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Overview

If your platform has built a bespoke analytics/reporting solution or envisions various proprietary use cases for large analytical/accounting data, Tight’s Data Lakes product is a natural add-on. Of course, Tight allows you to access all the data that is available for your users in the API. But, Tight takes this concept several levels further by periodically uploading raw data to your own data lake buckets, in the format your team desires. By pushing that data into the warehouse of your preference, Tight eliminates the need for your data team to build direct connections to the Tight API, allowing your team to work in the data stack that they are used to.

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Use cases

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Loan decisioning

For platforms offering lending products, Tight’s Data Lakes provide the comprehensive financial data needed for sophisticated underwriting and risk assessment. By automatically syncing transaction history, bank balances, invoice data, and categorized expenses to your data warehouse, your credit team can build robust models without requiring manual data uploads from applicants. Your data scientists can work directly in tools like Snowflake, BigQuery, or your preferred analytics platform to analyze cash flow patterns, revenue trends, expense ratios, and business health indicators. This eliminates the friction of API calls for large datasets and enables complex joins with your existing customer data, application information, and third-party data sources. The result is faster loan decisions with better risk assessment. Your team can instantly evaluate an applicant’s revenue consistency, expense management, and overall financial trajectory, all from data that’s already flowing into your warehouse in a format your team knows how to work with.

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User/product analytics

Understanding how your users engage with accounting features is critical for product optimization, but pulling this data through API calls doesn’t scale for analytics workloads. Tight’s Lifecycle Event uploads to Amplitude, Mixpanel, or Intercom provide automatic event tracking for all user actions within Tight’s embedded experiences. Every transaction categorization, invoice creation, bank connection, report generation, and dashboard view is captured as structured event data. Your product team can analyze activation funnels, feature adoption, and user retention patterns without building instrumentation infrastructure. Which features drive engagement? Where do users get stuck during onboarding? How does accounting feature usage correlate with overall platform retention? For platforms with bespoke analytics needs, full Data Lake uploads provide the raw material for custom analysis. Join accounting activity data with your proprietary user data to understand financial behaviors across segments, build predictive models for churn, or identify expansion opportunities based on accounting sophistication.

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Data types

Tight will upload data related to the following elements of Tight API/SDK information and interactions on daily, weekly, or monthly intervals:

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Bank linkage

A Parquet file containing information on all linked bank accounts. The columns include the bulk of data available in the /banks/accounts endpoint, including userId, apiInstitutionId, apiAccountNo, apiAccountType, createdDate, lastExpenseSyncedDate, lastRevenueSyncedDate, apiCurrentBalance, and more. Each file contains all the records that were updated since the last data upload.

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Invoices

A Parquet file containing information on all invoices. The columns include the bulk of data available in the /invoices endpoint, including userId, date, totalAmount, dueDate, sentDate, lastViewedDate, status, and more. Each file contains all the records that were updated since the last data upload.

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Lifecycle Events

A folder of Parquet files, one per event category, containing information on actions each user has taken, which is often useful for optimizing user experiences/funnels. The columns include userId, date, event, and event-specific metadata. The full list of events being tracked is available in the Lifecycle Event Dictionary.

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Transactions

A Parquet file containing information on all transactions. The columns include the bulk of data available in the /transactions endpoint, including userId, apiInstitutionId, apiAccountNo, date, amount, bankDescription, categoryName, and more. Each file contains all the records that were updated since the last data upload.

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Integrations

Tight currently supports native integrations for full Data Lake uploads to: Additionally, Tight natively supports Lifecycle Event uploads to: