All Services

Audits trading journal records (entry_price, exit_price) for data quality issues and compares two keyed datasets side-by-side, returning two analytical reports for up to 200 rows.

Audits data quality and computes numeric distribution statistics for trading journal entry_price and exit_price fields across up to 200 rows.

Audits record quality, normalises strings, and computes category frequencies across up to 200 trading journal rows (entry_price, exit_price) in three independent local analytical reports.

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 trading journal rows containing entry_price and exit_price fields.

Computes a secondary-measure weighted mean and a date-by-category pivot table for up to 200 trading journal rows containing entry and exit prices.

Computes a secondary-measure weighted mean and performs a keyed dataset comparison across two sets of trading journal records (entry_price, exit_price) for up to 200 rows each.

Runs two local analytical reports (string normalisation and duplicate key detection) on up to 200 trading journal rows containing entry and exit price data.

Runs string normalisation and an equal-width histogram analysis on trading journal entry_price or exit_price data for up to 200 rows, returning two analytical reports.

Normalises strings and deduplicates exact rows in trading journal observation records (entry_price, exit_price) for up to 200 rows, producing 2 analytical reports.

Normalises string fields and fills missing entry_price or exit_price values in trading journal observation records using zero, mean, or median imputation.

Runs string normalisation and numeric distribution analysis on up to 200 trading journal rows (entry_price or exit_price), returning two local analytical reports per call.

Computes a trailing mean time series and an equal-width histogram for entry_price or exit_price fields from up to 200 trading journal records.

Computes Pearson correlation between entry_price and exit_price and fills missing values in a chosen field using zero, mean, or median imputation for up to 200 trading journal rows.

Computes Pearson correlation between entry_price and exit_price, plus a weighted mean of the secondary measure, for up to 200 trading journal rows in two bundled analytical reports.

Runs a backtest of a trading strategy using historical market data and returns performance metrics

Computes adjacent row changes and a secondary-measure weighted mean for training assessment records (pre_score, post_score) across up to 200 rows.

Analyzes training assessment pre/post scores by generating a base-100 indexed series and filling missing values using a chosen imputation method, producing two analytical reports for up to 200 rows.

Runs two local analytical reports on training assessment records (pre/post scores): a Base-100 indexed series and a keyed dataset comparison, for up to 200 rows per call.

Computes category-level score frequencies and a daily sum time series from submitted training assessment records (pre_score and post_score fields) for up to 200 rows.

Analyzes training assessment records (pre_score, post_score) to produce category frequency counts and IQR-based outlier flags for up to 200 rows.

Analyzes training assessment records by computing course group category frequencies and Pearson/Spearman correlation between pre-score and post-score columns, returning two reports for up to 200 rows.

Computes a daily sum time series and a secondary-measure weighted mean from supplied training assessment records (pre_score, post_score) — up to 200 rows, two reports per call.

Computes daily sum time series and trailing moving-average series for pre_score and post_score fields across training assessment records, returning two independent analytical reports.

Analyzes training assessment records (pre_score, post_score) to produce two reports: a duplicate key report and adjacent row changes, for up to 200 rows.

Analyzes training assessment records to produce a duplicate key report and category frequency counts for pre_score and post_score fields across course groups.

Generates two analytical reports on training assessment records: a duplicate key report and a keyed dataset comparison between two supplied datasets of up to 200 rows each.

Generates a duplicate key report and numeric distribution analysis for training assessment records (pre_score, post_score) on up to 200 supplied rows.

Deduplicates training assessment records and computes category-frequency breakdowns for pre_score/post_score data across course groups, returning two analytical reports for up to 200 rows.

Deduplicates training assessment rows exactly and computes daily sum time series for pre_score or post_score fields across up to 200 records.

Deduplicates exact rows and generates a duplicate key report for training assessment records containing pre-score and post-score fields, processing up to 200 rows.

Deduplicates exact rows and flags IQR-based outliers in training assessment records containing pre_score and post_score fields, returning two analytical reports for up to 200 rows.

Deduplicates training assessment rows and computes a secondary-measure weighted mean for pre_score or post_score across up to 200 records, returning two analytical reports.

Runs two analytical reports on training assessment data: a grouped numeric summary by course group and an adjacent row changes report for pre/post scores, across up to 200 rows.

Computes a grouped numeric summary and numeric row ordering for training assessment pre/post score data, delivering two analytical reports for up to 200 rows.

