THE NEED FOR DATA COLLECTION AND STORAGE (STUDY OBJECTIVE 1)

Each day that a business operates, it may have hundreds or thousands of transactions with customers and vendors. Every one of these transactions generates data that must be processed to fill customer orders and purchase inventory and supplies. Data are the set of facts collected from transactions, whereas information is the interpretation of data that have been processed. For example, to process a sale to a customer, the business must collect many data items from the customer such as name, address, credit card number, items ordered, and shipping address. These data collected from all transactions that occur represent a large amount of data. This may be more obvious when you think of the volume of sales that occur at large companies such as L.L. Bean, Lands' End, J.Crew, and Walmart, as presented in previous The Real-World example. Similarly, each purchase of inventory or supplies involves collecting and processing a large amount of data. It is necessary to collect and process these data so that they can be translated into information that is useful to the business. Previous chapters described the accounting information systems that capture and process this large volume of data. However, those chapters did not describe the detail regarding the storage, retrieval, and use of these data.

The data collected in any transaction must be stored for many reasons. First, to complete a transaction such as a sale, detailed data must be collected and stored. For example, the warehouse employees would not know which items to pull from warehouse shelves and ship to customers if they could not see a record of items ordered. Second, the data must be stored for future transactions or followup. For example, if you create an account on the J.Crew website to order clothes, you want your customer information to be stored so that you can place your next order without reentering your name, address, and other basic information. Third, the data collected from a transaction must be incorporated into the accounting system so that regular financial statements can be prepared. Without the underlying data for each transaction, it would be impossible for the system to provide information about assets, liabilities, revenues, and expenses for any accounting period. Fourth, management needs to examine and analyze data from transactions to operate the organization in an efficient and effective manner. While there may be other reasons, this short list summarizes the main reasons to store transaction data:

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, receiving the cash, and updating the customer account for sales and collections.
2. To follow up with customers or vendors and to expedite future transactions. For example, if the company stores name, address, and other details about a customer, it need not reenter that data when the customer places future orders.
3. To create accounting reports and financial statements.
4. To provide feedback to management so they can effectively and efficiently manage.

Data collected from transactions are in the form of structured data. Structured data easily fit into rows and columns. These columns usually are fields of fixed length. An example would be ten digits for a phone number. Customer name, credit card number, and total dollar amount of sales are other examples of data that easily fit into rows and columns. Companies also collect unstructured data. Unstructured data do not easily fit into rows and columns of fixed length. An example of unstructured data would be the free-form text of a customer's online review of a product. Since accounting data are structured data, the remainder of this chapter describes the typical storage and processing techniques used in organizations to manage the mountain of structured data resulting from their transactions. The topics described in this chapter include the following:

1. The storage media types for data: sequential and random access
2. Methods of processing data: batch and real time
3. Databases and relational databases
4. Data warehouses, data mining, and OLAP
5. Distributed data processing and distributed databases

After studying this chapter, you should have an understanding of how data are processed and stored, how they are used for processing and inquiries, and what considerations pertain to physical location of the processing and storage of data. There are many details and concepts in each of these areas, and this chapter provides only an overview of each of these. However, it should give you, an accountant, the general understanding you need to use, audit, and assist in the design of IT systems. In addition, ethical concerns related to data and the controls over data are discussed in this chapter.