Connecting to BigQuery

Getting Started

Global Functions

Lucanet Lume

Data Hub

Administration

Extended Planning & Analysis (xP&A)

xP&A Video Tutorials

User Roles in Lucanet xP&A

Lucanet xP&A User Interface

All Steps at a Glance

Basic Concepts and Elements

Creating a Model

Integrating Data

Connecting to a Data Source

Connecting to a Spreadsheet

Connecting to an Accounting System

Connecting to a BI/Database System

Defining Database Queries

Connecting to BigQuery

Connecting to Postgres

Connecting to Databricks

Connecting to Microsoft SQL Server

Connecting to MySQL

Connecting to Redshift

Connecting to Snowflake

Connecting to Looker

Connecting to a CRM System

Connecting to an HRIS/Payroll System

Connecting to a Lucanet CFP Data Source

Connecting to a Source System Using a Webhook

Sharing Data Connections

Working With Integrated Data

Guideline for Exchanging Data Between xP&A and CFP

Modeling Your Data

Viewing and Visualizing Data

Working with Models

Using Comments and Descriptions

Comparison: xP&A vs. Excel Performance

Consolidation & Financial Planning

ESG Reporting

Disclosure Management

XBRL Tagger

Lease Accounting

Banking & Cash Management

Data Collection

Tax Compliance & Reporting

Glossary

You can establish a direct connection to BigQuery to pull in data into xP&A.

This article contains a description of the prerequisites and the individual steps of the set-up process.

The fields that are pulled in must be defined during the set-up process using a database query. For a detailed instruction on how to structure such a query, see Defining Database Queries.

In order to prevent the accidental import of large amounts of data, there is a limit on the number of rows (150,000) and the number of items (100) you can have in a dimension when importing data from BigQuery.

Data sources that exceed these limits can negatively affect the performance of your model.

If you would like to remove these limits, please reach out to your Lucanet contact person.

To reduce the size of your data, aggregate it to the granularity you intend to use in xP&A (day, week, month) using SQL.

Before connecting to BigQuery, you need to create a Google service account and an associated key.

A service account is a special kind of account for non-human users. For more information, see Understanding Service Accounts. The key is required during the set-up process of the connection in xP&A.

You might need privileged access to your Google infrastructure in order to create a service account. For more information, see Create service accounts.

To create the service account in Google:

Open your Google Cloud Dashboard, and go to Service Accounts page.

Shows the Dasboard menu of Google Cloud. Highlighte dis the section "Service Accounts" — Google Service Accounts

Click + Create service account.

Enter a name and an ID for the service account and click Create and continue.

Shows the dialog 'Service account details'. Highlighted are the fields to enter the name and the ID of the account — Enter service account name and ID

Grant xP&A access to BigQuery by assigning the Role BigQuery Admin and click Continue.

Shows the dialog 'Grant this service accpunt access to project'. Highlighted is the dropdown menu 'Role' and the 'Continue' button — Assign 'BigQuery Admin' role

Go back to the Service Accounts page and click on the service account you just created.

Open the Create key menu and choose Create new key.

Shows the details of the service account. Highlighted is the dropdown menu 'Add key' and the 'Create new key' option — Create new key

In the next dialog, slect JSON as key type and click Create to create and download the key.

To connect to Postgres:

Choose one of the following options:

Open the

Data

workspace from the overview on the start page and click

+ New.

Shows the start page of Lucanet xP&A. Highlighted are the buttons that need to be used to create a new data source connection from the start page. — New data source connection from the Data workspace

Open the model into which you would like to integrate the data, click the

sign next to

Data

in the overview, and choose

New data source

In the Data sources dialog, open the BI/Database tab and choose BigQuery.

Shows the Data Sources dialog. Highlighted in red is the 'BI/Database' tab. — 'BI/Database' tab

The New Data Source dialog is displayed as follows:

Shows the 'New Data Source' dialog for a BigQuery connection — 'New Data Source' dialog for BigQuery

Configure the steps as described in the following section.

Click Create data source.

The following steps are required to set up the data source:

Choose a connection

Choose an existing connection, or, if you have not configured a connection yet, click New Connection and upload the JSON file you created for the Google service account (as described in Creating a Google Service Account and Key)

Complete the query form

Enter the following:

Data source name

Query

to define the fields which are to be pulled in. For more information, see

Defining Database Queries

Name of the

Date

column

, which must be one of BigQuery's date formats

Names of the columns that contain

variables

(which must have a

numeric

data type.)

Any remaining columns will be treated as dimensions, and must have a string data type.

An exception is the cohort dimension, which must be a date, with the column header explicitly labelled Cohort.

This content was generated using AI and reviewed by Lucanet subject matter experts before publication.

Last updated on May 1, 2026

Overview

Limits for Data Imported from BigQuery

Prerequisites for the Setup

Creating a Google Service Account and Key

Connecting to BigQuery

Set-up Steps

Overview

Limits for Data Imported from BigQuery

Prerequisites for the Setup

Creating a Google Service Account and Key