Enterprise Applications
An enterprise (that’s small “e”, not capital “E,” as in Starship) application/database is one
whose scope is the entire organization or enterprise (or, at least, many different departments).
Such databases are intended to support organization-wide operations and decision
making. Note that an organization may have several enterprise databases, so such a
database is not inclusive of all organizational data. A single operational enterprise database
is impractical for many medium to large organizations due to difficulties in performance
for very large databases, diverse needs of different users, and the complexity of
achieving a single definition of data (metadata) for all database users. An enterprise database
does, however, support information needs from many departments and divisions.
The evolution of enterprise databases has resulted in two major developments:
1. Enterprise resource planning (ERP) systems
2. Data warehousing implementations
Enterprise resource planning (ERP) systems have evolved from the material requirements
planning (MRP) and manufacturing resource planning (MRP-II) systems of
the 1970s and 1980s. These systems scheduled the raw materials, components, and subassembly
requirements for manufacturing processes, and also scheduled shop floor and
product distribution activities. Next, extension to the remaining business functions resulted
in enterprise-wide management systems, or ERP systems. All ERP systems are
heavily dependent on databases to store the integrated data required by the ERP applications.
In addition to ERP systems, there are several specialized applications, such as
customer relationship management (CRM) systems and supply chain management
(SCM) systems, that also are dependent on data stored in databases.
Whereas ERP systems work with the current operational data of the enterprise,
data warehouses collect content from the various operational databases, including personal,
workgroup, department, and ERP databases. Data warehouses provide users with
the opportunity to work with historical data to identify patterns and trends and answers
to strategic business questions. We describe data warehouses in detail in Chapter 9.
Finally, one change that has dramatically affected the database environment is the
ascendance of the Internet, and the subsequent development of applications that are used
by the masses. Acceptance of the Internet by businesses has resulted in important changes
in long-established business models. Very successful companies have been shaken by
competition from new businesses that have employed the Internet to provide improved
customer information and service, to eliminate traditional marketing channels and distribution
channels, and to implement employee relationship management. For example,
customers configure and order their personal computers directly from the computer manufacturers.
Bids are accepted for airline tickets and collectables within seconds of submission,
sometimes resulting in substantial savings for the end consumer. Information about
open positions and company activities is readily available within many companies. Each
of these Web-based applications highlighted use databases extensively.
In the above examples, the Internet is used to facilitate interaction between business
and the customer (B2C) because the customers are necessarily external to the business
However, for other types of applications, the customers of the businesses are other
businesses. Those interactions are commonly referred to as B2B relationships and are
enabled by extranets. An extranet uses Internet technology, but access to the extranet is
not universal as is the case with an Internet application. Rather, access is restricted to
business suppliers and customers with whom an agreement has been reached about legitimate
access and use of each other’s data and information. Finally, an intranet is used
by employees’ of the firm to access applications and databases within the company.
An enterprise (that’s small “e”, not capital “E,” as in Starship) application/database is one
whose scope is the entire organization or enterprise (or, at least, many different departments).
Such databases are intended to support organization-wide operations and decision
making. Note that an organization may have several enterprise databases, so such a
database is not inclusive of all organizational data. A single operational enterprise database
is impractical for many medium to large organizations due to difficulties in performance
for very large databases, diverse needs of different users, and the complexity of
achieving a single definition of data (metadata) for all database users. An enterprise database
does, however, support information needs from many departments and divisions.
The evolution of enterprise databases has resulted in two major developments:
1. Enterprise resource planning (ERP) systems
2. Data warehousing implementations
Enterprise resource planning (ERP) systems have evolved from the material requirements
planning (MRP) and manufacturing resource planning (MRP-II) systems of
the 1970s and 1980s. These systems scheduled the raw materials, components, and subassembly
requirements for manufacturing processes, and also scheduled shop floor and
product distribution activities. Next, extension to the remaining business functions resulted
in enterprise-wide management systems, or ERP systems. All ERP systems are
heavily dependent on databases to store the integrated data required by the ERP applications.
In addition to ERP systems, there are several specialized applications, such as
customer relationship management (CRM) systems and supply chain management
(SCM) systems, that also are dependent on data stored in databases.
Whereas ERP systems work with the current operational data of the enterprise,
data warehouses collect content from the various operational databases, including personal,
workgroup, department, and ERP databases. Data warehouses provide users with
the opportunity to work with historical data to identify patterns and trends and answers
to strategic business questions. We describe data warehouses in detail in Chapter 9.
Finally, one change that has dramatically affected the database environment is the
ascendance of the Internet, and the subsequent development of applications that are used
by the masses. Acceptance of the Internet by businesses has resulted in important changes
in long-established business models. Very successful companies have been shaken by
competition from new businesses that have employed the Internet to provide improved
customer information and service, to eliminate traditional marketing channels and distribution
channels, and to implement employee relationship management. For example,
customers configure and order their personal computers directly from the computer manufacturers.
Bids are accepted for airline tickets and collectables within seconds of submission,
sometimes resulting in substantial savings for the end consumer. Information about
open positions and company activities is readily available within many companies. Each
of these Web-based applications highlighted use databases extensively.
In the above examples, the Internet is used to facilitate interaction between business
and the customer (B2C) because the customers are necessarily external to the business
However, for other types of applications, the customers of the businesses are other
businesses. Those interactions are commonly referred to as B2B relationships and are
enabled by extranets. An extranet uses Internet technology, but access to the extranet is
not universal as is the case with an Internet application. Rather, access is restricted to
business suppliers and customers with whom an agreement has been reached about legitimate
access and use of each other’s data and information. Finally, an intranet is used
by employees’ of the firm to access applications and databases within the company.
Allowing such access to a business database raises data security and integrity
issues that are new to the management of information systems, where data have traditionally
been closely guarded and secured within each company. These issues are covered
in more detail in Chapters 8 and 10.
Table 1-5 presents a brief summary of the different types of databases outlined in
this section.
EVOLUTION OF DATABASE SYSTEMS
Database management systems were first introduced during the 1960s and have continued
to evolve during subsequent decades. Figure 1-8a sketches this evolution by highlighting
the database technology (or technologies) that were dominant during each
decade. In most cases, the period of introduction was quite long, and the technology
was first introduced during the decade preceding the one shown in the figure. For example,
the relational model was first defined by E. F. Codd, an IBM research fellow, in a
paper published in 1970 (Codd, 1970). However, the relational model did not realize
widespread commercial success until the 1980s. For example, the challenge of the 1970s
where programmers needed to write complex programs to access data was addressed
by the introduction of the Structured Query Language (SQL) in the 1980s.
Figure 1-8b shows a visual depiction of the organizing principle underlying each
of the major database technologies. For example, in the hierarchical model, files are organized
in a top-down structure that resembles a tree or genealogy chart, whereas in
the network model, each file can be associated with an arbitrary number of other files.
The relational model (the primary focus of this book) organizes data in the form of
tables and relationships among them. The object-oriented model is based on object
classes and relationships among them. As shown in Figure 1-8b, an object class encapsulates
attributes and methods. Object-relational databases are a hybrid between objectoriented
and relational databases. Finally, multidimensional databases, which form the
basis for data warehouses, allow us to view data in the form of cubes or a star schema;
we discuss this in more detail in Chapter 9. Database management systems were developed
to overcome the limitations of file processing systems, described in a previous
section. To summarize, some of the following four objectives generally drove the development
and evolution of database technology:
1. The need to provide greater independence between programs and data, thereby
reducing maintenance costs
2. The desire to manage increasingly complex data types and structures
3. The desire to provide easier and faster access to data for users who have neither a
background in programming languages nor a detailed understanding of how data
are stored in databases
4. The need to provide ever more powerful platforms for decision support applications
1960s
File processing systems were still dominant during this period. However, the first
database management systems were introduced during this decade and were used primarily for large and complex ventures such as the Apollo moon-landing project. We can regard this as an experimental “proof-of-concept” period in which the feasibility of
managing vast amounts of data with a DBMS was demonstrated. Also, the first efforts
at standardization were taken with the formation of the Data Base Task Group in the
late 1960s.
issues that are new to the management of information systems, where data have traditionally
been closely guarded and secured within each company. These issues are covered
in more detail in Chapters 8 and 10.
