre-production projects. Use when consolidating database migrations, refactoring Flyway schemas, simplifying migration history, grouping tables by domain, or when user mentions "consolidate migration
Ready to connect
- View details
fuzzy-name-matchingSkillDatabases & data
Use when linking or deduping datasets by entity NAME because no shared key exists — 'fuzzy match', 'fuzzy name matching', 'entity resolution', 'record linkage', 'match company or person names', 'match these on the firm name', 'just merge these on company name', 'dedupe entity names', 'name-based joi
Ready to connect
- View details
gnomad-variantsSkillDatabases & data
Query gnomAD (Genome Aggregation Database) for population allele frequencies, gene constraint scores, and variant annotations to interpret ENCODE regulatory variants. Use when the user needs allele frequencies for variants in ENCODE regulatory elements, wants to assess gene constraint (pLI, LOEUF) f
Ready to connect
- View details
implementing-cdc-with-debeziumSkillDatabases & data
Capture database changes with Debezium change data capture — connector setup for Postgres/MySQL/SQL Server, snapshot vs streaming phases, handling inserts/updates/deletes and tombstones, schema changes, and applying the change stream idempotently to a warehouse/lake. Use when setting up CDC, replica
Ready to connect
- View details
implementing-data-cicdSkillDatabases & data
Set up CI/CD for data pipelines — SQL/dbt linting (SQLFluff), compilation and test gates, dbt Slim CI with state:modified and deferral, environment promotion (dev/staging/prod), and running only changed models on pull requests. Use when adding CI checks to a dbt or SQL project, automating pipeline t
Ready to connect
- View details
injection-checkerSkillDatabases & data
Use when writing database queries, file system operations, shell commands, XML/HTML processing, template rendering, or any operation that incorporates user-supplied input into a command or query. Triggers on: SQL queries, MongoDB queries, Mongoose queries, file path construction, exec/spawn/system c
Ready to connect
- View details
integrative-analysisSkillDatabases & data
Plan and execute integrative analysis combining multiple ENCODE experiments for cross-dataset or multi-omic workflows. Use when the user wants to combine experiments, perform cross-dataset comparison, multi-omic integration, peak overlap analysis, differential binding, signal correlation, chromatin
Ready to connect
- View details
jaspar-motifsSkillDatabases & data
Guide for using JASPAR transcription factor binding profiles with ENCODE ChIP-seq data. Use when users need to find TF binding motifs in ENCODE peaks, validate ChIP-seq targets with known motifs, or scan regulatory regions for TF binding potential. Trigger on: JASPAR, motif database, binding profile
Ready to connect
- View details
managing-data-lineage-openlineageSkillDatabases & data
Capture and use data lineage with OpenLineage and Marquez — emitting run/job/dataset events from Airflow, dbt, and Spark, column-level lineage, and using lineage for impact analysis, debugging, and backfill scoping. Use when setting up data lineage, integrating OpenLineage, tracing what a change bre
Ready to connect
- View details
migrating-legacy-etlSkillDatabases & data
Plan and execute migrations of legacy ETL and data warehouses — stored procedures, SSIS/Informatica, or on-prem warehouses to modern stacks (dbt, Spark, cloud warehouses) — using strangler-fig phasing, parallel runs, and row/aggregate reconciliation. Use when migrating legacy pipelines or warehouses
Ready to connect
- View details
- View details
modeling-dimensional-dataSkillDatabases & data
Design analytics data models using dimensional modeling — star and snowflake schemas, fact and dimension tables, grain declaration, surrogate keys, and slowly changing dimensions (SCD Type 1/2/3). Use when designing a warehouse schema, building marts, choosing a table grain, tracking history, or dec
Ready to connect
- View details
mongodb-atlasSkillDatabases & data
MongoDB Atlas cloud database management including clusters, schemas, aggregation pipelines, and Prisma ORM integration. Activate for MongoDB queries, schema design, indexing, and Atlas administration.
