Results for “data”

Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations. Use PROACTIVELY for business intelligence or strategic analysis.

Runs AutoMagicCalib calibration on local MP4s, RTSP streams, or a bundled sample dataset, and deploys the AMC microservice when needed.

Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, tooling, testing, and production-ready practices.

Optimize SQL queries, indexes, and database performance across MySQL, PostgreSQL, SQL Server, and Oracle with execution plan analysis and universal tuning techniques.

Optimize PostgreSQL databases with advanced features, performance tuning, and best practices for JSONB, full-text search, window functions, and indexing.

Read, write, and manipulate genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.

Query 40+ bioinformatics services (UniProt, KEGG, ChEMBL, Reactome) with a unified Python interface for cross-database analysis, identifier mapping, and sequence analysis.

Fit statistical models (OLS, GLM, ARIMA, mixed models) with detailed diagnostics, residuals, and inference for econometrics and time series analysis.

Guides statistical hypothesis testing with assumption checks, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting for research data.

Search and retrieve past work from claude-mem's persistent cross-session memory database using a three-layer workflow: search, timeline, and fetch.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over marker lists with an LLM.

Trains machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

Process and analyze mass spectrometry data with the Matchms Python library, including importing spectra, filtering peaks, calculating similarity scores, and building reproducible analytical workflows.

Queries CDC open data and WHO Global Health Observatory indicators for public health intelligence, covering disease surveillance, vaccinations, and mortality.

Store and query embeddings with metadata, vector and full-text search, and filtering. Integrates with LangChain and LlamaIndex for RAG and semantic search applications.

Authenticate, browse pipelines, samples, and projects, upload data, launch pipeline executions, and check run status on any Flow.bio instance via CLI.

Collects market data from Yahoo Finance and Exa, calculates technical indicators, scans watchlists, and generates market analysis reports to identify trading opportunities.

Guides analysis of Neuropixels recordings from raw data to curated units, covering preprocessing, motion correction, spike sorting, quality metrics, and export.

Performs geospatial vector data analysis with GeoPandas, including reading/writing shapefiles, GeoJSON, GeoPackage, and PostGIS, geometric operations, spatial joins, overlays, coordinate transformations, and map visualization.

Exchange data between Excel and MATLAB using Spreadsheet Link VBA macros and worksheet functions. Use when writing Excel VBA macros that call MLPutMatrix, MLGetMatrix, MLPutVar, MLGetVar, MLPutRanges, MLEvalString, MLGetFigure, or MatlabRequest.

Use when designing PostgreSQL tables, enums, relationships, migrations, storage metadata, or tenant-aware schema structures for a Supabase-backed app. Trigger on requests about Supabase schema planning or SQL-first data design.

Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.

Manage Azure MySQL Flexible Server deployments using the .NET SDK. Create servers, databases, firewall rules, configurations, backups, and configure high availability.

Manage Azure PostgreSQL Flexible Server deployments using the .NET SDK. Create servers, databases, firewall rules, configurations, backups, and high availability.

Curates clinical-specialty term lists, generates IPA-tagged synthetic audio via TTS, and produces NeMo-format manifests for ASR benchmark evaluation.

Provides production patterns and non-obvious traps for Prisma ORM in TypeScript backends, covering schema design, query optimization, transactions, pagination, and common pitfalls.

Find which of a GitHub repository's dependencies are sponsorable via GitHub Sponsors, using deps.dev API for dependency resolution and project health data.

Access Google Ads data through Google Analytics integration: run performance reports, list linked Ads accounts, and analyze campaign metrics using Rube MCP (Composio).

Design experiments and studies before data collection — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable.

Generate comprehensive, professional-grade market research reports (50+ pages) with LaTeX formatting, strategic frameworks, and data-driven visualizations.

Analyze US stocks with fundamental and technical analysis, peer comparisons, and investment reports using real-time market data.

Manages SurrealDB schemas as desired-state .surql files, with sync for disposable databases and reviewed rollouts for shared or production environments, plus seeding and declarative testing.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1, extracting events as NumPy arrays, metadata, and channel information, with support for creating and modifying FCS files.

Pythonic wrapper around RDKit for cheminformatics, simplifying SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing while returning native rdkit.Chem.Mol objects.

Production patterns and non-obvious traps for Prisma ORM in TypeScript backends, covering schema design, query optimization, transactions, pagination, and serverless connection handling.

Generates one-day Kiro credit usage reports from LanceDB usage events, with China-time windows, global totals, and account subset breakdowns.