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Data Harvesting
Accessing data is expensive and time consuming, and is often the culprit
leading to project failure.
Data harvesting technology is built into
every Quantellia model and is core to process: it automatically
analyzes your decision
model to find which information is most needed: what you need, and nothing more.
Sometimes a hundred inputs mean nothing, and targeting
just one piece of critical information makes all the difference.
Information changes rapidly, and your knowledge of
how to use it evolves over time.
Quantellia users work iteratively, which means
that they build a model, add data, test the model,
add more data (or update the model), repeating this process
as needed.
Quantellia Infonomics AnalysisTM
allows you to understand the cost and
value of inputs to your model, as well as the cost and value of metadata,
like a validation
constraint that says "if this price is over a hundred pounds then the discount
level field must be populated".
Quantellia software reasons about data costs, as well as values, to guide
iterative data harvesting.
(See how Quantellia Infonomics Analysis operates in the context of a worked example here.)
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Our consulting team can
work with your IT or other technical
groups to create automated interfaces to your data sources.
We can perform data harvesting work ourselves or
train your team,
Other offerings include:
- Data cleansing
- Empirical data gathering / market research
- Data migration
- Performance optimization
- Data model design
- External data source integration
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