Feb 15, 2024
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Ongoing
Data Architecture: Unique Collection & Storage
$100,000+
more 1 year
United States
10+
Service categories
Service Lines
Big Data
Cloud Consulting
Software Development
DevOps
QA and Testing
Domain focus
Other
Transportation & Logistics
Challenge
As the business was growing and scaling exponentially, the data flow was increasing daily, and new challenges were arising:
- Scale the system to support the exponential SaaS customer base growth, and speed up the onboarding process for new customers.
- Ensure that increased load or data quality issue for some customers is not affecting others.
- Ensure bulletproof data privacy and client experience compartmentalization.
- Ensure that the complexity of the solution and maintenance cost would both remain under control as the number of customers increased and collected data and customizations grew exponentially.
As the business was growing and scaling exponentially, the data flow was increasing daily, and new challenges were arising:
- Scale the system to support the exponential SaaS customer base growth, and speed up the onboarding process for new customers.
- Ensure that increased load or data quality issue for some customers is not affecting others.
- Ensure bulletproof data privacy and client experience compartmentalization.
- Ensure that the complexity of the solution and maintenance cost would both remain under control as the number of customers increased and collected data and customizations grew exponentially.
Solution
The team created a unique architecture for collecting and storing petabytes of data which allowed analyzing it to generate meaningful insights and statistics. Customers were isolated from each other while the code and core functions were shared. Whenever a new feature was added for one customer, it was possible to reuse it for others. At the same time, the design guarantees data privacy and security for each customer.
Finally, the newly-created architecture allowed smooth onboarding of new customers regardless of the data structures and business processes they are using.
The team created a unique architecture for collecting and storing petabytes of data which allowed analyzing it to generate meaningful insights and statistics. Customers were isolated from each other while the code and core functions were shared. Whenever a new feature was added for one customer, it was possible to reuse it for others. At the same time, the design guarantees data privacy and security for each customer.
Finally, the newly-created architecture allowed smooth onboarding of new customers regardless of the data structures and business processes they are using.
Results
By creating a solution that ensures an extreme level of data privacy and security, the team leveraged the platform’s anonymized knowledge for the mutual benefit of all the platform clients.
“We’ve been impressed with the quality of teammates and the speed at which Zoolatech has been able to source and land engineers that could help our internal team. On top of that, they’ve ensured that they choose teammates that have experience with the technology stack we’re dealing with”
Alex Ramirez, CEO, CognitOps
By creating a solution that ensures an extreme level of data privacy and security, the team leveraged the platform’s anonymized knowledge for the mutual benefit of all the platform clients.
“We’ve been impressed with the quality of teammates and the speed at which Zoolatech has been able to source and land engineers that could help our internal team. On top of that, they’ve ensured that they choose teammates that have experience with the technology stack we’re dealing with”
Alex Ramirez, CEO, CognitOps
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