All Services

Applies a numeric interval filter and computes a trailing mean series on business directory coverage data (listed_entities, verified_entities) for up to 200 rows, returning 2 analytical reports.

Generates two analytical reports (numeric row ordering and date-by-category pivot) for supplied business directory coverage data with listed and verified entity counts.

Runs two analytical reports on business directory coverage data: a record quality audit and a Base-100 index series for listed_entities and verified_entities metrics across up to 200 rows.

Runs two local analytical reports on business directory coverage data: a record quality audit and a date-by-category pivot, for up to 200 rows of listed_entities and verified_entities data.

Runs two analytical reports (record quality audit and duplicate key detection) on supplied business directory coverage data with listed_entities and verified_entities fields, processing up to 200 rows locally.

Audits record quality and detects exact duplicate rows in business directory coverage data (listed_entities, verified_entities) for up to 200 rows, producing two independent analytical reports.

Runs three analytical reports on business directory coverage data: record quality audit, exact row deduplication, and base-100 index series for listed_entities or verified_entities fields.

Runs three analytical reports on supplied business directory coverage rows: record quality audit, exact row deduplication, and category frequency analysis for listed and verified entity counts.

Runs three analytical reports (record quality audit, exact row deduplication, and daily sum series) on supplied business directory coverage data with listed and verified entity counts, for up to 200 rows.

Runs three local analytical reports on business directory coverage data: a record quality audit, exact row deduplication, and a duplicate key report — all on up to 200 supplied rows.

Runs three local analytical reports (record quality audit, exact row deduplication, and equal-width histogram) on up to 200 business directory coverage rows containing listed and verified entity counts.

Analyzes up to 200 business directory coverage rows, producing three reports: a record quality audit, exact row deduplication, and a grouped numeric summary of listed_entities and verified_entities fields.

Runs three local analytical reports on business directory coverage data: a record quality audit, exact row deduplication, and IQR-based outlier flagging for listed_entities and verified_entities fields.

Runs three analytical reports (record quality audit, exact row deduplication, and numeric distribution) on business directory coverage data (listed_entities, verified_entities) for up to 200 rows.

Runs three local analytical reports on business directory coverage data: a record quality audit, exact row deduplication, and a numeric interval filter on listed_entities or verified_entities fields, for up to 200 rows.

Runs three analytical reports on business directory coverage data: record quality audit, exact row deduplication, and trailing mean time series for listed_entities or verified_entities fields.

Performs a record quality audit and grouped numeric summary on business directory coverage data (listed_entities, verified_entities) for up to 200 rows, producing two independent analytical reports.

Audits supplied business directory coverage records (listed_entities, verified_entities) for data quality and flags statistical outliers using IQR analysis, producing 2 independent reports for up to 200 rows.

Audits record quality and computes numeric distribution statistics for business directory coverage data (listed_entities, verified_entities) across up to 200 supplied rows.

Audits business directory coverage records (listed_entities, verified_entities) for record quality, string normalisation issues, and adjacent row changes — producing 3 independent analytical reports for up to 200 rows.

Audits record quality, normalises strings, and computes a Base-100 index series for up to 200 business directory coverage rows (listed_entities, verified_entities) using three independent local analytical reports.

Audits record quality, normalises strings, and computes category frequencies for up to 200 business directory coverage rows (listed_entities, verified_entities) in a single call with three independent analytical reports.

Runs three local analytical reports (record quality audit, string normalisation, and grouped numeric summary) on up to 200 business directory coverage rows containing listed and verified entity counts.

Audits record quality, normalises strings, and flags IQR-based outliers in business directory coverage data (listed_entities, verified_entities) for up to 200 rows across 3 independent analytical reports.

Runs three analytical reports (record quality audit, string normalisation, and keyed dataset comparison) on up to 200 rows of business directory coverage data containing listed_entities and verified_entities fields.

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of business directory coverage data containing listed_entities and verified_entities fields.

Runs two local analytical reports on business directory coverage data: a record quality audit and a trailing mean series, for up to 200 rows of listed/verified entity counts.

Audits business directory coverage records for data quality and computes a two-measure correlation between listed_entities and verified_entities across up to 200 supplied rows.

Computes a secondary-measure weighted mean and a date-by-category pivot table for business directory coverage data (listed_entities, verified_entities) in a single API call producing two analytical reports.

Runs two local analytical reports (string normalisation and numeric distribution) on business directory coverage data rows containing listed_entities and verified_entities fields.

Computes a trailing moving average time series and a date-by-category pivot table for business directory coverage data (listed_entities, verified_entities) supplied by the caller.

