Big Data analytics is not the first thing that comes to mind when addressing the characterization phase of a new semiconductor product, since it’s a process that is typically conducted on a relatively limited number of devices.

But in fact, when considering the growing functionality and complexity of next generation ICs, it quickly becomes apparent that the number of tests-per-part and test condition combinations required can reach tens and even hundreds of thousands – big data, indeed.

EXACT derives maximum value from characterization data and streamlines the process:

Expedite data collection

Engineers tend to run characterization experiments manually and often. EXACT eases the arduous task of collecting, cleansing and annotating characterization data – which is typically less well-structured than production data – through our “Sandbox” capability, so that the process becomes more efficient and the results are far more accurate and complete.


Fine-tune analysis

EXACT provides all the capabilities you need to comprehensively analyze and chart the behavior of a new semiconductor product based on parametric and functional measurements across process, voltage and temperature conditions; lot names, product identifiers and much more.


Increase team collaboration

EXACT enables semiconductor companies to solve the typical disconnect that exists between the multiple teams working on new product characterization by enabling real transparency and collaboration.


Provide accurate reports

EXACT enables quick report generation of all characterization analyses, so that every stakeholder can easily review the detailed results that pertain to their areas of involvement in the project.

How It Works

Big Data for Better Characterization

The value of being able to apply extreme analytics to the characterization process is clear: the more data captured, compared and analyzed and the more actionable insights gained before production ramp-up begins, the better the chances of ensuring the creation of a high-quality performance product that is less prone to problems during high-volume productions and that subsequently results in fewer RMAs.


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Data set
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Data Analysis
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Report Generation
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