Detects IQR-based outliers and fills missing values in training assessment score data (pre_score, post_score) for up to 200 rows, returning two analytical reports.

Analyzes training assessment records (pre_score, post_score) to produce IQR-based outlier flags and a secondary-measure weighted mean, returning two statistical reports for up to 200 rows.

Computes numeric distribution statistics and category frequency counts for pre_score and post_score fields across up to 200 training assessment records.

Computes a numeric distribution report and a daily sum time series for pre_score and post_score fields across up to 200 training assessment records.

Computes numeric distribution statistics and fills missing values for training assessment pre/post scores across up to 200 rows.

Runs two analytical reports on training assessment records: a numeric interval filter on pre/post scores, and a keyed comparison between two supplied datasets, for up to 200 rows.

Filters training assessment rows by a numeric score range and computes correlation between pre_score and post_score across up to 200 supplied records, returning two analytical reports.

Computes numeric row ordering and Base-100 index series for up to 200 training assessment records (pre_score and post_score), returning two analytical reports using local computation only.

Computes numeric row ordering and a daily sum time series for training assessment records (pre_score and post_score) across up to 200 rows, returning two analytical reports.

Generates two analytical reports for training assessment data: numeric row ordering and a date-by-category pivot table for pre_score or post_score fields, supporting up to 200 rows.

Sorts training assessment records by pre_score or post_score and flags statistical outliers using IQR analysis, returning two analytical reports for up to 200 rows.

Ranks training assessment records by a numeric score field and compares two datasets of pre/post assessment scores using row keys, returning two analytical reports for up to 200 rows.

Runs two local analytical reports on training assessment data: a record quality audit and a date-by-category pivot for pre_score or post_score values.

Runs three analytical reports on training assessment records: record quality audit, exact row deduplication, and numeric distribution analysis for pre_score and post_score fields.

Audits training assessment records (pre_score, post_score) for data quality issues and flags statistical outliers using IQR analysis, producing two independent reports for up to 200 rows.

Runs two local analytical reports — a record quality audit and a numeric distribution analysis — on up to 200 rows of training assessment data (pre_score and post_score fields).

Runs three analytical reports (record quality audit, string normalisation, and category frequencies) on training assessment records containing pre-score and post-score fields, for up to 200 rows.

Audits record quality, normalises strings, and produces grouped numeric summaries for training assessment data (pre_score, post_score) across up to 200 rows in three independent reports.

Runs three combined analytical reports on training assessment records — record quality audit, string normalisation, and IQR outlier detection — for up to 200 rows of pre_score/post_score data.

Runs three local analytical reports on training assessment data (pre_score, post_score): a record quality audit, string normalisation, and a secondary-measure weighted mean — up to 200 rows per call.

Runs two analytical reports on training assessment data: a record quality audit and a trailing mean series over pre_score or post_score values, for up to 200 rows.

Computes a secondary-measure weighted mean and a date-by-category pivot table for up to 200 training assessment rows (pre_score / post_score), returning two analytical reports.

Computes a secondary-measure weighted mean and fills missing values for training assessment records (pre_score, post_score) across up to 200 rows, returning two analytical reports.

Runs two analytical reports on training assessment data: string normalisation and adjacent row changes for pre_score or post_score across up to 200 rows.

Runs two analytical reports on training assessment records: string normalisation and base-100 index series for pre_score or post_score fields, across up to 200 rows.

Runs string normalisation and equal-width histogram analysis on up to 200 training assessment records containing pre_score and post_score fields, returning two local analytical reports.

Normalises string fields and flags IQR-based outliers in pre_score and post_score columns for up to 200 training assessment rows, returning two independent analytical reports.

Computes a trailing mean series and adjacent row changes for pre_score or post_score fields across up to 200 training assessment records, returning two analytical reports.

Computes a trailing mean time series and fills missing values for pre_score or post_score fields in training assessment records (up to 200 rows, 2 reports per call).

Computes a rolling/trailing mean time series and a secondary-measure weighted mean for training assessment records containing pre_score and post_score fields.

Computes Pearson correlation between pre_score and post_score columns and fills missing values in a chosen score column for up to 200 training assessment rows, returning two analytical reports.

Computes a two-measure correlation between pre_score and post_score fields and performs a keyed dataset comparison across two supplied training assessment datasets (up to 200 rows each).