Table 1-5 presents a brief summary of the different types of databases outlined in
this section.
EVOLUTION OF DATABASE SYSTEMS
Database management systems were first introduced during the 1960s and have continued
to evolve during subsequent decades. Figure 1-8a sketches this evolution by highlighting
the database technology (or technologies) that were dominant during each
decade. In most cases, the period of introduction was quite long, and the technology
was first introduced during the decade preceding the one shown in the figure. For example,
the relational model was first defined by E. F. Codd, an IBM research fellow, in a
paper published in 1970 (Codd, 1970). However, the relational model did not realize
widespread commercial success until the 1980s. For example, the challenge of the 1970s
where programmers needed to write complex programs to access data was addressed
by the introduction of the Structured Query Language (SQL) in the 1980s.
Figure 1-8b shows a visual depiction of the organizing principle underlying each
of the major database technologies. For example, in the hierarchical model, files are organized
in a top-down structure that resembles a tree or genealogy chart, whereas in
the network model, each file can be associated with an arbitrary number of other files.
The relational model (the primary focus of this book) organizes data in the form of
tables and relationships among them. The object-oriented model is based on object
classes and relationships among them. As shown in Figure 1-8b, an object class encapsulates
attributes and methods. Object-relational databases are a hybrid between objectoriented
and relational databases. Finally, multidimensional databases, which form the
basis for data warehouses, allow us to view data in the form of cubes or a star schema;
we discuss this in more detail in Chapter 9. Database management systems were developed
to overcome the limitations of file processing systems, described in a previous
section. To summarize, some of the following four objectives generally drove the development
and evolution of database technology:
1. The need to provide greater independence between programs and data, thereby
reducing maintenance costs
2. The desire to manage increasingly complex data types and structures
3. The desire to provide easier and faster access to data for users who have neither a
background in programming languages nor a detailed understanding of how data
are stored in databases
4. The need to provide ever more powerful platforms for decision support applications
1960s
File processing systems were still dominant during this period. However, the first
database management systems were introduced during this decade and were used primarily for large and complex ventures such as the Apollo moon-landing project. We can regard this as an experimental “proof-of-concept” period in which the feasibility of
managing vast amounts of data with a DBMS was demonstrated. Also, the first efforts
at standardization were taken with the formation of the Data Base Task Group in the
late 1960s.
1970s
During this decade the use of database management systems became a commercial reality.
The hierarchical and network database management systems were developed,
largely to cope with increasingly complex data structures such as manufacturing bills of
materials that were extremely difficult to manage with conventional file processing
methods. The hierarchical and network models are generally regarded as first-generation
DBMS. Both approaches were widely used, and in fact many of these systems continue
to be used today. However, they suffered from the same key disadvantages as file
processing systems: limited data independence and lengthy development times for
application development.
1980s
To overcome these limitations, E. F. Codd and others developed the relational data
model during the 1970s. This model, considered second-generation DBMS, received
widespread commercial acceptance and diffused throughout the business world during
the 1980s. With the relational model, all data are represented in the form of tables.
Typically, SQL is used for data retrieval. Thus, the relational model provides ease of access
for nonprogrammers, overcoming one of the major objections to first-generation
systems. The relational model has also proven well suited to client/server computing,
parallel processing, and graphical user interfaces (Gray, 1996).
1990s
The 1990s ushered in a new era of computing, first with client/server computing, and
then with data warehousing and Internet applications becoming increasingly important.
Whereas the data managed by a DBMS during the 1980s were largely structured
(such as accounting data), multimedia data (including graphics, sound, images, and
video) became increasingly common during the 1990s. To cope with these increasingly
complex data, object-oriented databases (considered third generation) were introduced
during the late 1980s (Grimes, 1998).
