In a view
Caetsu Two, a 360 service advertising agency, part of the Domingo Alonso Group and Salvador Caetano Group, which operates in more than 20 markets, undertakes a project of integral datification of the operation that seeks to add value to the data generated by the advertising operation, with a clear strategy of governance and data modeling using Looker and BigQuery. As well as improving their knowledge and skills in the creation of dashboards, empowering the user in the consumption of data.
Caetsu Two was in the process of modernizing its Data Warehouse and democratizing its data. And, the agency felt that it should continue to evolve the data strategy, on the one hand, getting more out of it internally, facilitating and automating all processes, with all stakeholders, as well as externally, facilitating, making transparent and democratizing the data generated by the entire advertising operation to the brands they work with.
The main challenge that Caetsu Two has encountered along the way has been to connect all the silos caused by the geography of the organization, as well as the homogenization of the huge amount of data sources (CRMs, analytics tools, DSPs, platforms…) with which they work and those of their clients. In addition, being an Advertising Agency with international campaigns that need individual data governance of each client, Caetsu Two, wanted to have control over the tracking of marketing campaigns.
Some of the main challenges it was facing:
- To solve the problem of visualization, availability and traceability of the advertising operation data, in real time and on the brands they work with. And to improve and automate the internal operation through the orderly and structured use of data, allowing us to optimize and manage advertising campaigns in real time.
- Some of the main obstacles they faced were the dispersion of data, and a lack of strategy in the whole definition of business entities.
- Caetsu Two was looking for a partner that could help them with the design of the data architecture, as well as the implementation and development of dashboards.
Caetsu Two had a fragmented data analysis system that was difficult to manage. This made it difficult to get relevant insights from its data to make strategic decisions.
- Looker as a BI platform: This platform allowed users to create and share customized dashboards and reports.
- Semantic Model: This model provided a common description of the data, which facilitated its understanding and analysis.
- Decoupling users/developers: This approach allowed users to generate their own reports and dashboards without the need for developer intervention.
- User Self-Service: This feature allowed users to access data and analytics without going through an approval process.
- Embedding dashboards in applications: This functionality allowed dashboards to be embedded in web or mobile applications.
Main results and benefits
Improved data visibility
Efficiency increase and improved decision making
Autonomy in the development of LookML reports and dashboards.
Source of truth and quality in their BI processes
Security and user access to Explorers and Dashboards on Looker
Documentation and procedures for deployment of data models and dashboards
Application of best practices/standards in the Looker and BI environment
Do you want to improve your data analysis and make more informed decisions, like Caetsu Two?
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