HIGH-EFFICIENCY DA0-001 EXAM PRACTICE BOOTCAMP MATERIALS ARE WISE FOR YOU - ACTUALTESTPDF

High-efficiency DA0-001 Exam Practice Bootcamp Materials are wise for you - ActualtestPDF

High-efficiency DA0-001 Exam Practice Bootcamp Materials are wise for you - ActualtestPDF

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CompTIA Data+ Certification Exam Sample Questions (Q109-Q114):

NEW QUESTION # 109
Which of the following is used for calculations and pivot tables?

  • A. SAS
  • B. IBM SPSS
  • C. Domo
  • D. Microsoft Excel

Answer: D

Explanation:
This is because Microsoft Excel is a type of software application that allows users to create, edit, and analyze data in spreadsheets, which are composed of rows and columns of cells that can store various types of data, such as numbers, text, or formulas. Microsoft Excel can be used for calculations and pivot tables, which are two common features or functions in data analysis. Calculations are mathematical operations or expressions that can be performed on the data in the cells, such as addition, subtraction, multiplication, division, average, sum, etc. Pivot tables are interactive tables that can summarize and display the data in different ways, such as by grouping, filtering, sorting, or aggregating the data based on various criteria or categories. The other software applications are not used for calculations and pivot tables. Here is why:
IBM SPSS is a type of software application that allows users to perform statistical analysis and modeling on data sets, such as regression, correlation, ANOVA, etc. IBM SPSS does not use spreadsheets or cells to store or manipulate data, but rather uses data views or variable views to display the data in rows and columns. IBM SPSS does not have pivot tables as a feature or function, but rather has output views or charts to display the results of the analysis.
SAS is a type of software application that allows users to perform data management and analysis using a programming language that consists of statements and commands. SAS does not use spreadsheets or cells to store or manipulate data, but rather uses data sets or tables that are stored in libraries or folders. SAS does not have pivot tables as a feature or function, but rather has procedures or macros that can produce summary tables or reports based on the data.
Domo is a type of software application that allows users to create and share dashboards and visualizations that display data from various sources and systems, such as databases, cloud services, or web applications. Domo does not use spreadsheets or cells to store or manipulate data, but rather uses connectors or APIs to access and integrate the data from different sources. Domo does not have pivot tables as a feature or function, but rather has cards or widgets that can show different aspects or metrics of the data.


NEW QUESTION # 110
Which of the following describes the method of sampling in which elements of data are selected randomly from each of the small subgroups within a population?

  • A. Stratified
  • B. Simple random
  • C. Cluster
  • D. Systematic

Answer: A

Explanation:
Explanation
This is because stratified is a type of sampling in which elements of data are selected randomly from each of the small subgroups within a population, such as age groups, gender groups, or income groups. Stratified sampling can be used to ensure that the sample is representative and proportional of the population, as well as reduce the sampling error or bias. For example, stratified sampling can be used to select a sample of voters from different political parties based on their proportion in the population. The other types of sampling are not the types of sampling in which elements of data are selected randomly from each of the small subgroups within a population. Here is why:
Simple random is a type of sampling in which elements of data are selected randomly from the entire population, without dividing it into any subgroups. Simple random sampling can be used to ensure that every element in the population has an equal chance of being selected, as well as avoid any systematic error or bias. For example, simple random sampling can be used to select a sample of students from a school by using a lottery or a computer-generated number.
Cluster is a type of sampling in which elements of data are selected randomly from a few large subgroups within a population, such as regions, districts, or schools. Cluster sampling can be used to reduce the cost and complexity of sampling, as well as increase the feasibility and convenience of sampling. For example, cluster sampling can be used to select a sample of households from a few neighborhoods by using a map or a list.
Systematic is a type of sampling in which elements of data are selected at regular intervals from an ordered list or sequence within a population, such as every nth element or every kth element. Systematic sampling can be used to simplify and speed up the sampling process, as well as ensure that the sample covers the entire range or scope of the population. For example, systematic sampling can be used to select a sample of books from a library by using an alphabetical order or a numerical order.


NEW QUESTION # 111
A table in a hospital database has a column for patient height in inches and a column for patient height in centimeters. This is an example of:

  • A. invalid data
  • B. duplicate data.
  • C. dependent data.
  • D. redundant data

Answer: D

Explanation:
This is because redundant data is a type of data that is unnecessary or irrelevant for the analysis or purpose, which can affect the efficiency and performance of the analysis or process. Redundant data can be caused by having multiple data fields that store the same or similar information, such as patient height in inches and patient height in centimeters in this case. Redundant data can be eliminated or reduced by using data cleansing techniques, such as removing or merging the redundant data fields. The other types of data are not examples of data that is unnecessary or irrelevant for the analysis or purpose. Here is what they mean in terms of data quality:
Dependent data is a type of data that relies on or is influenced by another data field or value, such as a formula or a calculation that uses other data fields or values as inputs or outputs. Dependent data can be useful or important for the analysis or purpose, as it can provide additional information or insights based on the existing data.
Duplicate data is a type of data that is repeated or copied in a data set, which can affect the quality and validity of the analysis or process. Duplicate data can be caused by having multiple records or rows that have the same or similar values for one or more data fields or columns, such as customer ID or order ID. Duplicate data can be eliminated or reduced by using data cleansing techniques, such as removing or filtering out the duplicate records or rows.
Invalid data is a type of data that is incorrect or inaccurate in a data set, which can affect the validity and reliability of the analysis or process. Invalid data can be caused by having values that do not match the expected format, type, range, or rule for a data field or column, such as an email address that does not have an @ symbol or a date that does not follow the YYYY-MM-DD format. Invalid data can be eliminated or reduced by using data cleansing techniques, such as validating or correcting the invalid values.


NEW QUESTION # 112
Which of the following is a difference between a primary key and a unique key?

  • A. A primary key cannot be a date variable, whereas a unique key can be.
  • B. A unique key cannot take null values, whereas a primary key can take null values.
  • C. There can be only one primary key in a data set, whereas there can be multiple unique keys.
  • D. A primary key can take a value more than once, whereas a unique key cannot take a value more than once.

Answer: C

Explanation:
The correct answer is B. There can be only one primary key in a data set, whereas there can be multiple unique keys.
A primary key is a column or a set of columns that uniquely identifies each row in a table. A table can have only one primary key, which also enforces the NOT NULL constraint on the column(s) involved. A primary key can also be referenced by a foreign key of another table to establish a relationship between the tables12 A unique key is a column or a set of columns that also uniquely identifies each row in a table, but it is not the primary key. A table can have more than one unique key, which also allows one NULL value for the column (s) involved. A unique key can also be referenced by a foreign key of another table to establish a relationship between the tables12 Some of the differences between a primary key and a unique key are:
* A primary key creates a clustered index on the column(s), whereas a unique key creates a non-clustered index on the column(s)3
* A primary key does not allow any NULL values, whereas a unique key allows one NULL value for the column(s)123
* A primary key can be a unique key, but a unique key cannot be a primary key12


NEW QUESTION # 113
Daniel is using the structured Query language to work with data stored in relational database.
He would like to add several new rows to a database table.
What command should he use?

  • A. UPDATE.
  • B. INSERT.
  • C. ALTER.
  • D. SELECT.

Answer: B

Explanation:
INSERT
The INSERT command is used to add new records to a database table.
The SELECT command is used to retrieve information from a database. It's the most commonly used command in SQL because it is used to pose queries to the database and retrieve the data that you're interested in working with.
The UPDATE command is used to modify rows in the database.
The CREATE command is used to create a new table within your database or a new database on your server.


NEW QUESTION # 114
......

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