Module 4

Question 1

It is the practice of collecting, keeping and using data securely, efficiently and cost-effectively.

Answer 1

Data management

Question 2

Data is an ?

Answer 2

asset

Question 3

It is crucial for an organization’s success

Answer 3

efficient data management

Question 4

Relational databases, tables (MySQL)

Answer 4

Structured data

Question 5

Emails, videos, social media content (NoSQL databases)

Answer 5

Unstructured data

Question 6

Two types of data

Answer 6

Structured and unstructured data.

Question 7

Needs specialized tools like text mining, sentiment analysis, and machine learning algorithms

Answer 7

unstructured data.

Question 8

Ideal for transactional systems like customer records or sales
databases.

Answer 8

Structured data

Question 9

Ways of data storage and retrieval/databases and file system

Answer 9

Database Management Systems (MySQL, PostgreSQL, MongoDB)

Cloud Storage (AWS S3, Google Cloud Storage)

Query Languages for Data Retrieval (SQL for DBMS, MongoDB queries for NoSQL)

Question 10

Techniques for faster data retrieval

Answer 10

Indexing, caching and optimization

Question 11

The entire data lifecycle (CSPDA)

Answer 11

collection, storage, processing, dissemination, archiving

Question 12

This enhances database performance
by reducing the number of disk accesses
needed to process a query.

Answer 12

Indexing

Question 13

It is a data
structure that allows quick data retrieval by
creating indexes from specific database
fields.

Answer 13

Indexing

Question 14

They act as pointers to the data,
similar to a book’s index, making queries
faster and more efficient by providing a
quick lookup method for the requested
information.

Answer 14

Indexes

Question 15

It is the process of temporarily
storing copies of files or data in a cache for
faster access.

Answer 15

Caching

Question 16

These saved all the data that was
accessed for the first time by a user when
visiting a website or opening an application,
allowing quicker loading during subsequent
visits by retrieving the stored data instead
of downloading it again.

Answer 16

Caching

Question 17

It is a fundamental process in the
realm of information management
that focuses on improving data sets
to maximize their efficiency, utility,
and accuracy.

Answer 17

Optimization

Question 18

Refers to how well data meets the needs for its intended use.

Answer 18

Data Quality

Question 19

o Ensures data remains complete, accurate, and reliable over its lifecycle.
o Protects data from unauthorized access or corruption

Answer 19

Data Integrity

Question 20

Key Dimensions of data quality

Answer 20

Accuracy, completeness, consistency, timeliness and validity

Question 21

Data must be correct and free from errors

Answer 21

Accuracy

Question 22

All required data should be present (no missing fields).

Answer 22

Completeness

Question 23

Data should be uniform across systems and sources.C

Answer 23

Consistency

Question 24

Data must be up-to-date and available when needed

Answer 24

Timeliness

Question 25

Data should conform to expected formats and values

Answer 25

Validity

Question 26

Causes of poor data quality and integrity

Answer 26

Human Error System Integration Issues Outdated data

Question 27

: Data entry mistakes are common

Answer 27

Human eror

Question 28

Merging data from different sources can introduce inconsistencies.

Answer 28

System Integration Issues

Question 29

Without regular updates, data becomes irrelevant or inaccurate.

Answer 29

Outdated data

Question 30

Removing duplicates, correcting errors, and filling missing data.

Answer 30

Data Cleaning

Question 31

A process in data cleaning that applies rules to check the format, range, and consistency of data at the time of entry.

Answer 31

Validation

Question 32

A process in data cleaning that implements policies and assigning roles (e.g., data stewards) to oversee data quality.

Answer 32

Governance

Question 33

Data Integrity Methods

Answer 33

Encryption Audit Trails Referential Integrity

Question 34

: Ensures data security during storage and transmission.

Answer 34

Encryption

Question 35

: Track who accessed or changed data.

Answer 35

Audit Trails

Question 36

Ensuring relationships between tables in a database remain consistent.

Answer 36

Referential Integrity

Question 37

Republic Act 10173

Answer 37

Data Privacy Act of 2012

Question 38

Data Privacy Act of 2012

Answer 38

Republic Act 10173

Question 39

“to protect the fundamental human right of privacy, of communication while ensuring free flow of information to promote innovation and growth”

Answer 39

Republic Act 10173 or Data Privacy Act of 2012

Question 40

refers to extremely large datasets that are too complex and voluminous for traditional data-processing tools to handle.

Answer 40

Big Data

Question 41

5 V's of Big Data

Answer 41

Volume Velocity Variety Veracity Value

Question 42

The amount of data (e.g., terabytes, petabytes)

Answer 42

Volume

Question 43

The speed at which data is generated and processed (e.g., real-time data from social media).

Answer 43

Velocity

Question 44

: Different types of data (e.g., text, images, video, structured and unstructured data).

Answer 44

Variety

Question 45

Data accuracy and trustworthiness

Answer 45

Veracity

Question 46

The potential insights that can be gained from analyzing Big Data.

Answer 46

Value

Question 47

The process of examining large datasets (Big Data) to uncover patterns, trends, and insights that can support decision-making.

Answer 47

Data Analytics

Question 48

Types of Data Analytics:

Answer 48

Descriptive Analsys (What happened?) Diagnostic Analysis (Why did it happen?) Predictive Analysis (What will happen?) Prescriptive Analysis (What should be done?)

Question 49

Big Data Tools and Technologies

Answer 49

For Distributed Computing: Hadoop Spark For Data Storage NoSQL Databases like MongoDB, or Cassandra For Data Visualization Tableau, PowerBI, D3.js

Question 50

: A framework for distributed storage and processing of large datasets

Answer 50

Hadoop

Question 51

A fast, in-memory processing engine for Big Data that supports real-time analytics

Answer 51

Spark

Question 52

Tools like __________________ help present complex data in understandable visual formats like charts and graphs.

Answer 52

Tableau, Power BI, or D3.js

Question 53

Applications of Big Data

Answer 53

Healthcare Finance Retail Entertainment

Question 54

Challenges of Big Data

Answer 54

Data Privacy and Security Data Integration Data Quality

Question 55

Handling sensitive data securely

Answer 55

Data Privacy and Security

Question 56

Combining data from multiple sources.

Answer 56

Data Integration

Question 57

: Ensuring that the data is accurate and useful for analysis.

Answer 57

Data Quality