About

Teaming up with Strongbytes, an IPGE platform aimed to smoothly source, de-identify, and match 330 million patient data entries with top-tier precision. Ensuring HIPPA compliance, the initiative reshaped the landscape of data handling in healthcare. Read more

CASE STUDY DETAILS

Under MNDA

Enterprise/Corporation

Team augmentation

1 - 5 people

Ongoing for 9 months

€50 - 250K

Scrum

FOCUS AREA

Challenge, approach, and impact

  • Varied and Unstructured Data

    The vast majority of incoming data was inconsistent, appearing in multiple forms, and predominantly unstructured. Achieving accurate data ingestion presented a formidable challenge due to these disparities.

  • High Volume Transactions

    Handling 1.5 billion transactions from diverse sources and converting this data into standardized sink tables was an enormous task. Ensuring the precision and efficiency of this process was crucial.

Testimonials

Two blue lines

“Our biggest challenge in this project was the fact that we were handling a massive amount of data, coming from multiple sources and we needed to find a way to operate with this, in a compliant and secure way. Matching data to standardized tables then came after sufficient research and analysis using NLP and Deep Learning Classification.“ Read more

Anonymous

Delivery Manager

VERIFIED

Two blue lines

“Our biggest challenge in this project was the fact that we were handling a massive amount of data, coming from multiple sources and we needed to find a way to operate with this, in a compliant and secure way. Matching data to standardized tables then came after sufficient research and analysis using NLP and Deep Learning Classification.“ Read more

Anonymous

Delivery Manager

VERIFIED

Two blue lines

“Our biggest challenge in this project was the fact that we were handling a massive amount of data, coming from multiple sources and we needed to find a way to operate with this, in a compliant and secure way. Matching data to standardized tables then came after sufficient research and analysis using NLP and Deep Learning Classification.“ Read more

Anonymous

Delivery Manager

VERIFIED

Two blue lines

“Our biggest challenge in this project was the fact that we were handling a massive amount of data, coming from multiple sources and we needed to find a way to operate with this, in a compliant and secure way. Matching data to standardized tables then came after sufficient research and analysis using NLP and Deep Learning Classification.“ Read more

Anonymous

Delivery Manager

VERIFIED

Two blue lines

“Our biggest challenge in this project was the fact that we were handling a massive amount of data, coming from multiple sources and we needed to find a way to operate with this, in a compliant and secure way. Matching data to standardized tables then came after sufficient research and analysis using NLP and Deep Learning Classification.“ Read more

Anonymous

Delivery Manager

VERIFIED

Two blue lines

“Our biggest challenge in this project was the fact that we were handling a massive amount of data, coming from multiple sources and we needed to find a way to operate with this, in a compliant and secure way. Matching data to standardized tables then came after sufficient research and analysis using NLP and Deep Learning Classification.“ Read more

Anonymous

Delivery Manager

VERIFIED

Team Structure

Client Team

Daily point of contact

Product Owner

The client stakeholders worked closely with the team at Strongbytes

Client logo

Agency Team

Production

2 x Machine Learning Engineer

Production

1 x Frontend Developer

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