Key Concepts in Accounting Information Systems

data

facts that are collected, recorded, stored and processed by an information system.

Information

data that have been organized and processed to provide meaning and improve decision making.

Value of information

when the benefits exceed the costs of gathering, maintaining, and storing data.

Benefits

ex. Improved decision making

Cost

ex. Time and resources used to get the information

Transactions

an agreement between two entities to exchanged goods, services, or any other event that can be measured in economic terms by an organization.

Transaction processing

process of capturing transaction data, processing it, storing it for later use, and producing information output, such as a managerial report or a financial statement.

Transaction cycles

major give-get exchanges that occur frequently in most companies.

Accounting information system

a system that collects, records, stores, and processes data to produce information for decision makers.

Value chain

links together the different activities within an organization that provide value to the customer.

Primary activities of a value chain

provide direct value to the customer.

Inbound logistics

real time inbound inventory data, location of distribution facilities, trucks, material handling, warehouse.

Operations

standardized model, access to real time sales and inventory system.

Outbound logistics

order processing, full delivery trucks.

Marketing and sales

pricing, communication, promotion, products based in community needs, low prices.

Service

delivery, installation, repair, greeters, customer service focus.

Supporting activities of a value chain

enable primary activities to be efficient and effective.

Firm infrastructure

management, finance, legal, planning.

Human resource management

professional development, employee relations, performance appraisals, recruiting, competitive wages, training programs.

Technology development

integrated supply chain system, real time sales information.

Procurement

real time inventory, communication with suppliers, purchase supplies and materials.

Supply chain

an extended system that includes the organization's value chain as well as its suppliers, distributors, customers, manufacturers, and retailers.

Data processing cycle

the operations performed on data to generate meaningful and relevant information.

Data input

capture transaction data, data are accurate and complete, company policies followed.

Source documents

documents used to capture transaction data at its source when the transaction takes place.

Paper source documents

physical records that provide evidence of a business transaction, like invoices, receipts, checks, etc.

Turnaround documents

company output sent to an external part, who adds data to the document, and then are returned as an input.

Source data automation

the collection of transaction data in machine readable form at the time and place of origin (ex: ATM, point of sale scanners, barcode scanners).

Chart of accounts

organized list of all accounts used by a business to record its financial transactions. It includes assets, liabilities, equity, revenues, and expenses.

General journal

is used to record infrequent or nonroutine (large number of repetitive) transactions

Subsidiary ledger

records all the detailed data for any general ledger account that has many individual subaccounts

Audit trail

a traceable path of a transaction through a data processing system from point of origin to final output, or backward.

Control account

a summary account in the general ledger that consolidates and checks the accuracy of detailed transactions recorded in a subsidiary ledger

Sequence codes

items numbered consecutively to account for all items (ex: prenumbered forms)

Block codes

blocks of numbers reserved for specific categories of data (ex: product numbers that start with 2 are refrigerators)

Group codes

two or more subgroups of digits used to code items (ex: car vin #'s)

Mnemonic codes

letters and numbers interspersed to identify an item (ex: Dry300W05 is low end (300), white (W) dryer (DRY) made by Sears (05))

Parts of a database

files (master/transaction) which include, records (entities) which include, attributes (individual fields) which include, data value

4 types of data processing activities

creating new records, reading existing data, updating previous record or data, deleting data (CRUD)

Batch processing

collects and processes data in groups at a scheduled time

Online batch processing

data is entered online but still processed later in batches

Real time processing

processes data immediately as the transaction occurs

Document

records of transaction or other company data (ex: sales invoice)

Report

system output, organized in a meaningful fashion (ex: monthly sales report, annual report)

Query

a request for the database to provide the information needed to deal with a problem or answer a question (ex: what division had the most sales for the month?)

Smart contracts

regular contracts with terms and agreements stored in the blockchain in such a way that when the terms are met, they can auto execute to fulfill the contract.

Blockchain

individual digital records, called blocks, linked together using cryptography in a single list, called a chain. It is a distributed ledger that functions as a decentralized database.

