FINANCIAL ENTERPRISE

Improving data analytics to drive smarter decisions for a financial services provider

Financial enterprise project

The client

The client in a NYC based Fortune500 financial services company.

Country

USA

Industry

VC/PE

Finance

Type

Enterprise

The product

We supported the data science team of our client who was looking to improve the delivery of analytics reports to help managers make informed business decisions.

Technologies

Python

Django

Pandas

Numpy

JavaScript

Typescript

React

Apache Airflow

AWS

Terraform

Docker

image Financial enterprise product

The challenge

Business

The financial sector is experiencing unrelenting competition. Organizations that want to thrive must be quicker and smarter in acquiring insights from data to make data-driven business decisions.

The client was looking for software developers who would support the internal data science team with Python expertise and know-how. The primary business goal was developing a system that would enable them to deliver analytics reports quickly and efficiently to support the decision-making process at the organization.

Technology

First, our team implemented data pipelines. Next, we migrated the organization's data to a new data warehouse. We were also responsible for supporting the client's internal team of data scientists in completing various tasks and sharing best practices in the field.

We advised the client about the choice of programming tools such as CI, repository organization, and linters through their evaluation and consultancy in reference to the planned infrastructure for the implementation of Airflow.

Duration

2018 - ongoing

image Financial enterprise challenge

The solution

Since completing the data warehouse migration from Athena to Snowflake, the client’s team can now work with data more efficiently and with greater confidence. We also released our own instance of Apache Airflow for automating data processing to improve the user experience.

Our team helped in implementing Continuous Integration/Continuous Delivery (CI/CD) practices and shared other relevant know-how with the client’s team of data scientists.

Engagement Type

Dedicated development teams

Expertise

Data engineering

Fullstack web development

DevOps

Results

Successful data pipelines implementation

Successful data warehouse migration to Snowflake

Built internal Data Portal to automate routine tasks

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Selected work

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