Snowflakes AD MCQ

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HDFS
Bash scripts can automate what HDFS task?
Ans. Ingesting, exporting, and moving data
Which of the following commands creates a zero-length file in HDFS?
Ans. HDFS dfs -touchz
Pig was developed by Facebook as a data warehouse application for Hadoop.
Ans. FALSE
Before dropping a table in HBase, what command must you use first?
Ans. Disable
Which of the following is a use case for Sqoop?
Ans. Bulk transfers of data of structured data into HDFS
In what language is HDFS written?
Ans. Java
Bash scripts are written in what language?
Ans. POSIX Commands
Sqoop is an application that allows you to import and export data from:
Ans. Relational and NoSQL Databases
What kind of database is HBase?
Ans. NoSQL
When removing a file using the rm command, files are deleted permanently.
Ans. False
HDFS allows for files to be updated.
Ans. False
Which command shares the same functionality as HDFS dfs commands?
Ans. Hadoop fs

NameNode is responsible for remembering where data is stored in the cluster
Ans. True
HiveQL is best described as a:
Ans. Declarative Language
What is Pig’s scripting language called?
Ans. Pig Latin
What new resource manager was released in HDFS 2.0?
Ans. YARN
How many columns can HBase Scale to?
Ans. Billions
When writing a Bash script for HDFS, you must specify ‘HDFS’ in script.
Ans. False
HBase uses SQL.
Ans. False
Sqoop ships with Hortonworks Data Platform.
Ans. True

PYSPARK

Which of these lists is ordered from slowest to fastest method of working with data?
Ans. One at a time, parallel, and then pipeline
What function was used before createOrReplaceTempView?
Ans. registerTempTable
What do you use to install Spark 2?
Ans. Parcels

What is the name of the component that serves as an entry point to a Spark
application when using the higher level API?
Ans. SparkSession
What Spark package should you use if you want to use TensorFlow?
Ans. TensorFrames
What do you use to create a Dataset from a DataFrame?
Ans. .as[]
What is another name for Python’s interactive shell?
Ans. REPL
Which type do you use to represent a field in a schema?
Ans. StructField
What type of function is collect?
Ans. An Action
Which year was the RDD paper published?
Ans. 2012
Which is the default sort order in Spark?
Ans. Ascending
What is the name of the Cloudera Hadoop administration tool?
Ans. Cloudera Manager
What type of class do you use to specify types in a Dataset?
Ans. Case class
What is the name of Cloudera’s Platform-as-a-Service offering?
Ans. Cloudera Altus
What do you need when you want to concatenate a string a column?
Ans. lit(‘yourstring’)

What is the name of the file used to configure application properties, which is used
by Spark during execution?
Ans. spark-defaults.conf
What happens if you assign an integer to a string variable in Python?
Ans. The variable becomes of type integer and holds the value.
Which of these functions is used to return data back to the driver?
Ans. Collect
What is it called when there is data shuffling involved?
Ans. Wide transformation
Which function do you use to register a Temporary View?
Ans. createOrReplaceTempView()
Where can you discover the current Java version in Cloudera Manager?
Ans. Support > About
How do you save or persist a DataFrame to a table?
Ans. saveAsTable
Which component of Spark optimizes queries, thus improving performance?
Ans. Catalyst Optimizer
Which function can be used to register user defined functions?
Ans. Udf
Which port is used by default by the Spark History Server?
Ans. 18089(In Pluralsite) or 18080(In Google)
Which function do you use to apply an operation to all items in a collection?
Ans. Map
How much faster is Spark than MapReduce?
Ans. 10x to 100x

When you save a Picklefile, what are you saving?
Ans. A SequenceFile with multiple Pickle objects
What is the name of the community index of third-party packages for Apache Spark?
Ans. spark-packages.org
How can you define Map?
Ans. Apply function to each element
What do you use to install Spark 2 Standalone on a Mac?
Ans. Homebrew
Which type of RDD can you use that is in the format of key value?
Ans. PairRDD
Which component is in charge of reading and writing from and to data sources,
performing data processing, and storing intermediate results?
Ans. Executor
Which component of Spark optimizes for CPU and memory efficiency?
Ans. Project Tungsten
What command do you use to launch Spark 2 in a Python shell in a Cloudera
distribution?
Ans. pyspark2
When running Spark Standalone, what is the default assumed location?
Ans. file:///
Which is the default file format used by DataFrames?
Ans. Parquet
What is the name of Cloudera’s Platform-as-a-Service offering?
Ans. Cloudera Altus
What do you call a logical division of data?
Ans. Partition

When you sample data, what occurs if you specify withreplacement = True?
Ans. The probability of each item from being selected remains constant as other
items are taken
What do you use to install IPython in a Cloudera cluster?
Ans. Anaconda
What is the name of the component that serves as an entry point to a Spark
application when using the higher level API?
Ans. SparkContext
What do you have in a cell instead of a value?
Ans. A Catalyst Expression
Which type do you use to represent a schema?
Ans. StructType
Which of these lists contains only primitive types?
Ans. Strings, integers, floats, and Booleans
Which is the language used to create Spark?
Ans. Scala
What was the most important change in the release of Spark 2.0?
Ans. The unification of the Dataset and DataFrame API
What is the name of the original core abstraction in Spark?
Ans. RDD
What are the available SaveModes?
Ans. append, overwrite, error, and ignore

Getting Started with Stream Processing
What is checkpointing in streaming Spark applications?
Ans. Periodically saving data so state can be reconstructed from this intermediate
context
What are the basic components of any Spark application?
Ans. Driver, Executor and Receiver
Why does MapReduce NOT work well for streaming data?
Ans. It operates on a huge number files stored in reliable storage, typically running
jobs which can take hours or even days.
Which of these operations require real-time processing?
Ans. Requests on sale days to an e-commerce site
When are transformations considered stateful?
Ans. When they operate across multiple RDDs rather than a single RDD
You receive log messages at the rate of two messages per second and your batch
interval is five seconds. If the sliding window size is 20 seconds, how many RDDs
are included in the window at any point in time?
Ans. 4
In a sliding window operation, let’s say the summary function you want to apply
across a window is a multiplicative operation represented by this pseudocode:
multiple(a, b) {
return a * b
}
What is the pseudocode for the inverse function of this in the sliding window
operation?
Ans. divide(a, b){
return a/b
}

