QUESTION 94
Refer to the Exhibit.

You are going into a meeting where you anticipate your manager will have a question on your dataset. Specifically, your manager will want to know about customers that are classified as renters with a good credit status. In order to prepare for the meeting, you create a rule: RENTER => GOOD CREDIT.
What is the confidence of this rule?
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QUESTION 95
Consider the following SQL query:
SELECT product_id FROM supplier_A
UNION
SELECT product_id FROM supplier_B;
What is the expected result?
Response:

QUESTION 96
You are provided with the following list. Which window function is missing?
cume_dist()
dense_rank()
rank()
percent_rank()
first_value()
last_value()
lag()
lead()
ntile()
Response:

QUESTION 97
You are assigned the task of creating customer profiles for your company. In your database, you have 25 key input variables that come together to define 2,500 customers. You decide to run a K-means cluster analysis on the 25 input variables based on k=4 to build your profiles.
Your analysis resulted in four cluster populations:
Cluster A=1,000 customers
Cluster B=560 customers
Cluster C=925 customers
Cluster D=15 customers
What should be attempted first to more evenly distribute the customer population across clusters?
Response:

QUESTION 98
Refer to the exhibit.

You are using k-means clustering to discover groupings within a data set. You plot within- sum-of-squares (wss) of multiple cluster sizes. Based on the exhibit, how many clusters should you use in your analysis?
Response:

QUESTION 99
The Marketing department of your company wishes to track opinion on a new product that was recently introduced. Marketing would like to know how many positive and negative reviews are appearing over a given period and potentially retrieve each review for more in- depth insight.
They have identified several popular product review blogs that historically have published thousands of user reviews of your company’s products. You have been asked to provide the desired analysis.
You examine the RSS feeds for each blog and determine which fields are relevant. You then craft a regular expression to match your new product’s name and extract the relevant text from each matching review.
What is the next step you should take?
Response:

QUESTION 100
Refer to exhibit.

You are asked to write a report on how specific variables impact your client’s sales using a data set provided to you by the client. The data includes 15 variables that the client views as directly related to sales, and you are restricted to these variables only.
After a preliminary analysis of the data, the following findings were made:
1. Multicollinearity is not an issue among the variables
2. Only three variables A, B, and C have significant correlation with sales You build a linear regression model on the dependent variable of sales with the independent variables of A, B, and C. The results of the regression are seen in the exhibit. You cannot request additional data.
What is a way that you could try to increase the R2 of the model without artificially inflating it?
Response:

QUESTION 101
How are window functions different from regular aggregate functions?
Response:

QUESTION 102
On analyzing your time series data you suspect that the data represented as y1, y2, y3, … , yn-1, yn may have a trend component that is quadratic in nature.
Which pattern of data will indicate that the trend in the time series data is quadratic in nature?
Response:

QUESTION 103
Imagine you are trying to hire a Data Scientist for your team. In addition to technical ability and quantitative background, which additional essential trait would you look for in people applying for this position?
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QUESTION 104
You are performing a market basket analysis using the Apriori algorithm. Which measure is a ratio describing the how many more times two items are present together than would be expected if those two items are statistically independent?
Response:

QUESTION 105
What describes a true limitation of a Logistic Regression method?
Response:

QUESTION 106
You have plotted the distribution of savings account sizes for a bank.

Based on the distribution shown in the exhibit, how would you proceed?
Response:

QUESTION 107
What is the primary function of the NameNode in Hadoop?
Response:

QUESTION 108
You are using the Apriori algorithm to determine the likelihood that a person who owns a home has a good credit score. You have determined that the confidence for the rules used in the algorithm is > 75%. You calculate lift = 1.011 for the rule, “People with good credit are homeowners”.
What can you determine from the lift calculation?
Response:

QUESTION 109
You have scored your Naive Bayesian Classifier model on “hold out” test data for cross validation. You have determined the way the samples scored and have tabulated them as shown in the exhibit.

What are the Precision and Recall rates of the model?
Response:

QUESTION 110
You are using k-means clustering to classify heart patients for a hospital. You have chosen Patient Sex, Height, Weight, Age and Income as measures and have used 3 clusters.
When you create a pair-wise plot of the clusters, you notice that there is significant overlap between the clusters. What should you do?
Response:

QUESTION 111
Which activity is performed in the Operationalize phase of the data analytics lifecycle?
Response:

QUESTION 112
How is HDFS defined?
Response: