PROB IMPORTANT Flashcards

1
Q

Transmission Control Protocol (TCP)

A

Protocol to transfer large files over network, ensuring data arrives intact

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2
Q

Transaction Processing System (TPS)

A

Track, store, and process data from an organization’s daily business activities

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3
Q

Ad hoc (on-demand) reports

A

Special reports created as needed, often with unique information not in routine reports

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4
Q

Types of Routine/ad hoc Reports

A

Drill-down
Key indicator
Comparative

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5
Q

Drill-down reports

A

Reports that provide more detailed information than routine reports

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6
Q

Key indicator reports

A

Reports that summarize the performance of important activities

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7
Q

Comparative reports

A

Compare the performance of different business units or time periods

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8
Q

Enterprise Resource Planning (ERP) systems

A

Systems that help a business work together by sharing information, organizing resources, and using one software and database for the whole company

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9
Q

ERP II systems

A

ERP systems that connect a company’s key business systems (like inventory and production) with its customers, suppliers, and other partners through the web

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10
Q

ERP Implementation Methods

A

Vanilla Approach
Custom Approach
Best of Breed Approach

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11
Q

Customer Relationship Management (CRM)

A

A strategy focused on meeting customer needs and delivering high-quality, responsive services

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12
Q

Customer-facing CRM applications

A

Areas where customers directly interact with the organization

customer service, sales force automation, marketing, and campaign management

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13
Q

Customer-Touching CRM Applications

A

Applications and technologies that customers interact with and typically help themselves

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14
Q

Customer-Touching CRM Methods

A

Customized Products
Loyalty Programs
FAQs

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15
Q

Push Model

A

Company makes products based on guesses about what customers will want. They produce the items first and then try to sell them

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16
Q

Pull Model

A

A business model where production starts only after a customer places an order, and companies make just what the customer wants. This is linked to mass customization

17
Q

Herbert Simon Decision Making

A

Intelligence
Design
Choice

18
Q

Intelligence Phase

A

Identify the Problem/Opportunity

Gather Information to Understand the situation

19
Q

Design Phase

A

What are my options?

20
Q

Choice Phase

A

Select the best solution or course of action.
Implement the decision

21
Q

Business Analytics (BA) Tools

A

Online Analytical Processing (OLAP)
Data Mining
Decision-Support Systems (DSSs)

22
Q

Online Analytical Processing (OLAP)

A

Helps analyze data by breaking it into parts (slicing and dicing) to look at different categories (dimensions) and numbers (measures)

23
Q

Data Mining

A

The process of searching for valuable business insights in large databases, data warehouses, or data marts

24
Q

Decision-Support Systems (DSSs)

A

Uses data to solve semi-structured and unstructured problems

25
Q

Systems Development Life Cycle (SDLC)

A

A step-by-step process for planning, building, and managing big IT projects

26
Q

Alternative Methods/Tools for System Development

A

Joint Application Design (JAD)
Rapid Application Development (RAD)
Agile Development
End-User Development

27
Q

Joint Application Design (JAD)

A

A group-based method to gather user requirements and create system designs

28
Q

Rapid Application Development (RAD)

A

A method for creating software quickly using special tools and an approach that repeats steps to improve the system until it’s high-quality

29
Q

Agile Development

A

A software development method that delivers functionality in short, rapid cycles (weeks) with frequent communication, development, testing, and delivery

30
Q

End-User Development

A

An approach where the organization’s end users create their own applications with minimal or no help from the IT department

31
Q

Machine Learning (ML)

A

A type of artificial intelligence that allows systems to automatically learn and improve from experience without being explicitly programmed

32
Q

Neural Network (NN)

A

Virtual “neurons” arranged in layers that work together to simulate the human brain, to solve problems or recognize patterns

33
Q

Backpropagation

A

A supervised learning method used to update a model’s parameters to improve the accuracy of its predictions.

34
Q

Recurrent Neural Network (RNN)

A

A type of neural network that works with data in order, where each step depends on what happened before

35
Q

Convolutional Neural Network (CNN)

A

Used to understand images by looking at details

36
Q

Generative Adversarial Network (GAN)

A

Has 2 parts
Generator: Learns to create realistic data.
Discriminator: Learns to distinguish between real and generated (fake) data