Computes a trailing moving average time series and an equal-width histogram for business directory coverage metrics (listed_entities, verified_entities) over supplied row data.

Computes a trailing mean time series and fills missing values in business directory coverage data (listed_entities, verified_entities) for up to 200 rows, producing two analytical reports.

Runs two local analytical reports on supplied business directory coverage data: a Pearson-style correlation between listed_entities and verified_entities, plus a date-by-category pivot table.

Computes correlation between listed_entities and verified_entities, and fills missing values in business directory coverage rows using a chosen strategy (zero, mean, or median), producing two analytical reports for up to 200 rows.

Runs two local analytical reports (Pearson/Spearman correlation between listed_entities and verified_entities, plus a keyed row-by-row dataset comparison) on supplied business directory coverage records, up to 200 rows per call.

Computes adjacent row changes and an equal-width histogram for business event participation data (attendee_count, company_count) across up to 200 rows, returning two analytical reports.

Computes adjacent-row delta changes and fills missing values in business event participation data (attendee_count, company_count) for up to 200 rows, returning 2 analytical reports.

Computes adjacent-row delta changes and IQR-based outlier flags for business event participation data (attendee_count, company_count) across up to 200 rows.

Runs two local analytical reports on business event participation data: adjacent row changes and keyed dataset comparison for attendee_count or company_count fields, up to 200 rows.

Transforms business event participation records (attendee_count, company_count) into a Base-100 indexed series and fills missing values using zero, mean, or median imputation — up to 200 rows, 2 reports per call.

Generates two analytical reports — a Base-100 indexed time series and a keyed dataset comparison — for supplied business event participation data (attendee_count, company_count) across up to 200 rows.

Computes a Base-100 index series and a secondary-measure weighted mean for supplied business event participation data (attendee_count, company_count) in a single API call returning two analytical reports.

Analyzes business event participation records to produce category frequency distributions and adjacent row change reports for attendee_count or company_count fields.

Computes category frequency distributions and a Base-100 indexed series for supplied business event participation data (attendee_count or company_count) across up to 200 rows.

Analyzes business event participation records (up to 200 rows) to produce two reports: category frequency breakdown by company_group and a daily sum time series for either attendee_count or company_count.

Analyzes supplied business event participation records to produce two local reports: category frequency counts and a date-by-category pivot, for attendee_count or company_count fields.

Computes category frequencies and an equal-width histogram for business event participation records (attendee_count or company_count fields) across up to 200 rows.

Computes category frequency distributions and IQR-based outlier flags for business event participation data (attendee_count and company_count) across up to 200 rows.

Analyzes business event participation records to produce category frequency distributions and a keyed comparison between two supplied datasets (up to 200 rows each, two reports per call).

Computes category frequencies and numeric row ordering for business event participation records (attendee_count, company_count) across up to 200 rows, returning 2 analytical reports.

Computes category frequency distributions and trailing mean time series for business event participation data (attendee_count, company_count) across up to 200 rows.

Analyzes business event participation records to produce category frequency counts and Pearson/rank correlation between attendee_count and company_count across up to 200 rows.

Computes daily sum time series and adjacent row-over-row changes for business event participation metrics (attendee_count, company_count) across up to 200 supplied rows.

Computes a daily sum time series and a date-by-category pivot table for supplied business event participation data (attendee_count or company_count) across up to 200 rows.

Computes daily sum time series and fills missing values (zero, mean, or median) for business event participation data (attendee_count, company_count) across up to 200 rows, returning 2 analytical reports.

Computes a daily sum time series and a keyed dataset comparison for up to 200 business event participation records (attendee_count, company_count) using local analytical engines.

Computes daily sum series and trailing moving-average series for business event participation data (attendee_count or company_count) across up to 200 rows, producing two independent analytical reports.

Pivots business event participation data (attendee_count or company_count) by date and company group, filling missing values via zero, mean, or median imputation — returns two analytical reports for up to 200 rows.

Generates a date-by-category pivot table and a keyed dataset comparison report for up to 200 business event participation records, analyzing attendee_count or company_count.

Analyzes supplied business event participation data (attendee_count or company_count) to produce a duplicate key report and a Base-100 indexed series for up to 200 rows.

Runs two local analytical reports on supplied business event participation data: a duplicate key detection report and a daily sum time series, for up to 200 rows.

Analyzes up to 200 business event participation rows to produce two local analytical reports: a duplicate key report and a date-by-category pivot, for attendee_count or company_count.

Generates a duplicate key report and an equal-width histogram for business event participation data (attendee_count or company_count) across up to 200 supplied rows.