What attributes can represent a student in school?
Ans. Age, grade, test scores
What is the major difference in applying k-means clustering on batch vs streaming
data?
Ans. Determining how relevant older data is compared with newer data in the stream
You’re tracking trending news stories over the last 24 hours with your streaming
application and you receive news updates every hour. What kind of decay factor will
you use to perform streaming k-means clustering?
Ans. 0 < decayFactor < 1
Which of these are examples of stream processing?
Ans. Analyzing log messages to see whether all pages of the e-commerce site are up
and running
What are the two operations that can be performed on an RDD in Spark?
Ans. A transformation to create a new RDD and an action to retrieve results from an
RDD
Under what conditions would you use the updateStateByKey() function?
Ans. Summarizing across an entire DStream where each RDD in the stream is a pair
RDD
You receive log messages at the rate of two messages per second and your batch
interval is five seconds. The window size is 20 seconds and your sliding interval is 10
seconds.
How many RDDs enter and leave the window each time it slides?
(Remember that the same number of RDDs will enter and leave the window.)
Ans. 2

You’re tracking trending news stories over the last 2 days with your streaming
application and you receive a new batch of updates every hour. News received a day
ago is only half as important as the news received in the last hour. How would you
specify this forgetfulness in your streaming k-means algorithm?
Ans. Half-life of 24 batches
What is the relationship between a DStream and an RDD?
Ans. A DStream is made up of a sequence of RDDs, where every RDD contains
entities which are received within a batch interval.
You receive log messages at the rate of two messages per second and your batch
interval is five seconds. How many messages are included in one RDD in the
DStream?
Ans. 10

Structured Streaming in Apache Spark 2(PySpark)
Your e-commerce sites sends every transaction with product id as a stream to a Spark
application. The data sent can be assumed to always arrive on time. You want to keep
a global count of how many items of each product were sold and save this to an
RDBMS. What kind of output mode will you use when you write out this
information if you want to minimize updates to the RDBMS?
Ans. Update mode
Your e-commerce sites sends every transaction with product id as a stream to a Spark
application. The data sent can be assumed to always arrive on time. You want to keep
a global count of how many items of each product were sold and save this to an
RDBMS. What kind of aggregation would you perform on the incoming stream?
Ans. Group by product id and count the number of products
Which of the following relationships is correct regarding timestamps in streaming
data?
Ans. Event time < Ingestion time < Processing time
Which of the following are input arguments to the window function in structured
streaming?

A: The event time
B: The window interval
C: The sliding interval
D: The batch interval
Ans. A, B and C only
Which of the following is an improvement present in Spark 2 but not in Spark 1?
Ans. Unified APIs for batch as well as stream processing
How does a subscriber in Kafka receive messages from a publisher?
Ans. A subscriber subscribes to a topic and receives messages from all publishers to
that topic
What is a broker in Kafka?
Ans. A single node in a Kafka cluster
Which of the following is a timestamp that is assigned at the source of the streaming
data?
Ans. Event time
Which of the following is true of structured streaming
A: Can only work with streams using micro-batches
B: Interactions with output sinks are managed by the system
C: Ad hoc queries on streams are possible
Ans. B and C only
Which of the following is correct about the how the complete output mode works in
structured streaming?
Ans. The entire result table is recalculated
Which of the following are characteristics of RDDs in Spark?
A: They are distributed across multiple machines in the cluster
B: They can be reconstructed when a node crashes

C: They are stored on the hard disks of cluster machines
D: They are lazily evaluated
Ans. A, B and D only
What is a watermark as it applies to streaming data?
Ans. A watermark is the allowable lateness threshold for entities in a stream
Which of the following are important characteristics of any stream processing
system?
A: Ability to work with time-sensitive data
B: Manage out of order events
C: Replay data for recalculations
Ans. A, B and C
Which of the following are input arguments to the window function in structured
streaming?
A: The event time
B: The window interval
C: The sliding interval
D: The batch interval
Ans. A, B and C only
What does the explode() function in Spark do?
Ans. Creates a new row in the dataframe for every element
A single column data type in the schema for structured streaming is specified using
what data type?
Ans. StructField
In structured streaming, what is a trigger?
Ans. Events which determine when transformations on input data need to be reperformed

Which of the following is correct about the how the complete output mode works in
structured streaming?
Ans. The entire result table is recalculated

Data Essentials

1.On the Component tab displayed for the tSortRow component,
when you click to add criteria to the Criteria table, Talend
automatically populates the column values with defaults. In the “sort
num or alpha?” column Talend has chosen num by default for
customer_id as displayed. Which other values are available for the
“sort num or alpha?” column when you click to open the dropdown
list for that column?
Ans. date,alpha
2.You are using a tExtractDelimitedFields component to split the
Address2 field in the delimited file as displayed. What must you
specify as the Field separator property for the
tExtractDelimitedFields component to properly split the Address2
field?
ID;First_Name;Last_Name;Address1;Address2;Country
1;Claudia;Sand;10000 Main Dr NW;New York, NY;USA
2;Max;Bigot;60000 My St;Nashua, NH;USA
3;Rick;Tailleur;200000 Younge St;Toronto, ON;Canada
4;Noémie;Miller;500000 St. Catherines St Ouest;Montreal, QC;Canada
5;Catherine;Reilly;100000 Main St SW;Boston, MA;USA

Ans. “,” (a comma)

3. When configuring the properties for a tReplace component, you

can optionally click the Advanced mode checkbox. Doing so allows
you to specify what type of expression as the Pattern to search for?
Ans. Regular expression

When configuring the properties for a tAggregateRow
component. You are going to Group by the customer_id field in
order to aggregate the sales on a customer_id basis, so that in the
resulting output file you will have one row for each customer_id
with aggregated sales figures. Which Function value must you
choose when configuring the Operations table for this
tAggregateRow component?

Ans. Sum

5. You are using a tNormalize component to normalize the category
   field in the delimited file as displayed. What must you specify as the
   Item separator property for the tNormalize component to properly
   normalize the category field?
   product_id,product_name,category,unit_price
   1,Regular Widget,Normally Aspirated;Low Price;Highly Reliable,125
   2,Super Widget,Super;Medium Price;Very Reliable,250
   3,Turbo Widget,Turbo;Medium Price;Very Reliable,275
   4,S/T Widget,Super;Turbo;Premium Price;Reliable,425
   5,Hybrid Widget,Hybrid;Normally Aspirated;Premium Price;Reliable,425

Ans. “;” (a semi-colon)

6. Which of these statements accurately describes the Unique

Match Join match model in the Map Editor?
Ans. Last match is considered and passed to the output, Set as default
when configuring an explicit Join

7. You are building an expression in Map Editor for a column in

which you want to pad the row1.CustomerID string with leading
zeroes up to maximum length of 6 characters. Which code can you
use to accomplish this for you?
Ans. String.format(“$06d”,row1.CustomerID)

8. You have Map Editor open for a tMap object for which you are

mapping databases objects. You click the Join Model for a table Join
property. Which options appear in the Options dialog that appears?
Ans. Left outer join, inner join

9. You are building a filter expression in Map Editor for a column in

which you want to filter the product name, prd.name to equal
“Turbo Widgets”, and you want the transaction quantity, tx.qty to be
greater than 100. Which code can you use to accomplish this for
you?

