Results for “data processing”

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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Expert fintech engineer specializing in financial systems, regulatory compliance, and secure transaction processing. Masters banking integrations, payment systems, and building scalable financial technology that meets stringent regulatory requirements.

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Draft privacy policies, terms of service, disclaimers, and legal notices. Creates GDPR-compliant texts, cookie policies, and data processing agreements.

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Generate production-ready business documents including freelance contracts, project proposals, SOWs, NDAs, and MSAs with jurisdiction-aware clauses. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) legal frameworks. Includes contract templates, clause libraries, and DOCX conversion. Use when starting client engagements, writing proposals, drafting partnership agreements, or needing GDPR-compliant data processing addenda.

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Adapt and audit a PFC 5.0 asphalt Marshall stability/flow simulation using the external fistPkg26 dc.fis two-head controller as a starting skeleton; use for curved-head geometry, PFC5 wall/contact kinematics, load-deformation histories, peak stability, edition-specific flow processing, and validation against laboratory data.

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fMRI data analysis — preprocessing, GLM modeling, and group-level inference for task and resting-state studies.

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EPUB ebook creation and processing — structure, metadata, validation — use when generating or parsing ebooks.

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CSV processing done right — parsing edge cases, dialects, and large files — use when ingesting or exporting CSV data.

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Analyze survey and feedback data with statistical distributions, cross-tabulations, significance testing, and open-ended theme extraction. Produces executive-ready survey reports with segment comparisons and action recommendations. Use when processing NPS, CSAT, employee engagement, or market research surveys.

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Execute ENCODE DNase-seq pipeline from FASTQ to hotspots and footprints. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing DNase-seq data, calling DNase hypersensitive sites, performing footprinting analysis. Trigger on: DNase-seq pipeline, DNase hypersensitive, DHS, Hotspot2, footprinting, DNase I, chromatin accessibility DNase.

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Execute ENCODE Hi-C pipeline from FASTQ to contact matrices and loop calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing Hi-C data, generating contact matrices, or calling loops. Trigger on: Hi-C pipeline, chromatin conformation, contact matrix, loop calling, TAD detection, Juicer, HiCCUPS, 3D genome.

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Execute ENCODE Whole Genome Bisulfite Sequencing (WGBS) pipeline from FASTQ to methylation calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing WGBS/bisulfite-seq data, calling methylation levels, generating bedMethyl files. Trigger on: WGBS pipeline, bisulfite sequencing, methylation calling, DNA methylation pipeline, bismark, bwa-meth, bedMethyl.

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Execute ENCODE ATAC-seq processing pipeline from FASTQ to peaks and signal tracks. Child of pipeline-guide. Provides stage-by-stage Nextflow execution with Docker containers and cloud deployment. Handles Tn5 transposase offset correction, mitochondrial read removal, and nucleosome-free fragment selection. Use when users need to process ATAC-seq data following ENCODE standards. Trigger on: ATAC-seq pipeline, run ATAC-seq, process ATAC-seq, chromatin accessibility, open chromatin, Tn5 shift, TSS enrichment.

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Audit a government or public services system for compliance, fraud risk, and security — chains benefits processing review, fraud detection analysis, regulatory compliance check (ADA, Section 508, FISMA, Privacy Act), and PII-focused security audit. Use for benefits platforms, eligibility engines, enrollment portals, or inter-agency data systems.

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Audit precision agriculture and crop management software for yield prediction model accuracy, soil analysis integration, irrigation optimization algorithms, pest and disease detection pipelines, satellite and drone imagery processing, weather data integration.

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Use this skill when configuring or troubleshooting NPSP soft credits, partial soft credits, or matching gift workflows — including OpportunityContactRole-based credit attribution, npsp__Partial_Soft_Credit__c records, and the Find Matched Gifts process. NOT for gift entry templates or batch gift entry — use admin/gift-entry-and-processing. NOT for importing historical gifts and credits — use data/gift-history-import.

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Router for the 159 SfSkills `apex` skill packages. Apex and SOQL: triggers, Apex governor limits, async processing, OUTBOUND HTTP callouts, security enforcement, and test patterns. Owns calling an external API FROM Salesforce; salesforce-integration owns inbound. Generic nightly scheduling without naming code belongs to salesforce-flow. Codebase security review belongs to salesforce-security. NOT for SOSL — use salesforce-data. Use when the request mentions Apex, trigger, SOQL, Apex governor limit, batch, queueable, @future, schedulable, test class, CPU time, heap, with sharing, StripInaccessible, callout, HTTP callout, HttpRequest, call an external API, consume a REST API from Apex, Named Credential in Apex, HttpCalloutMock, Apex REST service. Finds and opens the exact skill package to read; it does not contain the guidance itself.

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Summarizes raw background check data into structured executive reports with risk categorization (GREEN/YELLOW/RED). Use when processing criminal records, court filings, employment/education verification, sanctions screening, or adverse media for pre-employment screening, executive due diligence, or investment-grade investigations.

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依据 RGPD 第 28 条、EDPB 07/2020 和 02/2024 号指南、2021 年标准合同条款（CCT）（执行决定 2021/914）、EDPB 01/2020 号建议（Schrems II 之后的补充措施）以及《欧盟条例 (UE) 2024/1689》（《人工智能条例》），对数据处理协议（DPA）进行系统性分析。生成逐条款的 结构化报告（18 个条款：13 项强制 + 5 项补充），附 🟢/🟡/🔴 诊断、可直接插入的 救济条款、国际传输的详细分析、《人工智能条例》核验以及应向供应商提出的问题。 触发词："analyse de DPA"、"audit DPA"、"vérifier un DPA"、"DPA fournisseur"、 "data processing agreement"、"art. 28 RGPD"、"sous-traitant RGPD"、"négociation DPA"、 "review DPA"、"conformité contrat sous-traitance"。

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Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.

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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.

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Process many sequence files in batch (count, merge, split, convert, summarize) with memory-safe streaming and on-disk indexing using Biopython, pysam, or pyfastx. Use when iterating over a directory of FASTA/FASTQ files, merging or splitting datasets, building random access across many or huge files, or automating per-file operations without exhausting RAM.

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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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Apache Spark 4.0.2 best practices for PySpark and Scala distributed data processing

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