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Setting up the BigQuery integration
Setting up the BigQuery integration

An overview of the BigQuery integration

Carly Hammond avatar
Written by Carly Hammond
Updated this week

Summary

  • Data you can sync

    • CRM data

      • Including mapping columns to both standard and custom fields on models

    • Time-series usage data

  • Sync direction

    • CRM data:

      • Specify per model and field

      • Choose between both directions, send, or receive

    • Time-series usage data: BigQuery to Planhat

  • Sync frequency

    • CRM data: hourly

    • Time-series usage data: every 5, 10, 30 or 60 minutes, or daily on a schedule

  • Data mapping

    • See table below

Who is this article for?

  • Anyone who would like an introduction to the BigQuery integration

Series

This article is part of a series on the BigQuery integration:

Article contents

Introduction

Planhat's BigQuery integration enables you to sync CRM (static) data bidirectionally, and time-series usage data from BigQuery to Planhat. Data is synced automatically, on a fast, regular cadence.

With your BigQuery data in Planhat, you can leverage Planhat's workflow platform to take data-driven action, to drive long-term value for your customers and improve internal efficiency. In addition, you can consolidate BigQuery data with additional data types, such as tickets or emails, to give your team a complete 360° view of your customers. You can also quickly and easily perform advanced data analysis and visualise your BigQuery data, helping your team proactively identify risks and opportunities to retain and grow customer revenue.

Here's a summary of some key specifications related to the BigQuery integration; we discuss these in further detail in this article.

CRM data

Time-series usage data

Automatic sync frequency

Hourly

Your choice: every 5, 10, 30 or 60 minutes, or once per day at specified time

ID (key) requirements

Unique and text

Unique, numeric and incrementing

Data mapping

Planhat

Sync direction

BigQuery

CRM data: Planhat models

(Company, End User, License and Opportunity etc.)

Bidirectional (or one-way)*

Tables or views

Time-series usage data

(User Activities and Custom Metrics)

From BigQuery to Planhat

Tables or views

*Note: Data cannot be synced from Planhat back to BigQuery views, as they are read-only.

Time-series usage data is applicable for the models Company, End User, Asset and Project.

Summary of setup steps

There are two main stages to setting up the BigQuery integration:

  1. Preparation in BigQuery and integration authentication

    • For details, see this article

    • A. In BigQuery

      • Create a new project in Google Cloud

      • Set up OAuth consent screen

      • Begin to configure credentials

    • B. In Planhat

      • Open BigQuery

      • Copy redirect URI

    • C. In BigQuery

      • Generate credentials (using URI from Planhat)

    • D. In Planhat

      • Enter BigQuery credentials and authenticate

      • Enable the integration

      • Select your BigQuery database

  2. Data mapping in Planhat's BigQuery integration

    • For details, see this article

    • The next stage is configuring the mapping in the BigQuery integration in Planhat, for CRM and/or usage data depending on what you want to sync

    • The main principles for each sync section are:

      • Choose which data model/type in Planhat to map to which column in BigQuery

      • For CRM data, choose the sync direction

      • Specify the unique IDs (keys) used in Planhat and BigQuery

      • Set up field mapping

      • For usage data, choose the sync frequency and batch size

Sync frequency

CRM data

CRM data can be synced automatically, both to and from BigQuery, on an hourly basis.

To enable the automatic sync, turn on the toggle switch "activate BigQuery automation synchronization" at the top of the integration.

You also have the option to sync manually via the "Full sync" button, or using the arrow symbols at the right of each sync section.

The BigQuery sync is always a full data sync (rather than a partial sync).

Usage data

You can set Planhat to fetch usage data from BigQuery every 5, 10, 30, or 60 minutes, or daily at a specified time.

Unique IDs

For both CRM data and usage data, the integration uses unique IDs for data mapping. You may hear these referred to as keys, keyables, IDs or identifiers.

The requirements for these unique IDs are slightly different for CRM data compared to usage data.

CRM data

When configuring CRM data mapping, for each sync section (Planhat data model), you select an ID for both the Planhat side and the BigQuery side, which is used to match records between the two systems.

The ID on the Planhat side is typically Source ID or External ID, although you can use email address in some cases, and it's also possible to select the Planhat native ID (although generally this is not recommended - see here for further details). These are fields on the Planhat models, containing a unique ID to specify that particular record.

For the ID on the BigQuery side, select a suitable column from the dropdown menu. The ID/key must be unique and text.

Usage data

When it comes to the one-way sync of usage data (time-series data), there are some differences:

  • There isn't an ID on the Planhat side, only the BigQuery side

  • The ID in BigQuery is also used for change tracking - i.e. to identify which rows are new data (that haven't been synced yet)

Rows in BigQuery must be identified by a unique, numeric, incrementing column for the ID (key).

  • Incrementing means increasing in value for each new row added, so that it is sorted from least to most recent

  • An ideal key would be an ingestion/sequence timestamp - e.g. 1, 2, ..., 2104, ....

  • It should be maximum 32 characters

Logs and errors

If you follow the instructions in the next articles in this series, the setup process should be smooth and easy.

If there are any errors with authorisation or sync (for example, if your BigQuery token has expired), they are surfaced in the BigQuery integration.

There are also detailed logs available within the integration, so you can see what actions have occurred and when.

This means it's easy for you to investigate and resolve any issues. Your TAM/CSM and our Support team would be happy to help if you require any additional advice.

Next steps

If you're ready to start setting up the BigQuery integration, part 1 of the setup guide is here.

[Tag for search purposes: Big Query]

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