Data Essentials

Ans. prd.name.equals(“Turbo Widgets”)&&tx.qty>100

10. Which common FTP operations are supported by Talend Open

Studio components available in the Palette?
Ans. Put
Selected
File Exist
Delete

11. What could be accomplished by using big data technologies?
    Ans. New product development and optimized offerings, Cost reductions
12. Velocity-The speed at which data is processed and becomes accessible
    Volume-The amount of data that exists
    Variety-The different types of data from XML to video to SMS
    Veracity-Making sure the data is accurate, which requires processes to keep
    bad data from accumulating in your systems
13. Which statements are correct about how Netflix utilizes big

data?
Ans. Netflix uses what is known as the big data recommendation algorithm
to suggest TV shows and movies based on a user’s preferences
Netflix has screenshots of scenes people might have viewed repeatedly, the
associated ratings, and the number of searches and the search topics

14. What are the main challenges that companies experience with

big data?
Ans. Unfamiliarity with big data and confusing it with traditional methods
Unprecedented data growth
Data security issues
Integrating data from a variety of sources

15. What are some examples of big data sources? Data Essentials

Ans. Open data, Social media, Sensor data, Email

16. What are some of the main business domains that use big data

tools today?
Ans. E-commerce industry, Aviation industry, Credit scoring agencies,
Transportation industry

17. What are the main deliverables of big data?

Ans. Text/image analytics, Multivariate analysis, Predictive models

18. What are the most important advantages of big data, according

to the International Institute for Analytics (IIA)?
Ans. Big data enables faster, better decision making
Big data leads to cost reductions
Big data helps to identify what customers need and to introduce new
products and services accordingly

19. Which statement is true about in-memory storage systems?

Ans. Data storage in an in-memory database is reliant on random access
memory (RAM)

20. What are the most important features of HDFS?

Ans. Replication, Scalability, Distributed storage, High availability

21. Which statement about parallel or distributed computing is true?

Ans. Distributed computing can allow an application on one machine to
leverage processing power, memory, or storage on another machine

22. Match each Hadoop component with its respective layer in the

Hadoop ecosystem. One layer will not be used.
Ans. ZooKeeper-Data management layer
HDFS-Data storage layer
Hive-Data access layer
MapReduce-Data processing layer

23. What are the benefits of migrating from Hadoop to the cloud? Data Essentials

Ans. Long-term cost savings, Better scalability, Better collaboration, Easy
access and resource availability

24. Which statements are true about unstructured data?

Ans. Unstructured data is very often linked to structured data. An example
is how X-ray images at a hospital are linked to patient IDs or health card
numbers.
Web pages, video files, and audio files are examples of unstructured data

25. Which statement about horizontal and vertical scaling is true?

Ans. Horizontal scaling is typically the easiest scaling option

26. Which statements are correct about HDFS?

Ans. HDFS provides high throughput access to application data by
providing the data access in parallel,
HDFS provides a fault-tolerant storage layer for Hadoop and its other
components

27. What are the differences between Hadoop and cloud

computing?
Ans. Cloud computing focuses on on-demand, scalable, and adaptable
service models, while Hadoop is all about extracting value out of volume,
variety, and velocity.
Cloud computing constitutes various computing concepts. This naturally
involves a large number of computers that are usually connected through a
real-time communication network. Hadoop, on the other hand, is a
framework that uses simple programming models to process large data sets
across clusters of computers.

28. Which statements accurately describe the differences between

big data and data warehousing?
Ans. Data warehouses only handle structured data (relational or nonrelational), whereas big data can handle structured, un-structured, or semistructured data.
While only DBMS compatible data are stored in data warehouses, all kinds
of data including transactional data, social media data (including audio and

video), machinery data, or any DBMS data can be stored and managed using
big data technologies.

29. Let’s say you have a two-dimensional numpy array called “twod”

and you want to split it row-wise into two equal halves. Then, which
of these numpy functions would you call on it to do so?
Ans. vsplit(twod,2)

30. Some of the features of digital images in Numpy are given below.

Which of these are true?
Ans. n numpy, images can be represented as a 3D matrix where the first two

dimensions represent the pixels in the image that are arranged in the form
of a grid and the third dimension specifies the number of channels for the
image.
A digital image is a multidimensional array and every pixel in a digital image
is represented by a number

31. Let’s say you have an image that you have split into two equal

halves along the x axis. You have stored these two halves of the
original image in the variables x1 and x2 respectively. Which numpy
function would you use to combine these two halves to reconstruct
the original image?
Ans. concatenate((x1,x2),axis=1)

32. Let’s say you have a numpy array called “array_1” and you

initialize “another array called “array_2” with the help of a following
command:
array_2 = array_1.view()
Match the following statements about “array_2” with the correct
Boolean value

Ans. A: array_1 and array_2 contain the same elements (True)

B: The base for array_2 points to the same object as array_1(True)
C: array_2 points to the same object as array_1(False)
D: If we re-assign array_2, then we will end up re-assigning array_1 as
well and change its contents (False)

33. Let’s say you have a numpy array called “array_3” and you

initialize “array_4” with the help of a following command:
array_4 = array_3.copy()

Match the following statements about “array_4” with the correct
Boolean value

A: If we change a single element of array_4, then the corresponding
element in array_3 changes too (False)
B: array_3 and array_4 contain the same elements (True)
C: If we re-assign array_4, then we will end up re-assigning array_3 as
well and change its contents (False)
D: Changing the shape of array_4 will change the shape of array_3 as
well (False)

34. Let’s say you have a 1-D numpy array called “cubes” consisting

of the cubes of the numbers 1,2,3 and so on till 10. What would be
the value of the array :
cubes [ [ [ 4, 5], [ 1, 2] ] ]
ans. [ [ 125, 216] , [ 8, 27] ]

35. Some of the features of Pandas is given below. Which of these

are true?
Ans. A particular column of a pandas dataframe can be referenced by its
column header.

