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Information Management > Module 4 > Flashcards

Module 4 Flashcards

1
Q

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

A

Data management

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2
Q

Data is an ?

A

asset

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3
Q

It is crucial for an organization’s success

A

efficient data management

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4
Q

Relational databases, tables (MySQL)

A

Structured data

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5
Q

Emails, videos, social media content (NoSQL databases)

A

Unstructured data

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6
Q

Two types of data

A

Structured and unstructured data.

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7
Q

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

A

unstructured data.

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8
Q

Ideal for transactional systems like customer records or sales
databases.

A

Structured data

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9
Q

Ways of data storage and retrieval/databases and file system

A

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)

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10
Q

Techniques for faster data retrieval

A

Indexing, caching and optimization

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11
Q

The entire data lifecycle (CSPDA)

A

collection, storage, processing, dissemination, archiving

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12
Q

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

A

Indexing

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13
Q

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

A

Indexing

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14
Q

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.

A

Indexes

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15
Q

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

A

Caching

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16
Q

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.

A

Caching

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17
Q

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

A

Optimization

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18
Q

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

A

Data Quality

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19
Q

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

A

Data Integrity

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20
Q

Key Dimensions of data quality

A

Accuracy, completeness, consistency, timeliness and validity

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21
Q

Data must be correct and free from errors

A

Accuracy

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22
Q

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

A

Completeness

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23
Q

Data should be uniform across systems and sources.C

A

Consistency

24
Q

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

A

Timeliness

25
Q

Data should conform to expected formats and values

A

Validity

26
Q

Causes of poor data quality and integrity

A

Human Error
System Integration Issues
Outdated data

27
Q

: Data entry mistakes are common

A

Human eror

28
Q

Merging data from different sources can introduce
inconsistencies.

A

System Integration Issues

29
Q

Without regular updates, data becomes irrelevant or inaccurate.

A

Outdated data

30
Q

Removing duplicates, correcting errors, and filling missing data.

A

Data Cleaning

31
Q

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

A

Validation

32
Q

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

A

Governance

33
Q

Data Integrity Methods

A

Encryption
Audit Trails
Referential Integrity

34
Q

: Ensures data security during storage and transmission.

A

Encryption

35
Q

: Track who accessed or changed data.

A

Audit Trails

36
Q

Ensuring relationships between tables in a
database remain consistent.

A

Referential Integrity

37
Q

Republic Act 10173

A

Data Privacy Act of 2012

38
Q

Data Privacy Act of 2012

A

Republic Act 10173

39
Q

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

A

Republic Act 10173 or Data Privacy Act of 2012

40
Q

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

A

Big Data

41
Q

5 V’s of Big Data

A

Volume
Velocity
Variety
Veracity
Value

42
Q

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

A

Volume

43
Q

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

A

Velocity

44
Q

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

A

Variety

45
Q

Data accuracy and trustworthiness

A

Veracity

46
Q

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

A

Value

47
Q

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

A

Data Analytics

48
Q

Types of Data Analytics:

A

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

49
Q

Big Data Tools and Technologies

A

For Distributed Computing:
Hadoop
Spark

For Data Storage

NoSQL Databases like MongoDB, or Cassandra

For Data Visualization

Tableau, PowerBI, D3.js

50
Q

: A framework for distributed storage and processing of large datasets

A

Hadoop

51
Q

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

A

Spark

52
Q

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

A

Tableau, Power BI, or D3.js

53
Q

Applications of Big Data

A

Healthcare
Finance
Retail
Entertainment

54
Q

Challenges of Big Data

A

Data Privacy and Security

Data Integration

Data Quality

55
Q

Handling sensitive data securely

A

Data Privacy and Security

56
Q

Combining data from multiple sources.

A

Data Integration

57
Q

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

A

Data Quality

Information Management (6 decks)

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