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Boost productivity with a Data Lake

DIGITAL TRANSFORMATION • DEVELOPMENT • DIGITAL TRANSFORMATION • DEVELOPMENT • DIGITAL TRANSFORMATION • DEVELOPMENT • DIGITAL TRANSFORMATION • DEVELOPMENT

Challenge

Address our client’s data management challenges

1

2

3

Duplicated Efforts

Each application developed and maintained its own ETL processes.

Lack of standardization​

Data formats and quality standards varied across applications.

Inconsistent information​

Data variations between applications caused confusion and decision-making problems.

Challenge

Address our client’s data management challenges

1

Duplicated Efforts

Each application developed and maintained its own ETL processes.

2

Lack of standardization​

Data formats and quality standards varied across applications.

3

Inconsistent information​

Data variations between applications caused confusion and decision-making problems.

Project

Our AWS Glue-powered data platform centralizes data in a secure S3 data lake, standardizes formats and quality, and ensures consistency with a single source of truth.

Dashboard showing state of the plant.

Built with infrastructure as code (IaC) for streamlined management, it empowers data transformation and quality control.

The platform was developed using Python and integrated with Looker, enabling non-technical users to create their own reports.

Built with infrastructure as code (IaC) for streamlined management, it empowers data transformation and quality control.

The platform was developed using Python and integrated with Looker, enabling non-technical users to create their own reports.

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Python logo
AWS logo
Looker logo

Achievements

Increased efficiency

ETL processes were streamlined and automated.

Improved data quality​

More accurate and reliable insights.

Empowered
users​

Users could analyze data using self-service tools like Looker.

Scalable solution​

It can be adapted to meet the needs of businesses of all sizes.

Cost-effective​

Reduces the time and effort required to manage data.

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