Business Processes and E-Tailing Quiz

<p>Coordinated collaboration among functional areas (A)</p> Signup and view all the answers

<p>The strategy of offering a large number of unique items in small quantities (B)</p> Signup and view all the answers

<p>The final product or service delivered to the customer (B)</p> Signup and view all the answers

<p>A collection of individual stores grouped under one internet address (D)</p> Signup and view all the answers

<p>Providing information (A)</p> Signup and view all the answers

<p>Effectiveness (A)</p> Signup and view all the answers

<p>The process of developing a new drug involving various functions (B)</p> Signup and view all the answers

<p>The inclusion of a magnetic stripe (D)</p> Signup and view all the answers

<p>Challenges associated with shipping and delivery (C)</p> Signup and view all the answers

<p>Low intensity of competition (C)</p> Signup and view all the answers

<p>Marketing and sales (A)</p> Signup and view all the answers

<p>By improving their own performance (C)</p> Signup and view all the answers

<p>Additional unit production costs approach zero (C)</p> Signup and view all the answers

<p>Marketing and sales (A)</p> Signup and view all the answers

<p>Processing of incoming materials (B)</p> Signup and view all the answers

<p>Distribution and shipping (A)</p> Signup and view all the answers

<p>Rapid feature matching leading to similarities (D)</p> Signup and view all the answers

<p>They contribute to competitive advantage. (C)</p> Signup and view all the answers

<p>Data is organized in more than two dimensions, often as a data cube. (D)</p> Signup and view all the answers

<p>Third-party data and website data. (B)</p> Signup and view all the answers

<p>It assesses the quality and characteristics of the data before integration. (B)</p> Signup and view all the answers

<p>Some source systems retain outdated and poor-quality data. (A)</p> Signup and view all the answers

<p>To describe the data and improve understanding of the data content and structure. (A)</p> Signup and view all the answers

<p>Organizing and storing data from multiple different systems efficiently. (B)</p> Signup and view all the answers

<p>Selecting an optimal source system can enhance data quality and relevance. (D)</p> Signup and view all the answers

<p>Diverse data types such as RFID sensing data. (C)</p> Signup and view all the answers

<p>They emerge as responses to identified business challenges or pain points. (C)</p> Signup and view all the answers

<p>Transactional databases require frequent updates while data warehouses are read-only. (B)</p> Signup and view all the answers

<p>Optimized for online transaction processing (OLTP) (A)</p> Signup and view all the answers

<p>Data marts can be implemented faster and at a lower cost. (A)</p> Signup and view all the answers

<p>Online analytical processing (OLAP) (C)</p> Signup and view all the answers

<p>Data warehouses are organized by subjects, unlike transactional databases which are process-oriented. (B)</p> Signup and view all the answers

<p>It ensures historical accuracy by preventing user alterations. (C)</p> Signup and view all the answers

<p>They store historical data over long periods of time. (A)</p> Signup and view all the answers

<p>Data is combined from multiple sources around specific subjects. (B)</p> Signup and view all the answers

<p>Analyzing accumulated data for decision support. (C)</p> Signup and view all the answers

<p>Transactional databases are optimized for retrieving individual records. (C)</p> Signup and view all the answers

A series of related activities that produce a valuable product or service for the organization, its partners, or customers.

Materials, services, and information that are changed or transformed during the process.

People and equipment that perform process tasks.

The finished product or service created by the process.

Doing tasks well without wasting resources or time.

Creating outputs that are valuable to the customer.

Business processes that involve multiple functional areas within an organization.

The intensity of competition among existing firms in an industry.

A way for a company to outperform its rivals, usually by allowing customers to use data from their products.

The cost to produce additional digital products is almost zero once the product is developed.

A model used to identify competitive strategies in an organization by examining the sequence of activities.

A series of activities that transforms inputs into valuable outputs.

Activities directly related to producing and distributing a firm's products or services.

Activities that do not add value directly to a product/service but support primary activities.

Activities involved in receiving and processing incoming materials, e.g., raw materials.

Activities related to getting products ready for delivery.

Prepaid cards that allow you to store a fixed amount of money and spend it as needed, reducing the balance with each transaction.

Cards with a chip that stores information and often includes a magnetic stripe for compatibility with older systems.

Selling products and services directly online through virtual storefronts or electronic malls.

The elimination of intermediaries (middlemen) from a supply chain, often due to automation or technology.

Services provided by intermediaries that enhance the core product or service, and are often difficult to fully automate.

A repository of historical data organized by subject to support decision-making. It's designed for complex queries and analysis, but can be expensive to implement.

A scaled-down, less expensive version of a data warehouse focused on specific business units or departments. It's faster to implement and provides targeted data analysis.

Organizations build data warehouses and marts to overcome limitations of transactional databases, which are designed for individual record transactions. These systems offer better data organization, efficient analysis, and historical data access.

Transactional databases use OLTP (Online Transaction Processing) for fast, individual transactions. Data warehouses/marts utilize OLAP (Online Analytical Processing) for analyzing large data sets to support decision-making.

Data warehouses and marts combine data from multiple sources into a consistent view around specific subjects (e.g., customers).

They store historical data, allowing for the analysis of trends and long-term patterns over time.

Data in warehouses and marts cannot be altered by users, ensuring data integrity and historical accuracy.

Data in warehouses and marts is organized by subject (e.g., customer, product), unlike transactional systems that focus on business processes.

They provide better organization, insights through analysis, and access to historical data, supporting business decisions.

They play a crucial role in gaining valuable insights from data, which can be used to improve sales, marketing, and overall business performance.

A multidimensional data structure that organizes data in more than two dimensions, often used in data warehouses.

Subjects like product, location, or time that define the different axes of a data cube in data warehouses.

Databases or applications that provide data to a data warehouse or data mart.

Analyzing data quality and characteristics before loading it into a warehouse to understand its structure and potential problems.

Data organized in multiple dimensions, typically stored in a data cube, unlike relational databases with two-dimensional tables.

Data about data in a repository, describing its structure, meaning, and relationships.

Processes and policies for managing data quality, security, and accessibility in a data warehouse.

Inaccurate, incomplete, or inconsistent data that can lead to faulty analysis and decision-making.