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Browse the market datasets
Updated 31 October 2026 · 3 min read · 14 Contents
Plain-language meaning
The Data pages are a catalogue of stored market and reference datasets grouped by scope: NSE, BSE, US, International and Global. Each dataset page shows its rows with filters, a freshness stamp and notes about its limits.
Why it is useful #
They give direct, filterable access to the underlying records — filings, earnings, ownership, index changes, quotes and reference lists — when a summary page is not enough.
Where it appears and the workflow #
Open Explore and choose a datasets link, or go to /data/{scope} (nse, bse, us, intl or global). Dataset cards are grouped under Filings & Events, Ownership & Governance, Markets and News. On a dataset page, filter by symbol, exchange where offered and From/To dates, then Apply. Read the 'Data as of', 'Retrieved' and timeliness stamp (reference, end of day, delayed, real time or news feed), page through 25, 50 or 100 rows and open a row's detail drawer, which charts the price series for quote datasets. On mobile, dataset links open the matching dataset screen.
Calculation or source #
Rows are read from data already stored by the platform's provider syncs; browsing never calls a provider live. Each dataset's notes panel states its specific caveats.
Prerequisites, inputs, period and unit #
Some datasets require one instrument before they show rows. Access follows the provider's display licence, so some datasets need sign-in and some show a licence-pending notice. Dates are source dates; units and currency follow each dataset's columns.
Worked example #
Illustrative only: filtering a US earnings dataset to one symbol and the last four quarters returns four dated rows, each with its own retrieved time. A missing quarter is a missing row, not a zero result.
What high and low mean #
There is no single high or low for a catalogue; each dataset's columns carry their own meaning, explained in its notes.
Positive, negative and zero #
Zero values are shown only when the source reported zero. Negative values follow each column's definition, such as a net sale in an ownership dataset.
Limitations and common mistakes #
Datasets differ in coverage, delay and history depth, and some optional datasets can be turned off by configuration. A common mistake is treating the retrieved time as the source date.
Market-specific differences #
NSE and BSE scopes focus on Indian earnings, sector valuation, statements and corporate actions; the US scope adds SEC filings, insider and congressional trades, 13F holdings and treasury rates; Global covers index, forex, crypto and commodity quotes plus calendars and reference lists.
Suggested next steps #
Open the US scope, choose an insider-trading dataset, filter to one symbol and a one-year range, and record the 'Data as of' and 'Retrieved' stamps. Then open a Global quote dataset and explain the difference between its timeliness label and the insider dataset's.
Educational use only #
This guide explains descriptive research evidence. It is not investment advice, a price prediction, a recommendation, a claim of predictive accuracy, or an instruction to buy, sell, rebalance or place an order.