The column header of a Pandas dataframe can be treated in the same way
as the index label of a numpy array

36. Let’s say you imported numpy as np and you have initialized a 1-

D array of integers called “array”. What would np.all (x < 50) return?
Ans. This function would return a true boolean value if all the entries in
your array are less than 50 and false otherwise

37. Let’s say you have a Pandas dataframe called “phone_data”

which contains the data of various phones released in 2018 and
their prices. It has the following three columns:
“manufacturer”, “phone name” and “ price”.
You want only the names of all the phones that are priced more
than 10,000. Which of these commands can be used to print these
values?
Ans. phone_data[phone_data[‘price’] > 10000][‘phone name’]

38. What are the conditions under which broadcasting can take

place between two elements in Numpy?
Ans. Broadcasting works when at least one of the elements is a scalar
A smaller array can be broadcast on a larger array only when the
corresponding dimensions of the two arrays being operated upon are
compatible i.e. when the corresponding dimensions are equal or one of the
two dimensions is 1

39. Match the following statements about broadcasting with the

correct Boolean value:

Ans. A:The array [ [ 1, 2] , [ 3, 4] ] and the array [ 1, 2 ,3 ] are

incompatible with broadcasting(True)
B:The scalar 10 and the scalar 20 are compatible with
broadcasting(True)
C:The array [ [ 1, 2] , [ 3, 4] ] and the scalar 10 are incompatible with
broadcasting(False)
D:The array [ [ 1, 2] , [ 3, 4] ] and the array [ [1], [2] ] are compatible
with broadcasting(True)

40. In the following Python code, typing which Python command will

give the user the CEO of Facebook?
import pandas as pd

companies_ceo = {

Data Essentials
‘Amazon’ :

‘Jeff Bezos’

‘Apple’ : ‘Tim Cook‘,
‘SpaceX’: ‘Elon Musk‘
‘Facebook’: ‘Mark Zuckerberg’
‘Netflix’: ‘Reed Hastings’
}
companies_ceo_series= pd.Series(companies_ceo)

ans. companies_ceo_series[‘Facebook’]
companies_ceo_series[3]

41. In the following Python code, typing what command will create a

DataFrame called “companies_ceo” whose first column has all the
entries of the ‘companies’ list and whose second column has all the
entries of the ‘ceo’ list, with the column names as the names of the
respective variables?
import pandas as pd
companies = {
‘Amazon’
‘Apple’
‘SpaceX’
‘Facebook’
‘Netflix’
}

ceo = {
‘Jeff Bezos’
‘Tim Cook‘,

Data Essentials
‘Elon Musk‘
‘Mark Zuckerberg’
‘Reed Hastings’
}

Ans. companies_ceo_tuple = list (zip(companies, ceo)) companies_ceo =
pd.dataframe(companies_ceo_tuple, columns=[‘companies’, ‘ceo’])

42. What happens when we call the stack () function on a Pandas

DataFrame?
Ans. It will create a new DataFrame such that a single row in the original

DataFrame is stacked into multiple rows in the new DataFrame depending
on the number of columns for each row in the original DataFrame.

43. Which of these correctly match the following libraries in the

Numpy ecosystem with what that library is used for?

Ans. A: Bokeh-Data visualization tool used for large datasets-

B: Statsmodel-Used to perform statistical operations
C: Scikit-learn-Specifically meant for machine learning, data mining,
and data analysis

44. Match the following statements related to the iloc indexer in

Pandas with the correct boolean values.

Ans. A: The iloc indexer is similar to the loc indexer and can be used

to access records located at a particular index in a Pandas DataFrame
(True)
B: The column headers can be passed as input arguments in the form
of a string to the iloc function without any errors (False)
C: When we pass 2:6 as input argument to the iloc function, we get all
details of the records located in the second index all the way up to
the 5th index of the DataFrame (False)

45. Let’s say you have saved a dataset in a pandas DataFrame

called “dataset” which has tons of records and you only want
to access the details of the records in only the 5th, 8th and 14th
index. Which of these Python commands can you use to do
so?

Data Essentials

Ans. dataset.loc[[5,8,14],:], dataset.loc[5,8,14]

46. Let’s say you have a pandas DataFrame called “panda”

which has 8 rows in total and you want to remove the last row
from this DataFrame. Which of these Python commands would
you use to do so?
Ans. panda.drop(panda.index[7])

47. Which of these statements related to the pivot function in

Pandas is true?
Ans. The combination of the row index and the column header must
be unique in order to generate a pivot table

The Pivot function summarizes the details of each column in a
DataFrame

48. Match the following statements related to Pandas

DataFrames with the correct boolean values.

Ans. A: All the data within a particular column in a Pandas DataFrame
must be of the same data type (True)
B: Once a Pandas DataFrame has been created, it is not possible to
add a new column to this DataFrame (False)
C: Data in different columns of a Pandas DataFrame cannot be of
different data types (False)

49. Match the following statements related to the concept of

multiIndex in Pandas with the correct Boolean values

Ans. A: MultiIndex is useful when we have large datasets where using
numeric indexes to refer to each record is unintuitive (True)
B: MultiIndex lets the user effectively store and manipulate higher
dimensional data in a 2-dimensional tabular structure (True)
C: The MultiIndex for a row is some composite key made up of
exactly one column (False)

50. Which of these statements related to the Pandas Series

object are true?
Ans. Pandas Series object is similar to a Python list

Data Essentials
Once we create a Pandas Series object, an index representing the
positions for each of the data points is automatically created for the
list.

51. Let’s say you have a pandas DataFrame called “frame” and

you want to export this DataFrame along with its index as a
CSV file called “data_frame” located in the datasets folder of
our workspace.
Ans. frame.to_csv(‘datasets/data_frame.csv’)

52. Consider the following Python code. What command would you

use to iterate through the “companies_ceo” DataFrame and print the
list of all the CEOs in this DataFrame?
import pandas as pd

companies = {
‘Company’ : [‘Facebook’, ‘Apple’, ‘Amazon’, ‘Netflix’],

‘CEO’ : [‘Mark Zuckerberg’, ‘Jeff Bezos’, ‘Tim Cook’
, ‘,’Reed Hastings’ ],

}

companies_ceo = pd.DataFrame(companies)

ans. for row in companies_ceo.itertuples(): print(row.CEO),
for row in companies_ceo.iterrows(): print(row[1])

53. Which of the following formats does Pandas not support

natively when exporting the contents of a Dataframe?
Ans. JPEG

54. Let’s say you have created a Pandas DataFrame called
    “unsorted” and you want to sort the contents of this
    DataFrame column wise in alphabetical order of the header
    name. Then, which function would you call on the “unsorted”
    DataFrame to do so?
    Ans. unsorted.sort_index(axis=1)
55. Match the following functions that you can call on a Pandas

DataFrame correctly with what they do
Ans. Returns a Boolean array containing true or false values and

returns the value in a cell as true if it does not contain NaN-.notnull()
All the rows which contain a NaN value in any cell of that row are
removed-.dropna()
Every cell in the Dataset which has a NaN value will be replaced with
0-.fillna(0)
Returns a Boolean array containing true or false values and returns
the value in a cell as true if it contains NaN-.isnull()

56. Match the following statements related to the .xs function

in Pandas DataFrame with their correct Boolean values.