Ready to connect
- View details
optimizing-bigquery-queriesSkillDatabases & data
Reduce Google BigQuery cost and runtime — partitioning and clustering, minimizing bytes processed, avoiding SELECT * and full scans, slot usage and reservations, approximate functions, and materialized views. Use when BigQuery queries are expensive or slow, bytes billed are high, a query scans full
Ready to connect
- View details
optimizing-parquet-storageSkillDatabases & data
Optimize columnar Parquet storage for analytics — file and row-group sizing, compression codecs (Snappy/ZSTD), partitioning and file layout, column pruning and predicate pushdown, dictionary encoding, and fixing the small-files problem. Use when Parquet reads are slow or costly, files are too small/
Ready to connect
- View details
optimizing-pyspark-jobsSkillDatabases & data
Optimize slow or failing PySpark and Spark SQL jobs — partitioning and repartitioning, data skew, shuffles, broadcast joins, caching, Adaptive Query Execution, and avoiding driver collects and Python UDFs. Use when a Spark job is slow, spills, OOMs, has skewed tasks, runs a huge shuffle, or a stage
Ready to connect
- View details
optimizing-snowflake-workloadsSkillDatabases & data
Reduce Snowflake cost and latency — right-size and auto-suspend warehouses, use multi-cluster for concurrency, apply clustering keys, read the Query Profile, exploit result/warehouse caching, and control credit spend. Use when Snowflake queries are slow or expensive, warehouses spill or queue, credi
Ready to connect
- View details
reviewing-data-pipeline-codeSkillDatabases & data
Review data engineering pull requests with a data-specific checklist — idempotency, correct grain, incremental logic, cost impact, data quality tests, PII handling, and backward compatibility — that generic code review misses. Use when reviewing a dbt/SQL/Spark/Airflow PR, a data pipeline change, or
Ready to connect
- View details
rseng-citation-hygieneSkillDatabases & data
Covers verifying that every citation is real, correct and current: checking references in manuscripts, READMEs, references files and code metadata against Crossref and OpenAlex, screening cited DOIs against the Retraction Watch database, catching fabricated or mis-attributed citations (a documented
Ready to connect
- View details
rseng-data-managementSkillDatabases & data
Covers research data management around software: organizing and documenting datasets (layout, data dictionaries), keeping data out of git while versioning it properly (DVC, git-annex, DataLad), FAIR data and metadata standards, depositing data with DOIs in repositories such as Zenodo, licensing data
Ready to connect
- View details
rseng-fair-mlSkillDatabases & data
Covers applying FAIR principles to machine learning artifacts: making models findable and reusable with model cards and rich repository metadata, documenting datasets with Croissant and datasheet-style records, licensing models and weights, linking the model-data-code-paper cluster with persistent i
Ready to connect
- View details
scrna-meta-analysisSkillDatabases & data
Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, lab
Ready to connect
- View details
session-analyticsSkillDatabases & data
Understanding and optimizing Claude Code session performance — token tracking, bottleneck identification, caching behavior, and cost estimation
Ready to connect
- View details
terraform-for-data-infraSkillDatabases & data
Provision data infrastructure with Terraform — warehouses, buckets, IAM/roles, orchestration, and streaming resources — using modules, remote state, workspaces/environments, and safe plan/apply workflows. Use when writing Terraform for Snowflake/BigQuery/Redshift, S3/GCS, IAM, Airflow/MWAA, or Kafka
Ready to connect
- View details
ui-contextSkillDatabases & data
Load context for UI, frontend, navigation, and analytics work. Use when starting any visual, interaction, or engagement task.
Ready to connect
- View details
adabas-postgresql-migrationSkillDatabases & data
Model Adabas files, DDM and FDT definitions, MU and PE structures, packed and unpacked numerics, descriptors, and ISN identity as a PostgreSQL schema, then prove equivalence with recorded reconciliation numbers. Use when designing or reviewing an Adabas to PostgreSQL data migration, mapping legacy f
Ready to connect
- View details
ai-insecure-output-handlingSkillDatabases & data
Exploit apps that trust LLM output — pass model text unsanitized into XSS sinks, SQL, shell, code, or downstream calls. Load when LLM output is rendered as HTML/markdown, executed, or fed to another system. Signals: chatbot output shown with innerHTML/dangerouslySetInnerHTML, "run this code", LLM-ge
Ready to connect
- View details
ai-supply-chainSkillDatabases & data
Attack the ML/LLM supply chain — poisoned models, datasets, plugins, and unsafe model deserialization. Load when an app loads third-party models/weights (HuggingFace, .pt/.pkl/.h5), installs ML deps, uses plugins/extensions, or fine-tunes on external data. Signals: torch.load, pickle model files, mo
Ready to connect
Looking for something else?
Databases & data is one category of skills on Ahel. Browse all skills, or open another category above.