Counts how many times each course category appears across up to 200 training attendance records, returning category frequency distributions.

Pivots training attendance data (attendees or completions) by date and course category, producing a cross-tabulated summary from up to 200 supplied records.

Identifies duplicate row keys in a batch of training attendance records, returning a data-quality report of conflicting entries.

Removes exact duplicate rows from training attendance records (up to 200 rows) based on all field values, returning a deduplicated dataset.

Fills missing numeric values in training attendance records (attendees or completions) using zero, mean, or median imputation across up to 200 rows.

Computes a grouped numeric summary (e.g. count, sum, mean) of attendees or completions across training courses from up to 200 supplied records.

Compares two keyed datasets of training attendance records (up to 200 rows each) and returns numeric and data-quality difference analysis.

Filters training attendance records (attendees or completions) to return only rows where a specified numeric field falls within a given min–max range.

Audits up to 200 training attendance records for numeric and data-quality issues, returning a bounded quality report per batch.

Computes a secondary-measure weighted mean over training attendance records (attendees or completions) for up to 200 course session rows, locally, with no external enrichment.

Normalises and cleans string fields in training attendance records (course names, dates, attendee and completion counts) for up to 200 rows per call.

Computes a trailing (rolling) mean series for training attendance or completion metrics across up to 200 date-keyed course records.

Analyzes training compliance data (completed_courses, assigned_courses) by computing adjacent row changes and an equal-width histogram, returning two analytical reports for up to 200 rows.

Analyzes training compliance data (completed_courses, assigned_courses) to produce two reports: category frequency counts and a base-100 indexed series, for up to 200 rows.

Runs two analytical reports on training compliance data: category frequency counts and a date-by-category pivot, for up to 200 rows of completed/assigned course records.

Analyzes training compliance records (completed_courses, assigned_courses) to produce category frequency counts and an equal-width histogram report for up to 200 rows.

Analyzes training compliance records (completed_courses, assigned_courses) to produce category frequency distributions and IQR-based outlier flags for up to 200 rows.

Computes category frequencies and a secondary-measure weighted mean for up to 200 training compliance records (completed_courses, assigned_courses) in two independent local analytical reports.

Analyzes training compliance records to produce category frequency distributions and a two-measure correlation report for completed_courses vs assigned_courses data.

Computes daily sum series and adjacent row changes for training compliance records (completed_courses, assigned_courses) across up to 200 rows.

Computes daily sum time series and base-100 indexed series for training compliance data (completed_courses, assigned_courses) using local analytical engines.

Computes a daily sum time series and a secondary-measure weighted mean for training compliance records (completed_courses, assigned_courses) across up to 200 rows in two independent analytical reports.

Computes daily sum series and trailing mean series for training compliance data (completed_courses, assigned_courses) across team groups, returning two independent analytical reports.

Runs two analytical reports on training compliance data: a date-by-category pivot table and a keyed dataset comparison, for up to 200 rows of completed/assigned course records.

Analyzes training compliance records to produce a duplicate row_id report and category frequency breakdown for completed_courses and assigned_courses fields, using local analytical engines on up to 200 supplied rows.

Analyzes up to 200 training compliance records to produce a duplicate key report and a keyed dataset comparison between two supplied datasets, using local analytical engines with no external lookups.

Computes an equal-width histogram and a two-measure correlation report for training compliance data (completed_courses and assigned_courses) from up to 200 supplied rows.

Analyzes up to 200 training compliance records to identify exact duplicate rows and detect adjacent row changes across completed_courses and assigned_courses fields.

Deduplicates training compliance records and pivots completed/assigned course counts by date and category, returning two analytical reports for up to 200 rows.

Deduplicates training compliance records and generates a duplicate key report for up to 200 rows of completed/assigned course data.

Deduplicates training compliance records and flags IQR-based outliers for completed_courses or assigned_courses fields, producing two analytical reports from up to 200 rows.

Runs two local analytical reports on training compliance records: exact row deduplication and numeric distribution analysis for completed_courses or assigned_courses fields, for up to 200 rows.

Deduplicates and numerically sorts up to 200 training compliance records (completed_courses, assigned_courses) using local analytical engines, returning two independent reports.

Deduplicates training compliance records and computes correlation between completed_courses and assigned_courses across up to 200 rows, returning two analytical reports.