Ans. A: By default, the .xs function only takes a look at values in the

first level index(True)
B: The. xs function is used when our Pandas DataFrame makes use of
a MultiIndex(True)
C: The .xs function cannot be used to return a cross section of
columns(False)

57. Let’s say you have imported Python as pd and have

instantiated two DataFrames called “frame_1” and “frame_2”
with the exact same schema. What command will you use to
combine these two DataFrames into a single DataFrame and

Data Essentials

make sure that the combined DataFrame has its own unique
index?
Ans. pd.concat( [frame_2, frame_1], ignore_index = True )
pd.concat( [frame_1, frame_2], ignore_index = True )

58. The ‘how’ argument in the Pandas merge function allows us

to specify what kind of join operation we want to perform on
the given Pandas DataFrames. What are the valid values that
we can give for this argument?
Ans. Left,right,inner,outer

59. Some statements related to working with SQL Databases in

Python are given below. Match them with their correct
Boolean values.

Ans. A: The sqlite3 library in Python allows us to create Databases on
our local file system(True)
B: Once we have created a table, we can use sqlite3’s .execute()
function to recreate the same table with the same table name so that
we have duplicates of a table(False)
C: All the changes that we make to an SQL database on a Jupyter
notebook by connecting with it, will be committed to the database
only after we execute sqlite3’s .commit() function(True)

60. Which statement is true about the Kappa architecture?

Ans. The Kappa architecture uses stream processing to manage data
flows through a single path

61. Which are the main reasons for using batch processing?
    Ans. To run complex algorithms on large datasets which require
    access to the entire batch.
    To join tables in relational databases
62. Which statement is true about the Lambda architecture? Data Essentials

Ans. Data that enters the system is dispatched to two layers in the
Lambda architecture: the batch layer and the speed layer.

The Lambda architecture provides fault-tolerance against possible
hardware failures and human errors.

63. Place the layers of big data analytics architecture in the

correct order from the bottom to the top.
Ans. Data monitoring
Data security
Data storage
Data processing
Data query
Data visualization

64. What are some ways in which big data processing can be

performed?
Ans. Batch and stream processing

65. What are the parameters of data ingestion?
    Ans. Data format, Data size, Data frequency, Data velocity
66. Which is correct about stream processing?

Ans. Stream processing provides analytical insights before the data
storage stage

67. Which statement about data storage systems is correct?

Ans. The Hadoop distributed file system (HDFS) is the primary data
storage system used by Hadoop applications

68. Which are the main components of the big data

architecture?

Data Essentials

Ans. Big data analytics, Big data security, The data model

69. What are the biggest challenges associated with traditional

data analytics?
Ans. Scalability, consistency, reliability, efficiency, and maintainability

70. What are some advantages that Spark provides to modern

healthcare providers?
Ans. Behind the scenes distributed execution
Convenient workflow fulfillment
A user-friendly API

71. What are some components of Apache Spark?

Ans. Spark SQL
GraphX

72. Which statements are true about resilient distributed

datasets (RDDs) and directed acyclic graphs (DAGs)?
Ans. Compared to MapReduce that creates a graph in two stages,
Apache Spark can create DAGs that contain many stages

RDD is an immutable (read-only), fundamental collection of elements
or items that can be operated on many devices at the same time
(parallel processing)

73. As Spark usage grew at Uber, users encountered an

increasing number of issues. What were some of those
issues/challenges?
Ans. Multiple Spark versions
Multiple compute clusters

74. What are some examples of metrics that Alibaba measures

by utilizing Spark?

Ans. Connected components
Degree distribution

75. What are some predominant industries that use Spark

today?
Ans. Finance industry
Media and entertainment industry

76. What are the three API types that are compatible with

Spark?
Ans. RDD, DataFrame, DataSet

78. What are some of the most important best practices when

it comes to using Apache Spark?
Ans. Joining a large and a medium size RDD
Proper tuning
Using the right level of parallelism

79. Which statement is correct about how Spark and Hadoop

are different?
Ans. The Hadoop MapReduce model provides a batch engine, hence

it is dependent on different engines for other requirements, whereas
Spark performs batch, interactive, machine learning and streaming all
in the same cluster.

80. Which of the following is a characteristic of a data silo?

Ans. Data is stored in isolation and cannot be combined with other
sources

Data is not easily accessible using common tools
Data may be in a raw, native format and not useful unless processed

81. Which of the following are valid data types that can be stored

in a data lake?
Ans. Unstructured data
Semi-structured data
Structured data

82. Which of the following is not a characteristic of a data lake?

Ans. Data is not searchable easily

83. Which of the following are challenges involved in designing

and building data lakes?
Ans. Data lakes need to work with different data types and sparse and
incomplete data

Data lakes need to maintain data security and compliance
Data lakes need to be able to support a huge volume of data

84. Which of the following are valid differences between a

traditional relational database and a data warehouse?
Ans. A data warehouse is optimized for read access, a database is
optimized for read as well as write access.

A database supports ACID properties and a data warehouse does not

85. Which of the following statements about data lakes and data

warehouses are true?
Ans. Data lakes need to maintain security and ensure compliance of the
data stored within it

Data warehouses hold fairly structured data optimized for analysis
Data lakes promote shared data stewardship

86. Which of the following is not an example of a data stream?

Ans. Census data stored in a database

87. Which of the following is not a valid service used to ingest

data into the AWS cloud?
Ans. Amazon Athena

88. Which of the following correctly defines AWS Glue?

Ans. A single catalog which indexes data from multiple sources to make
it searchable

89. Which of the following AWS services can be used to visualize

data stored in a data lake on AWS?
Ans. Amazon QuickSight

90. Select the benefits of a distributed system

Ans. fault tolerance
Concurrency
Scalability

91. Arrange the following ETL processing steps in order from the

top.
Ans. ingest data from source
message brokering
streaming data engine
long-term storage and analytics

92. Select the characteristics of a NoSQL data store.

Ans. dynamic schema
cluster-friendly
horizontal scaling

93. Match the data management category with its description.

Ans. standardized data, static information-Reference Data Management
organizational data-Master Data Management
dashboards and real-time results-Visualization and Analytics
data warehousing, transformation, extraction-ETL

94. Match the ETL process with its description.

Ans. importing data for computation-Load
selecting raw data-Extract
format and representation shift-Transform

95. Where does the library of job components reside in the

Talend Open Studio UI?
Ans. Pallete

96. What high level model is used to get a project overview for
    ETL jobs in Talend Open Studio?
    Ans. Business Model
97. Put the following AI hierarchy steps in pyramid order from the

bottom up.
Ans. ETL
Data Exploration
Aggregation
Machine Learning
Deep Learning

98. Reducing the number of fields in the output is an example of

what type of partitioning?

