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Analytics and Big Data

Analytics and Big Data

Creating and delivering customized financial services solutions in the Cloud


A multinational investment bank and financial services company made the decision to move their big data to the cloud in order to decrease costs and increase their ability to scale. Working with a third party or using a public cloud service was not a potential solution, because the smallest risk of having a single leak of data would be unacceptable. Data security was paramount to the client; the cloud service had to be impregnable and impenetrable to anyone outside the organization. Once completed, the goal was to provide each user in the organization a unique username and password to access the data, with individualized permissions and restrictions.


The client needed a customized solution for this initiative, one which ensured the integrity and security of their data. Unable to work with a third-party service provider, the resolution was to build the cloud storage service in-house. This would be a huge and costly project, so the client approached Saggezza to assist with one of the most crucial components, converting all of the data to the cloud. The data needed to be transferred in a single format, and during this process, there could be no distortion or misplacement of any single piece of data.


Saggezza was tasked with the initial undertaking, and began converting all the client’s data into a single format, regardless of the data’s original form. The data needed to be converted from it’s unstructured form to structured and simplified for easy access and manipulation by the client.

While converting the data, Saggezza ensured that no information was lost or distorted. Working closely with the client’s cloud security team, Saggezza was able to secure and re-write all the client’s data into a single structured format. The data was converted into AVRO and pushed into the cloud, making it easily accessible. In the end, the client could use this new structured data in descriptive analytics, to gain useful insight into the past.

More importantly, the client was able to now use this data with machine learning algorithms, to engage in predictive analytics. Predictive analytics utilizes various statistical models to analyze past data and make predictions about future trends and potential outcomes.


Apache Avro is a data serialization system. It stores the data definition in JSON format making it easy to read and interpret.

Apache Hadoop is a collection of open-source software utilities that facilitate using a network of many computers to solve problems involving massive amounts of data and computation.

Java is a general-purpose programming language that is class-based, object-oriented, and designed to have as few implementation dependencies as possible.

Saggezza is a proven technology and consulting partner that delivers personalized, high-value solutions to accelerate business growth.

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