Navent migrates its data architecture to accelerate data-driven decisions
Navent, a leader in online classifieds in Latin America, had its data platform on another public cloud that no longer met the scalability and performance the business needed. Together with its team, Amarello implemented a data architecture on Google Cloud with a realistic roadmap: in six months they migrated the entire architecture, with improvements and benefits for the business.
- Client
- Navent
- Sector
- Online classifieds
- Country
- Argentina
- Project
- Data migration and architecture on Google Cloud
- Technologies
- BigQuery · Cloud Composer · Data Fusion · Google Cloud
In numbers
- 3x
less time consuming analytics in Business Intelligence tools
- 6 months
to migrate the entire data architecture to Google Cloud
- 10%
less operational load for the data team, with a target of 40%
In short
Navent is a company of the Quinto Andar group, a leader in Latin America in online classifieds, with a presence in Argentina, Mexico, Brazil, Peru, Panama and Ecuador, oriented to helping people find a home.
Amarello, together with the Navent team, achieved a successful migration by applying its experience to implement an optimal data architecture on Google Cloud, with a realistic roadmap that also delivered improvements and benefits to the business.
01 · The problem
Multiple lines of business, lots of data and a platform with bottlenecks
- 01
Complexity and volume
With multiple lines of business, analyzing the portfolio, sales, customer behavior, marketing and their multiple segmentations is a challenge in itself, due to the complexity and volume of data.
- 02
Scalability and performance
The previous solution, on another public cloud, no longer met the scalability and performance the business needed.
- 03
Bottlenecks
There were multiple bottlenecks in data and processes that slowed down the delivery of reports.
02 · How we solved it
BigQuery as the cornerstone, Composer to orchestrate and Data Fusion for ETL
- 1
BigQuery and security at all levels
The cornerstone of the solution is BigQuery, for its high elastic and cost-effective processing power, with data security measures at all levels.
- 2
Orchestration and ETL processes
Cloud Composer improved the architecture through its capabilities to orchestrate the data lifecycle in a robust way, and Data Fusion paved the way for ETL process improvement.
03 · The benefit for the client
Faster analytics, lower cost and a team focused on value
Speed
- A 3x time reduction in the consumption of analytics in Business Intelligence tools.
Cost
- Costs improved thanks to the native elasticity of Google Cloud.
Operations
- Data and process bottlenecks were solved.
- The data team reduced its operational load by 10%, with the expectation of reaching 40%, to focus that effort on delivering value to the business.
In the client's words
I have been in the BI & Analytics world for more than 16 years, I have worked with other architectures and On Premise and Cloud solutions, but I had never experienced such a simple and intuitive process as in Google Cloud. In 6 months we migrated our entire architecture to GCP. We got a great improvement in data mining and BI reporting delivery for data-driven decision making.
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