Ans. column-based

99. Match the data storage model approach with its descriptions.

Ans. Star Schema-Fact Tables, Dimension Tables
Normalization-Less Redundancy, Standardized

100. Select the features common to interactive reporting tools.
     Ans. Filtering, drilling down, sorting
101. Match the data backup methods with their descriptions.

Ans. Gets a backup for all data within the hard drive-Full backup
Gets a backup of data for the past n years-Differential backup
Gets a backup of the data generated or revised since the last full backupDifferential backup
Gets a backup of the data generated or revised since the last backup,
regardless of the type of the last backup-incremental backup

102. Match the concepts with their descriptions.

Ans. Raw and unstructured facts, numbers, or figures which convey a
message-Data

The ability to ask questions and learn new things-Information
Contextualized, organized, and vetted data that convey some sort of
trend or pattern-Information
The ability to use your knowledge and experience to make good
decisions and judgements-wisdom
The application of information which is measured by the ability to “do
things”-knowledge

103. Ravi wants to create a data visualization to show which parts

of his company website are receiving the most clicks and are
being most viewed by his viewers. Which data visualization will

provide Dan with a visual that is easy to assimilate and make
decisions from?
Ans. Heat Map

104. Match each of the SQL codes with the functions that they
     perform.
     Ans. Creates groups to summarize data-GROUP BY
     Lists the columns you want to retrieve-SELECT
     Applies filtering logic to your groups-HAVING
     Applies filtering logic to limit records in your results-WHERE
     Describes how you want your data sorted-ORDER BY
     Name of the table to pull the data from-FROM
105. A university professor collects information about the

classification of her students as freshmen, sophomores, juniors, or
seniors. The data is then displayed in a bar chart. What type of
data is the university professor collecting?
Ans. Qualitative data

106. Which characteristics do all data migration projects have in

common?
Ans. They all require identifying source and target systems.
They all begin with data ingestions and cleansing of the data prior to
integration.
They all require performing proper ETL mapping to ensure consistency
and compatibility.

107. Alex is in the process of creating a report that displays the

results of a survey. Which data type best describes the data that
Alex is dealing with?
Ans. Observational

108. ABC Company wants to migrate their CRM data from their
     current legacy systems into newly purchased web-based CRM
     software. Place the data migration steps that they should perform
     in the correct order.
     Ans. Planning
     Analyzing the data
     Design
     Implementation
     Final migration
     Testing
109. Which is not a type of data that would be encountered in an

enterprise?
Ans. Logical

110. What is the primary reason for data integration across

domains?
Ans. Provide a unified single version of the data

111. In your multi-domain enterprise where the primary function

is of a stock market broker and where you need real-time data
synchronization, what will be the required style of architecture
needed for the data management program?
Ans. Hybrid style

112. Which is not a function of entity resolution?

Ans. Data Propagation

Suppose you have a company of 50 employees, and you are
writing code for a very specific type of program. There are five
vendors that provide you the graphical support and your target

client are very small businesses. Which statement will be true in
the domain of data management?
Ans. You do not need a data management program at all

114. Which is not a goal of metadata management?

Ans. Data reference

115. Which correctly describes the difference between static and

dynamic data?
Ans. Static data does not require updating whereas dynamic data
requires regular updating

116. What will be the best approach of data management for a

multi-faceted enterprise with multiple domains?
Ans. A combination of top-down and middle out approaches

117. In your enterprise where you are planning to develop a

perfectly aligned system across all the domains, which function
will you deem as not necessary for building a truly aligned
system?
Ans. Data Quality Program

118. What is the proper order for the levels of management and

control from a Measurement of Maturity point of view?
Ans. Unstructured, Structured, Managed, Optimized

119. Which can be considered an advantage of IT systems in

preventing security threats?
Ans. Access control is limited to a particular system

120. Which is NOT true about the entity resolution process?

Ans. Application of business and data quality rules is not a step in entity
resolution

121. What is the integral meaning of data harmonization?

Ans. Data harmonization means obtaining a single version of the truth

122. Which is NOT a primal rule for data validation?

Ans. Governance practices

123. In building your data governance practice, which will not be

an objective for the governance practice?
Ans. Dividing the business

124. Which is not the kind of job that is to be included in the role of

a data steward?
Ans. Deciding which information is to be provided to which individual

125. Which are the two factors critical to an organization when

considering the regulation of data privacy?
Ans. Storage Networking Industry Association & General Data Protection
Regulation

126. In your multi-domain enterprise where there are multiple

vendors and multiple resources, which will be a key deciding factor
in how you will manage the CRUD?
Ans. Enterprise resource planning

127. Which can be a major problem in companies that have a “Bring

your Own Device” policy?
Ans. Leakage of information when the device is used in a public network

128. When implementing your data governance practice in your

organization, which is the one factor that will NOT play a major role
when considering the implementation?
Ans. Data quality

129. Which is a performance measurement level?

Ans. Strategic measurement

130. Which is NOT a data quality aimed project initiative?

Ans. Data integration

131. Which function is a must for data compliance but not required

at all for data management and data governance?
Ans. Inter-relations

132. Which is an essential factor to ensure good data quality?

Ans. Fix data quality issues

133. What are the advantages of a good data compliance strategy?

Ans. Proactive environment, organizational growth, and customer
relationships

134. What is meant by reference data?

Ans. Data that is used for classification of other data

135. In your data driven enterprise, how will you ensure that good

quality data is being maintained and reconciled across systems?
Ans. Ensure source to target consistency

136. Which is a major solution to address the data governance and

compliance issues?
Ans. Knowing the data

137. Which is NOT a continuous improvement method in data

governance?
Ans. Overlook achievable governance maturity milestones

138. Which is NOT an advantage of data lakehouse?

Ans. Provides an on-premises data warehouse solution

139. Identify essential table types that we can use to implement a

Star schema.
Ans. Fact table, dimension table

140. Which statements about cloud-based data warehouse are true?

Ans. Cloud-based Data warehouses are scalable
Cloud-based Data warehouses are elastic

141. Identify the essential levels of management that require

strategic reports.
Ans. Middle management level
Strategic

142. Match the data modelling strategies with their features.

Ans. A: Ensures the dependencies are properly enforced-

Normalization
B: Applies formal rules to enforce dependencies-Normalization
C: Splits tables-Normalization
D: Used on previously normalized databases to increase performanceDenormalization
E: Adds redundant data-Denormalization
F: Combines tables-Denormalization

143. Choose the characteristics of weighted reports.

Ans. With weighted reports we get a meaningful subtotal and total
Weighted reports multiply all the facts by weight before aggregating

144. Which processes involved in a data warehouse project are

important?
Ans. Data cleansing,ETL

145. Which are essential tasks that we can execute to facilitate

business intelligence?

