# Managing Data
· The difficulties of managing data:
o The amount of data increases exponentially with time.
o Data are scattered and collected by many individuals using various methods and devices.
o Data come from multiple sources, such as: internal resources, personal resources and external resources.
o Data are subject to data rot. (Data rot refers to problems with media on which the data are stored.
o Data security, quality and integrity are critical.
ü As a result: Organizations are using database and data warehouse to manage their data more efficiently and effectively.
· The data life cycle:
1) Selected data from the organization's database are processed to fit the format of a data warehouse or data mart.
2) Users access the data the data in the warehouse or data mart for analysis.
3) The analysis is performed with data analysis tools.
4) These activities generate knowledge that can be used to support decision making.
# The Database Approach:
· Database management system (DBMS) provides all users with access to all the data.
· DBMSs minimize the following problems:
o Data redundancy: The same data are stored in many places.
o Data isolation: Applications cannot access data associated with other applications.
o Data inconsistency: Various copies of the data do not agree.
· DBMSs maximize the following issues:
o Data security: Databases have extremely high security measures in place to deter mistakes and attacks.
o Data integrity: Data meet certain constrains, such as no alphabetic characters in a social security number field.
o Data independence: Applications and data are independent of one another. Applications and data are not linked to each other, meaning that applications are able to access the same data.
· The Data Hierarchy:
o A bit is a binary digit, or a “0” or a “1”.
o A byte is eight bits and represents a single character (e.g., a letter, number or symbol).
o A field is a group of logically related characters (e.g., a word, small group of words, or identification number).
o A record is a group of logically related fields (e.g., student in a university database).
o A file is a group of logically related records.
o A database is a group of logically related files.
· Designing the Database:
o The data model is a diagram that represents the entities in the database and their relationships.
ü An entity is a person, place, thing, or event about which information is maintained.
ü A record generally describes an entity. (Table)
ü An attribute is a particular characteristic or quality of a particular entity. (Field = Column)
ü The primary key is a field that uniquely identifies a record. (Identifier)
ü Secondary keys are other field that have some identifying information but typically do not identify the file with complete accuracy.
· Entity Relationship Modeling:
o Database designers plan the database design in a process called entity-relationship (ER) modeling.
o ER diagrams consist of entities, attributes and relationships:
ü Entity classes: are groups of entities of a certain type
ü Instance: of an entity class is the representation of a particular entity.
ü Identifiers: which are attributes that are unique to that entity instance.
4.3: Database Management Systems:
· A database management system is a set of programs that provide users with tools to add, delete, access, and analyze data stored in one location.
· The relational database model: is based on the concept of two-dimensional tables:
o Structured query language (SQL), allows users to perform complicated searches by using relatively simple statements or keywords.
o Query by example (QBE), allows users to fill out a grid or template to construct a sample or description of the data he or she wants.
· Normalization is a method for analyzing and reducing a relational database to its most streamlined form for:
o Minimum redundancy.
o Maximum data integrity.
o Best processing performance.
o Normalized data is when attributes in the table depend only on the primary key.
· Non - Normalization: all the data are placed in one table.
# Data Warehousing:
· A data warehouse is a repository of historical data organized by subject support decision makers in the organization.
· Data warehouses are multidimensional, with 3 dimensions (customer, product & time).
· Data warehouses are historical: in data warehouses can be used for identifying trends, forecasting, and making comparisons over time.
· Data warehouses use online analytical processing (OLAP): involves the analysis of accumulated data by end users (usually in a data warehouse).
In contrast to OLAP, online transaction processing (OLTP) typically involves a database, where data from business transactions are processed online as soon as they occur.
· Benefits of Data warehousing:
o End users can access data quickly and easily via Web browsers because they are located in one place.
o End users can conduct extensive analysis with data in ways that may not have been possible before.
o End users have a consolidated view of organizational data.
· Data Mart:
o Is a small data warehouse, designed for the end-user needs in a strategic business unit (SBU) or a department.
# Data Governance:
· Data governance is an approach to managing data and information across an entire organization.
· Master data management is a method that organizations use in data governance.
· Master data are a set of core data that span all enterprise information systems.
# Knowledge Management:
· Knowledge management is a process that helps organizations manipulate important knowledge that is part of the organization’s memory, usually in an unstructured format.
· Knowledge that is contextual, relevant, and actionable.
· Intellectual capital is another term often used for knowledge.
· Types of Knowledge Management:
o Explicit knowledge: objective, rational, technical knowledge that has been documented.
§ Examples: policies, procedural guides, reports, products, strategies, goals, core competencies
o Tacit knowledge: cumulative store of subjective or experiential learning.
§ Examples: experiences, insights, expertise, know-how, trade secrets, understanding, skill sets, and learning.
· Knowledge Management system Cycle:
o Create knowledge
o Capture knowledge
o Refine knowledge
o Store knowledge
o Manage knowledge
o Disseminate knowledge
Thanks for the really interesting infrmation
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