Because organizations must manage a vast amount of structured and unstructured
data, both relational and object-oriented databases are of great importance today.
In fact, some vendors are developing combined object-relational DBMSs that can manage
both types of data. We describe object-relational databases in Chapter 13.
2000 and Beyond
Currently, the major type of database that is still most widely used is the relational
database. However, object-oriented and object-relational databases are also garnering
some attention, especially as the growth in unstructured content continues. This
growth is partially fueled by Web 2.0 applications such as blogs, wikis, and social
networking sites (Facebook, MySpace, Twitter, LinkedIn, etc.) and partially by how
easy it has become to create unstructured data such as pictures and images.
Developing effective database practices to deal with these diverse types of data is
going to continue to be of prime importance as we move into the next decade. As larger
computer memory chips become cheaper, new database technologies to manage
in-memory databases are emerging. This trend opens up new possibilities for even
faster database processing.
Recent regulations such as Sarbanes-Oxley, HIPAA, and the Basel Convention
have highlighted the importance of good data management practices and the ability to
reconstruct historical positions has gained prominence. This has led to developments in computer forensics with increased emphasis and expectations around discovery of
electronic evidence. The importance of good database administration capabilities also
continues to rise because effective disaster recovery and adequate security are mandated
by these regulations.
During this decade the use of database management systems became a commercial reality.
The hierarchical and network database management systems were developed,
largely to cope with increasingly complex data structures such as manufacturing bills of
materials that were extremely difficult to manage with conventional file processing
methods. The hierarchical and network models are generally regarded as first-generation
DBMS. Both approaches were widely used, and in fact many of these systems continue
to be used today. However, they suffered from the same key disadvantages as file
processing systems: limited data independence and lengthy development times for
application development.
1980s
To overcome these limitations, E. F. Codd and others developed the relational data
model during the 1970s. This model, considered second-generation DBMS, received
widespread commercial acceptance and diffused throughout the business world during
the 1980s. With the relational model, all data are represented in the form of tables.
Typically, SQL is used for data retrieval. Thus, the relational model provides ease of access
for nonprogrammers, overcoming one of the major objections to first-generation
systems. The relational model has also proven well suited to client/server computing,
parallel processing, and graphical user interfaces (Gray, 1996).
1990s
The 1990s ushered in a new era of computing, first with client/server computing, and
then with data warehousing and Internet applications becoming increasingly important.
Whereas the data managed by a DBMS during the 1980s were largely structured
(such as accounting data), multimedia data (including graphics, sound, images, and
video) became increasingly common during the 1990s. To cope with these increasingly
complex data, object-oriented databases (considered third generation) were introduced
during the late 1980s (Grimes, 1998).
Because organizations must manage a vast amount of structured and unstructured
data, both relational and object-oriented databases are of great importance today.
In fact, some vendors are developing combined object-relational DBMSs that can manage
both types of data. We describe object-relational databases in Chapter 13.
2000 and Beyond
Currently, the major type of database that is still most widely used is the relational
database. However, object-oriented and object-relational databases are also garnering
some attention, especially as the growth in unstructured content continues. This
growth is partially fueled by Web 2.0 applications such as blogs, wikis, and social
networking sites (Facebook, MySpace, Twitter, LinkedIn, etc.) and partially by how
easy it has become to create unstructured data such as pictures and images.
Developing effective database practices to deal with these diverse types of data is
going to continue to be of prime importance as we move into the next decade. As larger
computer memory chips become cheaper, new database technologies to manage
in-memory databases are emerging. This trend opens up new possibilities for even
faster database processing.
Recent regulations such as Sarbanes-Oxley, HIPAA, and the Basel Convention
have highlighted the importance of good data management practices and the ability to
reconstruct historical positions has gained prominence. This has led to developments in computer forensics with increased emphasis and expectations around discovery of
electronic evidence. The importance of good database administration capabilities also
continues to rise because effective disaster recovery and adequate security are mandated
by these regulations.