Data Essentials

Ans. Load
Extract

146. Which of the following local and global warehouse

statements are true?
Ans. Local data warehouse cannot be accessed globally
We can provision a single global repository for a particular domain

147. Select data modelling strategies that we can adopt to

create an ER model.
Ans. Normalization,Denormalization

148. Which of the following OLAP statements are true?
     Ans. OLAP provides real-time analytical capability
     OLAP is a part of the overall Data warehouse implementation
149. Identify the terminologies that we generally use in data

warehousing.
Ans. ETL, Dimension model

150. Identify essential features of Strategic Information.
     Ans. Preserves data integrity, Time-variant
151. Identify some of the essential features which

differentiates a data warehouse from OLTP.
Ans. Data warehouse provides predictive analytical capabilities
Data warehouse stores historical data

152. Identify the essential differences between RDBMS and

data lakes?
Ans. RDBMS databases are transaction while data lakes are not
transactional

Data Essentials

RDBMS databases defines fixed schema while data lake follows no
schema design

153. Which statements about Snowflake schemas are true?

Ans. A Snowflake schema is an extension of the Star schema
Application binary interface allows us to contextualizes contracts

154. Identify the essential components of Azure data lake.

Ans. Data factory, SQL server

155. Match the data warehousing solutions with their associated

benefits.

Ans. A: Preferred in banking or government domains (On-premise
data wareshouse)
B: Offers absolute control over security (On-premise data
wareshouse)
C: Provides scalability (On-cloud data warehouse)
D: Cost effective (On-cloud data warehouse)
E: Offers better speed and connectivity (On-cloud data warehouse)

156. Specify some of the outcomes of a data warehouse

realization.
Ans. Intuitive dashboards
Predictive analytical reports

157. Specify some of the essential logical components of a data

warehouse
Ans. Attributes,Entities

158. Which of the following components are provided by
     Talend to design ETL jobs?
     Ans. tMap, tFileInput
159. Which of the following statements correctly defines the

characteristics of the Kimball model?

Ans. In the Kimball model the analytical systems can access the data
directly

In the Kimball model the analytical systems can access the data
directly

160. Identify essential tasks involved in an ETL process.

Ans. Extracting data from diversified sources
Transforming extracted data

161. Which of the following dimensional components

differentiates a Dimensional model from an ER model?
Ans. Dimension and fact table.

162. What are some of the essential tasks that we can execute
     using Talend?
     Ans. ETL job designing, Business modelling
163. What are some of the integrated components of a data

warehouse?
Ans. Storage, Data Staging

164. What are some of the important tasks that we need to
     perform to implement a Physical model for a given Logical
     model?
     Ans. Create Foreign keys to establish the relationships among objects
     Create tables to represent the entities
165. Select prominent ETL tools that we can use with a data

warehouse implementation.
Ans. PowerCenter Informatica,Talend

166. You have an on-premises data warehouse already

installed in your organization. In the period following the

Data Essentials

COVID pandemic, your business started to grow exponentially,
and you were tired of adding more nodes to the physical
storage of the data warehouse. You decide to modernize your
data warehouse and make it cloud-based. What major
advantage will you achieve by modernizing your data
warehouse?
Ans. Speed up time to analytics

167. You plan to implement a modern data warehouse solution

into your enterprise. You have understood the proper data
management and governance issues. You have set up all your
domains and data ingestion methods. Now you plan to make a
central repository of all your files. What should be the next
step for the implementation of the data warehouse solution?
Ans. Selection of the nature of the data

168. You have a very well-run data management program in

your organization, which is very secure. You use analytics for
making big data driven decisions. In recent months, you realize
that whatever decisions you are making based on the analytics
are proving to be wrong and harmful for the organization.
After consulting with the data analysts and data stewards you
conclude that it is due to poor data quality. What should be
the next step of action?
Ans. Install a firewall

169. Other than gaining real-time insights of the data, what is

another major advantage of streaming analytics?
Ans. Real-time dashboards

170. BigQuery is a cloud-native warehouse that is also a fully

managed data warehouse. What is the major advantage of
BigQuery over Amazon Redshift that may be a deciding factor
for the selection of a data warehouse?
Ans. Access control allows improved data sharing

171. Your organization has an effective sales team that is

backed up by analytics that help accelerate the process of
sales from the initial contact. One of the primary reasons for
its effectiveness is a data input tool that hastens the process of
data entry by providing preset suggestions. What are these
suggestions commonly known as in data science terminology?
Ans. Reference data

172. You have incorporated the usage of Amazon Redshift in

your organization, and you don’t want your data to be
corrupted by processing. Therefore, you want the data to be
stored in raw format before the processing is done, which is a
service offered by Amazon Redshift. What is the key benefit of
storing data in raw format?
Ans. Minimal loss of data

173. What is not a component of an on-premises data

warehouse?
Ans. Processing space

174. You have an automobile company that helps sort out

vehicles and make monthly sales versus expenditure reports.
What is the best way to handle the data for centrally storing it?
Ans. Batch processing

175. In a candlestick chart, you see the share price of your

company falling. You have implemented a streaming analytical
tool that helps in analyzing and dashboarding the data as it is
produced. You realize that the candlesticks pattern has
consolidated and is not responding well to the influx of data.
What is the source of this problem?
Ans. Server downtime

176. In your enterprise, customer information needs to be

readily available to indicate whether the information given by

customers is valid or not, and to see the potency of a positive
deal. Which factors would you consider a priority when
selecting the appropriate data pipeline tool?
Ans. Batch-wise vs. real-time ingestion and analytics

177. What are the major advantages of a cloud warehouse

solution over an on-premises data warehouse solution?
Ans. Less worry about storage
Low cost

178. What are the two different data pipeline tools that address specific job roles?
     Ans. Data engineers and analysts
179. Place the steps for a typical Azure Databricks warehouse in the

correct order.

