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ARM 401 – 4 (Big Data) – Comprehensive Study Guide
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ARM 401 – 4 (Big Data) – Comprehensive Study Guide
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ARM 401 – 4 (Big Data) – Comprehensive Study GuideBig Data Right Ans - Sets of data that are too large to be gathered and
analyzed by traditional methods.
Data Governance Right Ans - Is a framework of rules, standards and
decisions for managing data. The program set standards and oversee the
management of a firm's data assets in order to meet quality standards and to
prevent abuse.
Five Characteristics of Big Data Right Ans - 1. Volume
2. Variety
3. Velocity
4. Veracity
5. Value
Sources of Big Data Right Ans - Internal data - Owned, captured and stored
by an organization.
External data - Belongs to an entity other than the entity that wishes to use it.
Internal Data Right Ans - Data owned by the entity that uses it.
External Data Right Ans - Belongs to an entity other than the entity that
wishes to use it.
Structured Data Right Ans - Is data organized into databases
with defined fields and links between and among
databases.
Unstructured Data Right Ans - Is data that is not organized and
that often consists of text, images, and nontraditional media.
Third-party data includes Right Ans - Geo-demographic data (classification
of population), economic data (interest rates, assets prices, exchange rates
and consumer pricing index) and credit rating
Economic data. Right Ans - Includes interest rates, asset prices, exchange
rates, and the consumer price index
, Geodemographic data Right Ans - Regards classifications of population
groups.
Big Data Categories Right Ans - 1. External and structured - telematics,
financial data, labor statistics.
2. External and unstructured - Social media, new reports and internet videos.
3. Internal and Structured - Policy information, claims history and customer
data.
4. Internal and unstructured - Adjusters notes, customer voice recordings and
surveillance videos.
Predictive Modeling Right Ans - Uses a defined target variable to predict or
estimate an unknown outcome. Used to predict future values and estimate
unknown past or present values.
Target Variable Right Ans - Is the attribute whose value is being predicted
in a data analytical model.
Seven Steps in Building a Predictive Model Right Ans - 1. Gather historic
data.
2. Divide date into training data and holdout data.
3. Build the model using the training data.
4. Apply the model using the training data.
5. Use performance metrics to evaluate the model.
6. Use feedback to adjust the model, repeating Steps 3, 4 and 5 as needed.
7. Put the model into production and reevaluate as needed.
Training a Predictive Model Right Ans - Using existing data to create
predictive models that help them anticipate behaviors.
Training Data Right Ans - Data that is used to train a predictive model and
that therefore must have known values for the target variable of the model.
Overfitting Right Ans - Occurs when the model is so closely tailored to the
training data that it is not effective on other, new data.
Holdout Data Right Ans - Existing data with a known target variable that is
held back and not used as part of the training data. The data is used to test the
model to make sure that it performs well on known data.
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