Analyzes up to 200 business event participation records to detect duplicate row keys and fill missing values in attendee_count or company_count fields using zero, mean, or median imputation.

Analyzes up to 200 business event participation records to produce a duplicate key report and a grouped numeric summary for attendee_count or company_count fields.

Analyzes up to 200 business event participation records to produce a duplicate key report and IQR-based outlier flags for attendee_count or company_count fields.

Analyzes up to 200 business event participation records to produce two reports: a duplicate row_id detection report and a keyed comparison between two supplied datasets.

Analyzes business event participation data to produce a duplicate key report and numeric distribution for attendee_count or company_count across up to 200 rows.

Generates two analytical reports on business event participation data: a duplicate key report and a trailing mean series for attendee_count or company_count fields.

Computes equal-width histograms and fills missing values for business event participation data (attendee_count and company_count) across up to 200 rows, producing 2 independent analytical reports.

Runs two local analytical reports on business event participation data: an equal-width histogram over attendee or company counts, and a keyed comparison between two supplied datasets, for up to 200 rows.

Computes an equal-width histogram and a secondary-measure weighted mean for up to 200 business event participation records (attendee_count, company_count) using local analytical engines.

Deduplicates business event participation records and computes a Base-100 indexed series for attendee_count or company_count across up to 200 rows.

Deduplicates exact rows and computes category-level frequency counts for business event participation records (attendee_count, company_count) across up to 200 rows.

Deduplicates business event participation rows and computes daily sum time series for attendee_count or company_count metrics across up to 200 records.

Deduplicates business event participation records and generates a date-by-category pivot table for attendee and company count metrics across up to 200 rows.

Deduplicates business event participation records and generates a duplicate key report for up to 200 rows of attendee and company count data.

Deduplicates business event participation records and generates equal-width histogram reports for attendee_count or company_count fields across up to 200 rows.

Deduplicates exact duplicate rows and fills missing values in business event participation data (attendee_count, company_count) for up to 200 rows, returning 2 analytical reports.

Deduplicates business event participation records exactly and produces grouped numeric summaries for attendee_count or company_count fields, up to 200 rows with 2 reports per call.

Deduplicates business event participation records and compares two keyed datasets (attendee_count, company_count) across up to 200 rows, producing two independent analytical reports.

Deduplicates identical rows and applies numeric ordering to business event participation records (attendee_count, company_count) for up to 200 rows, returning 2 analytical reports.

Deduplicates business event participation records and computes a trailing mean time series for attendee_count or company_count across up to 200 rows.

Generates two local analytical reports — a grouped numeric summary and adjacent row changes — for business event participation data (attendee_count, company_count) across up to 200 rows.

Generates two local analytical reports (grouped numeric summary and Base-100 indexed series) for business event participation data including attendee and company counts, across up to 200 rows.

Computes grouped numeric summary statistics and category frequency reports for business event participation data (attendee_count and company_count) across up to 200 rows.

Computes a grouped numeric summary and a daily sum time series for business event participation data (attendee_count and company_count) across up to 200 rows.

Computes grouped numeric summary statistics and IQR-based outlier flags for business event participation data (attendee_count or company_count), grouped by company_group.

Computes grouped numeric summaries and keyed dataset comparisons for business event participation data (attendee_count, company_count) across up to 200 rows.

Analyzes business event participation records by computing grouped numeric summaries and filtering by numeric interval for attendee_count or company_count fields across up to 200 rows.

Computes a grouped numeric summary and a trailing mean series for business event participation data (attendee_count or company_count) across up to 200 rows, returning two analytical reports.

Computes grouped numeric summaries and a two-measure correlation report for business event participation data (attendee_count and company_count) across up to 200 supplied rows.

Runs two local statistical reports on supplied business event participation data: IQR-based outlier flagging and a date-by-category pivot, for up to 200 rows.

Detects IQR-based outliers and fills missing values in business event participation records (attendee_count, company_count) for up to 200 rows, producing two analytical reports.

Analyzes business event participation records (attendee_count, company_count) to flag IQR-based outliers and compute a secondary-measure weighted mean, producing two analytical reports per call.

Runs IQR outlier detection and two-measure correlation analysis on business event participation records (attendee_count and company_count) for up to 200 rows, returning two independent statistical reports.

Computes numeric distribution statistics and a base-100 index series for business event participation data (attendee_count and company_count) across up to 200 supplied rows.

Computes numeric distribution statistics and category frequency reports for business event participation data (attendee_count, company_count) across up to 200 rows.

Computes a numeric distribution and daily sum time series for attendee_count or company_count fields from supplied business event participation records (up to 200 rows, 2 reports per call).