MIS Chapter 6

The four primary sources of low quality data include

1.Customers intentionally enter inaccurate data to protect their privacy 2.Different entry standards and formats 3.Operators enter abbreviated or erroneous data by accident or to save time 4.Third party and external data contains inconsistencies, inaccuracies, and errors

Primary key

A field (or group of fields) that uniquely identifies a given entity in a table

data warehouse

A logical collection of data - gathered from many different operational databases - that supports business analysis activities and decision-making tasks

Entity

A person, place, thing, transaction, or event about which data is stored

Foreign key

A primary key of one table that appears as an attribute in another table and acts to provide a logical relationship between the two tables

Extraction, transformation, and loading (ETL)

A process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse

Proof-of-work

A requirement to define an expensive computer calculation, also called mining, that needs to be performed in order to create a new group of trustless transactions (blocks) on the distributed ledger or blockchain

Blockchain

A type of distributed ledger technology consisting of data structure blocks that may contain data or programs, with each block holding batches of individual transactions and the results of any executables. Each block contains a time stamp and a link to a previous block.

Database management systems

Allows users to create, read, update, and delete data in a relational database

Data mart

Contains a subset of data warehouse data

Access Control

Determines types of user access, such as read-only access

access level

Determines who has access to the different types of information

Transactional Data

Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks

Analytical data

Encompasses all organizational data, and its primary purpose is to support the performing of managerial analysis tasks

Blockchain

Formed by linking together blocks, data structures containing previous hash and data

Real-time data

Immediate, up-to-date data.

Performance

Measures how quickly a system performs a certain process or transaction

Password

Provides authentication of the user

Real-time system

Provides real-time information in response to requests

Ledger

Records classified and summarized transactional data

Scalability

Refers to how well a system can adapt to increased demands

Data redundancy

The duplication of data or storing the same data in multiple places

Genesis block

The first block created in the blockchain

master data management

The practice of gathering data and ensuring that it is uniform, accurate, consistent, and complete, including such entities as customers, suppliers, products, sales, employees, and other critical entities that are commonly integrated across organizational systems

The four primary traits of the value of data

Type, Timeliness, Quality, Governance

Record

a collection of related data elements

Hash

a function that converts an input of letters and numbers into an encrypted output of a fixed length

Data cleansing or scrubbing

a process that weeks out and fixes or discards inconsistent incorrect, or incomplete data

Data lake

a storage repository that holds a vast amount of raw data in its original format until the business needs it

Proof-of-stake

a way to validate transactions and achieve a distributed consensus

Characteristics of High-quality data

accuracy, completeness, consistency, uniqueness, timeliness

Data cube

common term for the representation of multidimensional information

data dictionary

compiles all of the metadata about the data elements in the data model

data visualization

describes technologies that allow users to see or visualize data to transform information into a business perspective

Metadata

details about data

Dirty data

erroneous or flawed data

Data validation

includes the tests and evaluations used to determine compliance with data governance polices to ensure correctness of data

Data model

logical data structures that detail the relationships among data elements using graphics or pictures

Database

maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)

Data integrity

measures the quality of data

Data visualization tools

move beyond Excel graphs and charts into sophisticated analysis techniques such as controls, instruments, maps, time-series graphs, and more

Distributed computing

process and manages algorithms across many machines in a computing environment

Data governance

refers to the overall management of the availability, usability, integrity, and security of company data

Integrity constraint

rules that help ensure the quality of information

Data element

smallest basic unit of information

data aggregation

the collection of data from various sources for the purpose of data processing

Attribute

the data elements associated with an entity

Business intelligence dashboards

track corporate metrics such as critical success factors and key performance indicators and include advanced capabilities such as interactive controls, allowing users to manipulate data for analysis