Enterprise Resourcing Planning (ERP) system

a system that integrates all aspects of an organization's activities to one system

Advantages of an ERP system

integrated enterprise wide single view of the organization's data which streamlines the flow of information, data captured once, greater visibility and monitoring capabilities for management, improved access of control of the data through security settings, standardization of procedures and reports, improves customer service, increases productivity through automation

Disadvantages of an ERP system

costly, significant amount of time to implement, standardizing a business process to use the ERP, complexity, user resistance

Documentation

a formal record that describes a system or process with narratives, flowcharts, diagrams, and other written materials

Systems development and changes

standardize and improve processes

Efficient knowledge transfer

includes employee training and employee work guide

Effective audits

internal and external audit

Comply with laws and regulations

includes the Sarbanes-Oxley Act

Evaluate and improve internal controls

management and auditors

Business process diagrams

A visual way to describe the different steps of activities in a business process.

Flow objects

Elements that include events, activities, and gateways.

Connecting objects

Elements that include sequence flow, message flow, and association.

Swim lanes

Elements that include pool or lanes.

Artifacts

Elements that include data objects, annotation, group, control, risk.

Flowchart

A pictorial and analytical technique that uses a standard set of symbols to describe some aspects of an information system in a clear, concise, and logical manner.

Document flowchart

Shows the flow of documents and data for a process, useful in evaluating internal controls.

System flowchart

Depicts the data processing cycle for a process in a system (ex: sales processing).

Program flowchart

Illustrates the sequence of logic in the system flowchart.

Data flow diagrams

A graphical description of the flow of data within an organization.

Context diagram

The highest level data flow diagram that provides a summary level view of the data flow.

Subdividing the DFD to lower levels

A method to better satisfy users' different needs by increasing amounts of detail.

Big data

Datasets that are too large and complex for businesses' existing systems to handle using their traditional capabilities.

Volume

Refers to the massive amount of data involved.

Velocity

Refers to the fact that the data comes in at quick speeds or in real time.

Variety

Refers to unstructured and unprocessed data, such as comments in social media, emails, GPS measurements.

Veracity

refers to the quality and trustworthiness of data

Data analytics

the science of examining raw data, removing excess noise and organizing the data with the purpose of drawing conclusions for decision making

Analytics mindset

a way of thinking that centers on the correct use of data and analysis for decision making

Four steps of an analytic mindset

ask the right questions, extract, transform and load relevant data, apply appropriate data analytic techniques, and interpret and share the results with stakeholders

Specific

be direct and focused to produce a meaningful answer

Measurable

be amenable to data analysis and thus the inputs to answering the question must be measurable with data

Achievable

should be able to be answered and the answer should cause a decision maker to take an action

Relevant

should relate to the objectives of the organization or the situation under consideration

Timely

must have a defined time horizon for answering

Extracting data

understand data needs and the data available, perform the data extraction, verify the data extraction quality and document what you have done

Transforming data

understand the data and the desired outcome, standardize, structure, and clean the data, validate data quality and verify data meets data requirements, document the transaction process

Loading data

store the transformed data in a format and structure acceptable to the receiving software, understand how the new program will interpret data formats, update or create a new data dictionary

Attributes of high quality data

accurate, complete, consistent, timely, valid

Data structuring

the process of changing the organization and relationships among data fields to prepare the data for analysis

Data joining

the process of combining different data sources

Aggregate data

the presentation of data in a summarized form

Data pivoting

rotating data from rows to columns

Data standardization

the process of standardizing these structure and meaning of each data element so it can be analyzed and used in decision making

Data parsing

separating data from a single field into multiple fields

Data concatenation

the combining of data from two or more fields into a single field

Cryptic data values

data items that have no meaning without understanding a coding scheme

Misfielded data values

data values that are correctly formatted but not listed in the correct field

Data consistency

the principle that every value in a field should be stored in the same way

Data cleaning

the process of updating data to be consistent, accurate, and complete

Data deduplication

the process of analyzing data and removing two or more records that contain identical information

Data filtering

the process of removing records or fields of information from a data source

Data imputation

the process of replacing a null or missing value with a substituted value

Data contradiction errors

errors that exist when the same entity is described in two conflicting ways