Comparison Area WebQuery BQ Connector Datastudio Connector API Technical complexity Low Medium Medium High Ease of report customization High Medium Low High Reporting Details Complete Limited

Reports not supported on API are not available

E.g.

Location targets

Remarketing targets

Audience reports Possible Data Warehouse Any

The report is generic and needs to be loaded into the data-warehouse using DWs custom loading methods. BigQuery ONLY None Any

Solution Approach

Customers’ business data resides in a data-warehouse , which is designed for analysis, insights and reporting. To integrate ads data into the data-warehouse, the usual approach is to bring/ load the campaign data into the warehouse; to achieve this, SA360 offers various options to retrieve paid-search data, each of these methods provide a unique capabilities.Comparing these approaches, in terms of technical knowledge required, as well as, support for data warehousing solution, the easiest one is WebQuery report for which a marketer can build a report by choosing the dimensions/metrics they want on the SA360 User Interface.BigQuery data-transfer service is limited to importing data in BigQuery and Datastudio connector does not allow retrieving data.WebQuery offers a simpler and customizable method than other alternatives and also offers more options for the kind of data (vs. BQ transfer service which does not bring Business Data from SA360 to BigQuery). It was originally designed for Microsoft Excel to provide an updatable view of a report. In the era of cloud computing, a need was felt for a tool which would help consume the report and make it available on an analytical platform or a cloud data warehouse like BigQuery.This tool showcases how to bridge this gap of bringing SA360 data to a data warehouse, in generic fashion, where the report from SA360 is fetched in XML format and converted it into a CSV file using SAX parsers. This CSV file is then transferred to staging storage to be finally ETLed into the Data Warehouse.As a concrete example, we chose to showcase a solution with BigQuery as the destination (cloud) data warehouse, though the solution architecture is flexible for any other system.