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Chapter 13 – Direct Access Files, and Data Base Systems
Instructor Manual
➢ The Need For Data Collection And Storage. Data that results from any transaction
must be collected and stored for many reasons.
1. To complete transactions from beginning to end. For a sale, this may involve
taking the order, pulling items from the warehouse, shipping items, billing the
customer, collecting the cash, and crediting the customer account for
payment.
manage.
Accounting data from transactions is in the form of structured data. Structured data
is the type of data that easily fits into rows and columns. Companies also collect
unstructured data. Unstructured data is data that does not easily fit into rows and
columns of fixed length. An example of unstructured data would be the free-form
text in customer reviews of products. This chapter describes the typical storage and
processing techniques used in organizations to manage the mountain of structured
data resulting from transactions.
➢ Storing And Accessing Data. The storage of data and the way in which that data
is used are extremely interrelated. Data that will be needed quickly and frequently
must be stored in a manner that allows frequent and quick access. The reverse of
batch processing, online processing, or online, real-time processing.
➢ Data Processing Techniques. Processing can be accomplished via batch
processing, online processing, or online, real-time processing. When determining
whether batch or real time processing is appropriate, system professionals must
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➢ Databases. A database is a collection of data stored on the computer in a form that
allows the data to be easily accessed, retrieved, manipulated, and stored. The term
database usually implies a shared database within the organization. If data is not in
a shared database, there are two problems. Data redundancy occurs when the
same data is stored in more than one file, rather than in a shared database. Due to
database can be read or modified by individuals or processes. Data have
relationships between records. There are three types of relationships: one–to-one,
one–to-many, and many-to-many.
o The History Of Databases. The earliest databases were flat file databases
in two dimensional tables. These were stored in text format in sequential files
and such files are not efficient ways to access and use single records.
Databases later evolved into hierarchical databases define that relationships
to represent many different kinds of relationships in the data. Relational
databases are built with many tables, with relationships between tables. The
tables are flexible enough to answer an unlimited number of queries. To
obtain this flexibility, the tables within a relational database must be designed
according to specific rules. The process of converting data into tables that
meet the definition of a relational database is called data normalization.
o The Need For Normalized Data. To obtain this flexibility, the tables within a
relational database must be designed according to specific rules. The
process of converting data into tables that meet the definition of a relational
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2. Eliminate redundant data.
3. Eliminate columns not dependent on the primary key.
o Trade-offs in database storage. While the relational database is very
flexible for queries, it is not the most efficient way to store data that will be
used in other ways. The quickest way to access and process records from a
database when their intended use is processing a large volume of
transactions is the hierarchical model. But, the hierarchical model is not
flexible when querying. Thus, there is a trade-off of transaction processing
efficiency for flexibility.
➢ The Use Of A Data Warehouse To Analyze Data. A data warehouse is an
integrated collection of enterprise-wide data that includes five to 10 years of non-
o Build The Data Warehouse. The data in the data warehouse must support
users’ needs and it must be standardized across the enterprise. Rather than
collect and incorporate all of the available data into the data warehouse, it is
important to include only data that meets user needs. Management,
accounting, finance, production and distribution functions will be using this
data warehouse to budget, plan, forecast, and analyze profitability.
o Identify The Data. The data in the data warehouse must be data that
provides the right kind of information to these user groups. To determine data
o Standardize The Data. The data in the data warehouse will come from many
different processes and sub-units across the enterprise. Different
warehouse.
o Cleanse Or Scrub The Data. Since the data in a data warehouse is likely to
come from many different sources within the enterprise, there are likely to be
errors and inconsistencies in the data. To the extent possible, the data
should be cleansed to remove or fix errors or problems in the data.
o Upload The Data. Data from each of the HIP systems must be uploaded to
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➢ Data Analysis Tools. The purpose of a data warehouse is to give managers a rich
source of data that they can query and examine for trends and patterns. Data in the
data warehouse is analyzed by the use of data mining and analytical processing.
o Data Mining. Data mining is the process of searching for identifiable patterns
in data that can be used to predict future behavior. Although there are many
o OLAP. OLAP is a set of software tools that allow online analysis of the data
within a data warehouse. The analytical methods in OLAP usually include:
1. Drill down. This is the successive expansion of data into more detail,
going from high-level data to successively lower levels of data. For
example, if a person is examining sales, drill down would involve
examining sales for the year, then by month, then by week or day. This
different parts of the business.
➢ Distributed Data Processing Data can be stored in a central location, or it can be
distributed across various locations. Similarly, the processing of data and
transactions can occur only in a central location, or distributed across the various
locations. In the early days of computing, data processing and databases were
stored and maintain in a central location. This would be called centralized
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1. Reduced hardware cost. Distributed systems use networks of smaller
computers rather than a single mainframe computer. This configuration is
much less costly to purchase and maintain.
computers.
3. Easier incremental growth. As the organization grows or requires
additional computing resources, new sites can be added quickly and
easily. Adding smaller, networked computers is easier and less costly
than adding a new mainframe computer.
However, it is important to recognize that there are also disadvantages to the
use DDP and DDB. These disadvantages are increased difficulty of
managing, controlling, and maintaining integrity of the data.
o Client/Server Systems. Cloud-based database services are a fast growing
area of IT. Many of the largest computer-related companies are providers of
cloud-based database services. The cloud provider generally provides not
only the data storage space, but the software tools to manage and control the
➢ IT Controls For Data And Databases. The data is a valuable resource that must
be protected with good internal controls. IT-general controls assist in preventing
unauthorized access and in assuring adequate backup. It is important to use
authentication and hacking controls such as log-in procedures, passwords, security
tokens, biometric controls, firewalls, encryption, intrusion detection, and vulnerability
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such as data validation, control totals and reconciliation, and reports that are
analyzed by managers.
➢ Ethical Issues Related To Data. There are many ethical issues related to the
collection, storage, and protection of data in databases. Companies collect and
store a wealth of information about customers in their databases.
o Ethical Obligations Of The Company. All companies collect data from
customers that may be private, non-sharable data. The sensitivity and
privacy of that data depends on the nature of the business and the type of
o Ethical Obligations Of The Employee. Within organizations, many
employees must have access to private data about clients and customers.
These employees have an ethical obligation to avoid misuse of any private or
personal data about customers. There are no specific IT controls that would
prevent authorized employees from disclosing private information, but having
and enforcing a code of ethics within the organization can reduce the chances
of such disclosure. Proper IT control procedures such as log-in procedures,