Chapter 11 - ERP Systems Flashcards
___________ are multiple module software packages that evolved primarily from traditional
manufacturing resource planning (MRP II) systems.
ERP systems
The _______________ coined the term ERP, which has become widely used in recent years.
Gartner Group
The objective of ERP is:
to integrate key processes of the organization such as order entry, manufacturing, procurement and accounts payable, payroll, and human resources.
Under this approach, a database management system is used to provide minimal technological advantage over flat-file systems.
closed database architecture
ERP functionality falls into two general groups of applications:
core applications and business analysis applications
________________ are those applications that operationally support the day-to-day activities of the business. If these applications fail, so does the business. Typical examples include, but are not limited to, sales and distribution, business planning, production planning, shop floor control, and logistics
Core applications
Core applications are also called ___________________.
online transaction processing (OLTP) applications
A ____________ is a database constructed for quick searching, retrieval, ad hoc queries, and ease of use
data warehouse
__________________ includes decision support, modeling, information retrieval, ad hoc reporting/analysis, and what-if analysis.
Online analytical processing (OLAP)
An ERP system could not exist without having a data warehouse. TRUE OR FALSE.
FALSE
Organizations that have not implemented an ERP may deploy data warehouses. TRUE OR FALSE.
TRUE
Most ERP systems are based on the ______________
client-server model
Most ERP systems are based on the ______________
client-server model
The ___________________ is a form of network topology in which a user’s computer or terminal (the client) accesses the ERP programs and data via a host computer called the server.
client-server model
Two basic architectures of a client-server model are the _____________________.
two-tier model and the three-tier model
In a typical __________ the server handles both application and database duties. Client computers are responsible for presenting data to the user and passing user input back to the server. Some ERP vendors use this approach for local area network (LAN) applications for which the demand on the server is restricted to relatively small population of users.
two-tier model
The database and application functions are separated in the _______________. This architecture is typical of large ERP systems that use wide area networks (WANs) for connectivity among the users. Satisfying client requests requires two or more network connections. Initially, the client establishes communications with the application server.
three-tier model
___________ consist of large numbers of relatively simple transactions, such as
updating accounting records that are stored in several related tables.
OLTP events
When implementing an ERP system that will include a data warehouse, a clear distinction needs to be made between the competing types of data processing:
OLTP and OLAP
____________ is the aggregation or roll-up of data. For example, sales offices data can be rolled up to districts and districts rolled up to regions
Consolidation
____________ permits disaggregating data to reveal the underlying details that explain
certain phenomena. For example, the user can drill down from total sales returns for
a period to identify the actual products returned and the reasons for their return.
Drill-down
__________________ enables the user to examine data from different viewpoints. One
slice of data might show sales within each region. Another slice might present sales
by product across regions. This is often performed along a time axis to
depict trends and patterns.
Slicing and dicing
____________ allow users to analyze complex data relationships. The physical database itself is organized in such a way that related data may be rapidly retrieved across
multiple dimensions. These servers need to be efficient when storing and processing multidimensional data.
OLAP servers
OLAP can be characterized as online transactions that:
• Access very large amounts of data (e.g., several years of sales data).
• Analyze the relationships among many types of business elements such as sales, products, geographic regions, and marketing channels.
• Involve aggregated data such as sales volumes, budgeted dollars, and dollars spent.
• Compare aggregated data over hierarchical time periods (e.g., monthly, quarterly, yearly).
• Present data in different perspectives such as sales by region, by distribution channel, or by product.
• Involve complex calculations among data elements such as expected profit as a function of sales revenue for each type of sales channel in a particular region.
• Respond quickly to user requests so they can pursue an analytical thought process without being stymied by system delays.
The difference between OLAP and OLTP
OLTP applications support mission-critical tasks through simple queries of operational databases. OLAP applications support management-critical tasks through analytical investigation of complex data associations that are captured in data warehouses
The ____________ is the set of activities associated with moving goods from the raw materials stage to the consumer
supply chain
_________________ links all of the partners in the chain, including vendors, carriers, third-party logistics companies, and information systems providers.
Supply Chain Management
When the data warehouse is organized for a single department or function, it is often called a ________.
data mart.
The process of data warehousing involves:
- extracting
- converting
- standardizing an organization’s operational data from ERP and legacy systems and loading it into a
central archive—the data warehouse
When the data warehouse is organized for a single department or function, it is often called a _____________.
data mart.
___________ is the process of selecting, exploring, and modeling large amounts of data to uncover relationships and global patterns that exist in large databases but are hidden among the vast number of facts.
Data mining
This involves sophisticated techniques that use database queries and artificial intelligence to model real-world phenomena from data collected from the warehouse.
Data mining
The data warehousing process has the
following essential stages:
• Modeling data for the data warehouse
• Extracting data from operational databases
• Cleansing extracted data
• Transforming data into the warehouse model
• Loading the data into the data warehouse database
_________________ is the process of collecting data from operational databases, flat files, archives, and external data sources.
Data extraction
A technique called changed _________ can dramatically reduce the extraction time by capturing only newly modified data.
data capture
A key feature of a data warehouse is that the ______________________.
data contained in it are in a nonvolatile, stable state.
________________ involves filtering out or repairing invalid data prior to being stored in the warehouse.
Data cleansing
A data warehouse is composed of:
detail and summary data.
Reasons for employing a data warehouse:
- Internal Efficiency
- Integration of Legacy Systems
- Consolidation of Global Data
_______________ is an OLAP feature of data mining tools available to the user.
Drill-down capability
The primary reason for data warehousing is to _____________________________.
optimize business performance
Fields of Applications of Data Mining
Banking/Investments
Health Care and Medical Insurance
Marketing
___________ is the system’s ability to grow smoothly and economically as user requirements increase.
Scalability
________________________ is the ability to increase system capacity at an acceptable incremental cost per unit of capacity without encountering limits that would demand a system upgrade or replacement
Smooth and economical growth
_______________________ pertain to volume-related activities such as transaction processing volume, data entry volume, data output volume, data storage volume, or increases in the user population.
User requirements