1. Ans. Ingest
2. Store
3. Prep and train
4. Model and serve
5. The reason why Azure Databricks is so easy to use is

because it is universal and is integrated with Microsoft’s server
for better parsing of information. Which platform has the same
source of origin as Databricks, which gives it an analytical
advantage over other platforms?
Ans. Apache spark

181. What are the major disadvantages of Snowflake that
     might be troublesome for a few companies that seek data
     categorization?
     Ans. Fewer options with geospatial space
     No option for un-structured data

182. While setting up an integrated data pipeline for your

enterprise to facilitate data ingestion in the warehouse, what
should you place more emphasis on from a business
perspective?
Ans. Analytics and business intelligence

183. Suppose you have a full-blown data management program

with a well-running data warehouse and an optimum data
pipeline tool that facilitates data transformation and
transmission. While measuring the maturity of the data
pipeline tool, what will be the sole factor that will determine
the efficiency of the data pipeline tool?
Ans. Reliability and scalability

184. What is the one difference that separates the model of

the Snowflake data warehouse from all the other data
warehouse solutions?
Ans. Hybrid model

185. What is not a design component of a data pipeline?

Ans. Data integration

186. Select the main dependency that has to be installed for

Talend to be installed.
Ans. Java

187. Select the supported OSs by Talend Open Studio.

Ans. MacOS
Windows 64

188. Select the main parts of the default UI of Talend Open Studio.

Ans. Repository, Palette

189. When installing MySQL relational Database to be used with

Talend, select the configuration to be performed once the
installation of the components is complete.
Ans. MySQL root password
MySQL server port

190. Select the folder that contains all the project information for a

job that is exported from Talend studio.
Ans. Process

191. Rank the steps required to for any job in Talend studio.

Ans. Create job in the repository
Configure the components properties
Add components from palette to the design space
Run the job

192. Select the correct description of Talend Metadata Bridge

Ans. Synchronize metadata across data pipelines

Match each description with the variable in Talend studio.

Ans. A: studio provisions through components used in jobs

integration (Studio global variables)
B: Ad-hoc variables that can be configured in jobs (User defined
global variables)
C: execute jobs with parameters for different environments (Job
contexts variables)

194. Select the correct differences between XML attributes and
     elements.
     Ans. Elements can contain tree structure, Elements can have multiple
     values

195. Select the component used to generate an XML file from a CSV

file in Talend studio.
Ans. tFileOutputXML

196. Select the exit code value the signifies the successful

completion of a job in Talend studio.
Ans. 0

197. Select the tMap Component description in Talend studio.
     Ans. congregate input data to output data
198. Select the option to be enabled to allow the specification of 2

schemas for an XML input file in Talend studio.
Ans. Enable XPath in column “Schema XPath loop” but lose the order

199. In order to generate a complex XML file where data is specified

using attributes of elements and elements trees in Talend studio,
which component allows such.
Ans. tAdvancedFileOutputXML

200. Select the component used to perform lookup data in Talend

studio.
Ans. tJoin

201. Select the component access a MySQL database in Talend

studio.
Ans. tMysqlInput

202. Select the tool that allows specifying the relation of multiple

tables as data sources when reading data from a database as input in
Talend studio.
Ans. SQL Builder

203. Match the attribute value with its attribute that will only Add

new records or modify existing ones without modifying the table

structure or other records already exist in the table when writing
data to a database table in Talend studio. Two options are invalid.
Ans. Action on data-Insert or update
Action on table-Default

204. Select the component that allows updating data in a database in

Talend studio.
Ans. tMySQLRow

205. Select the components and concepts to facilitates accepting as

input multiple databases in Talend studio.
Ans. tMap, LookUp

206. Select the component used to combine multiple database
     records to a single records in Talend studio.
     Ans. tDenormalize
207. Which of these statements accurately describes the Unique

Match Join match model in the Map Editor?
Ans. Set as default when configuring an explicit Join
Last match is considered and passed to the output

208. You are building an expression in Map Editor for a column in

which you want to pad the row1.CustomerID string with leading
zeroes up to maximum length of 6 characters. Which code can you
use to accomplish this for you?
Ans. String.format(“$06d”,row1.CustomerID)

209. You have Map Editor open for a tMap object for which you are

mapping databases objects. You click the Join Model for a table Join
property. Which options appear in the Options dialog that appears?
Ans. Inner Join, Left Outer Join

210. You are building a filter expression in Map Editor for a column

in which you want to filter the product name, prd.name to equal

Data Essentials

“Turbo Widgets”, and you want the transaction quantity, tx.qty to be
greater than 100. Which code can you use to accomplish this for
you?
Ans. prd.name.equals(“Turbo Widgets”)&&tx.qty>100

211. Which common FTP operations are supported by Talend Open

Studio components available in the Palette?
Ans. Delete
File Exist
Put

212. On the Component tab displayed for the tSortRow component,

when you click to add criteria to the Criteria table, Talend
automatically populates the column values with defaults. In the “sort
num or alpha?” column Talend has chosen num by default for
customer_id as displayed. Which other values are available for the
“sort num or alpha?” column when you click to open the dropdown
list for that column?
Ans. Alpha,date

213. You are using a tExtractDelimitedFields component to split the
     Address2 field in the delimited file as displayed. What must you
     specify as the Field separator property for the
     tExtractDelimitedFields component to properly split the Address2
     field?
     ID;First_Name;Last_Name;Address1;Address2;Country
     1;Claudia;Sand;10000 Main Dr NW;New York, NY;USA
     2;Max;Bigot;60000 My St;Nashua, NH;USA
     3;Rick;Tailleur;200000 Younge St;Toronto, ON;Canada
     4;Noémie;Miller;500000 St. Catherines St Ouest;Montreal, QC;Canada
     5;Catherine;Reilly;100000 Main St SW;Boston, MA;USA
     Ans. “,” (a comma)

214. When configuring the properties for a tReplace component,

you can optionally click the Advanced mode checkbox. Doing so
allows you to specify what type of expression as the Pattern to
search for?
Ans. Regular Expression

215. When configuring the properties for a tAggregateRow
     component. You are going to Group by the customer_id field in
     order to aggregate the sales on a customer_id basis, so that in the
     resulting output file you will have one row for each customer_id
     with aggregated sales figures. Which Function value must you
     choose when configuring the Operations table for this
     tAggregateRow component?
     Ans. Sum
216. You are using a tNormalize component to normalize the
     category field in the delimited file as displayed. What must you
     specify as the Item separator property for the tNormalize
     component to properly normalize the category field?
     product_id,product_name,category,unit_price
     1,Regular Widget,Normally Aspirated;Low Price;Highly Reliable,125
     2,Super Widget,Super;Medium Price;Very Reliable,250
     3,Turbo Widget,Turbo;Medium Price;Very Reliable,275
     4,S/T Widget,Super;Turbo;Premium Price;Reliable,425
     5,Hybrid Widget,Hybrid;Normally Aspirated;Premium Price;Reliable,425
     Ans. “;” (a semi-colon)