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Benefits of quality info

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info is powerful, employees must be able to obtain and analyze to make decisions and successfully collecting can provide tremendous insight into how an org is performing

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Triangle of info

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Granularities (detail fine summary aggregate coarse), Formats (documents presentations spreadsheets database) then levels (individual to enterprise)

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Transactional information -

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

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Analytical information -

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Encompasses all organizational information, and its primary purpose is to support the managerial analysis tasks

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4 traits of info

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Type, Timeliness, quality and governance

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Timeliness

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is an aspect of information that depends on the situation Real-time information - Immediate, up-to-date information Real-time system - Provides real-time information in response to requests

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Quality 5 High quality characteristics

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Accurate, Complete, Consistent, Unique and Timely

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Low quality sources

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

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Costs of low quality

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1.Inability to accurately track customers 2.Difficulty identifying valuable customers 3.Inability to identify selling opportunities 4.Marketing to nonexistent customers 5.Difficulty tracking revenue 6.Inability to build strong customer relationships

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Benefits of good info

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High quality information can significantly improve the chances of making a good decision Good decisions can directly impact an organization's bottom line

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Database -

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

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Database management systems (DBMS) -

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

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Data element -

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Smallest or basic unit of information

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Data model -

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Logical data structures that detail relationships among data elements using graphics or pictures

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Metadata -

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Provides details about data

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Data dictionary -

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

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Entity -

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A person, place, thing, transaction, or event about which information is stored Rows in a table contain entities

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Attribute (field, column) -

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Data elements associated with an entity Columns in each table contain attributes

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Record -

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A collection of related data elements

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Primary key -

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

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Foreign key -

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

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Database advantages

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increased flexibility, increased scalability, increased information integrity increased information security and reduced information redundancy.

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Database advantage Flexibility

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A well-designed database should Handle changes quickly and easily Provide users with different views Have only one physical view Physical view - Deals with the physical storage of information on a storage device Have multiple logical views Logical view - Focuses on how individual users logically access information to meet their own particular business needs

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Database advantage increased scalability (and performance)

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A database must scale to meet increased demand, while maintaining acceptable performance levels Scalability - Refers to how well a system can adapt to increased demands Performance - Measures how quickly a system performs a certain process or transaction

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Database advantage reduces information redundancy

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Databases reduce information redundancy Information redundancy - Duplication of data or storing the same information in multiple places Inconsistency is one of the primary problems with redundant information

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Information integrity -

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measures quality of information

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Integrity constraints -

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rules that help ensure the quality of information Relational integrity constraints Business-critical integrity constraint

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Relational integrity constraints -

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Rules that enforce basic constraints, e.g., they would not allow someone to create an order for a nonexistent customer, or provide a markup percentage that was negative, or order zero pounds of raw materials from a supplier.

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Business-critical integrity constraints

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- Rules that are vital to an organization's success and requires more insight and knowledge than relational integrity constraints. E.g., a supplier of fresh produce to large grocery chains might implement a business-critical integrity constraint stating that no product returns are accepted after 15 days past delivery.

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Password -

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Provides authentication of the user

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Access level -

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Determines who has access to the different types of information

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Access control -

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

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Data-driven website -

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An interactive website kept constantly updated and relevant to the needs of its customers using a database managed by

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Content creator -

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Person responsible for creating original website

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Content editor -

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Person responsible for updating and maintaining website content

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Static information -

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Fixed data incapable of change in the event of a user action

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Dynamic information -

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Data that change based on user action, e.g., website changes information based on user requests such as movie ticket availability, airline prices, or restaurant reservations

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Dynamic catalog -

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An area of website that stores information about products in a database

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Data driven website advantages

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Easy to manage content Easy to store large amounts of data Easy to eliminate human errors

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Benefits of data warehousing

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1. extends the transformation of data into information 2. In the 1990's executives became less concerned with the day-to-day business operations and more concerned with overall business functions 3. Data warehouse provided the ability to support decision making without disrupting the day-to-day operations

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Data warehouse -

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

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data warehouse

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single repository doe decision making purposes

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poor quality of data warehousing in the latter half of last century due to

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Inconsistent data definitions, lack of data standards and poor data quality, inadequate data usefulness, ineffective direct data access

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Extraction, transformation, and loading (ETL) -

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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

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Data mart -

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Contains a subset of data warehouse information

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Differences in databases vs data warehouses and marts

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Databases contain information in a series of two-dimensional tables In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows

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Dimension -

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A particular attribute of information

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Cube -

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Common term for the representation of multidimensional information

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Information cleansing or scrubbing -

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A process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information

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Data mining -

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Process of analyzing data to extract information not offered by the raw data alone

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Data-mining tools -

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use a variety of techniques to find patterns and relationships in large volumes of information through Classification - Assigns records to one of a predetermined set of classes Estimation - Determines value for a variable Affinity grouping - Determines which things to together Clustering - Divides an information set into groups

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Classification -

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Assigns records to one of a predetermined set of classes Estimation - Determines value for a variable

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Estimation -

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Determines value for a variable

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Affinity grouping -

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Determines which things to together

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Clustering -

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Divides an information set into groups

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Data mining is done on structured data -

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Data already in a database or a spreadsheet

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Unstructured data -

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Data does not exist in a fixed location and can include text documents, PDF's, voice messages, emails

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Text mining -

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Analyzes unstructured data to find trends and patterns in words and sentences

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Web mining -

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Analyzes unstructured data associated with websites to identify consumer behavior and website navigation

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3 Common forms of data-mining analysis capabilities include

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Cluster analysis Association detection Statistical analysis

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Cluster analysis -

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A technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible

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Association detection -

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Reveals relationship between variables along with the nature and frequency of the relationships. E.g., "55% of the time, events A and B occurred together," or "80% of the time that items A and B occurred together, they were followed by item C within three days."

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most common form of association detection

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Market basket analysis - Analyzes such items as websites and checkout scanner information to detect customers' buying behavior and predict future behavior

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Statistical analysis -

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Performs such functions as information correlations, distributions, calculations, and variance analysis Forecast - Predictions made on the basis of time-series information Time-series information - Time-stamped information collected at a particular frequency

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problem Data rich Information poor

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Businesses face a data explosion Amount of data generated is doubling every year Some believe it will soon double monthly

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Business Intelligence enables business users to receive data for analysis that is

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Reliable Consistent Understandable Easily manipulated

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Informing -

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Accessing large amounts of data from different management information systems

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Infographics -

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Displays information graphically

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Data visualization -

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Allows users to "see" or visualize data to transform information into a business perspective

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Data visualization tools -

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Analysis techniques such as pie charts, control charts, instruments, maps, time-series graphs, and so on

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