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Development & Collaboration

Challenges

01. Secure Data Access and Collaboration

A FinTech company specializing in open banking, faced challenges in securely accessing and collaborating on financial data for their machine learning projects. They struggled with a standalone AWS EC2 machine, multiple VPNs, and temporary credentials that often expired, making data access and collaboration cumbersome.

02. Onboarding and Team Collaboration

The complexity of their existing infrastructure made onboarding
new team members difficult. Collaboration within the Machine
Learning team and with stakeholders was hindered by the lack
of a seamless and secure platform for data analysis and
sharing insights.

Solutions

Adoption of Datalore

The Fintech Company addressed these challenges by adopting Datalore, a secure and collaborative data science platform. Datalore enabled the team to securely access data while meeting strict security requirements, significantly improving collaboration within the Machine Learning team and with stakeholders.

Improved Data Analysis and Reporting

Within their Machine Learning team, the company heavily utilizes Datalore for data exploration, visualization, and storytelling. The platform's intuitive interface, support for Python libraries like pandas, and collaborative features such as shared notebooks and version history greatly enhance their data analysis and reporting capabilities.

Integration with Development Tools

The Fintech company integrates Datalore with other development tools like PyCharm and Code With Me for model prototyping, training, and API development. This seamless integration streamlines their workflow and improves productivity across different tasks.

Future Expansion and Accessibility

Looking ahead, the Fintech company plans to expand Datalore usage to software and data engineers, simplifying data access and analysis for a broader range of team members. This approach aims to lower the barrier of entry for accessing and utilizing data products within the organization.

Challenge: Striking the Perfect Balance

Ensuring quality code meets efficient deployment, seamlessly integrated with GitLab through IntelliJ IDEA.

Solution: JetBrains Tools

IntelliJ IDEA, a flagship IDE from JetBrains rewarded team’s success. Its powerful code analysis, intelligent coding assistance, and seamless integration with GitLab provided the team with a comprehensive development environment.

But the story doesn't stop there. TeamCity, another JetBrains gem, entered the scene to automate the build, test, and deployment pipelines. This combination laid the foundation for an agile development process that seamlessly blended quality and efficiency.

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