Ch 5 : Managing Knowledge and Data

                                        

         

Difficulties in Managing Data

            1) Amount of data increases exponentially

                               1.2 zettabytes

          2) Data come from many sources

                   Internal sources:corporate data, company document

                    External sources:commercial database, government report

                    Personal sources:opinions, experiences

http://searchcrm.techtarget.com/definition/clickstream-analysis

3) Data degrades overtime 

     customers move to a new address employees are hired and fired 

         4 )Data rot  problems with media on which the data are stored 

 Managing Data

   Data Governance:  an approach to managing data across an entire organization.

Formal sets of policies that are designed to ensure that the data are collected, handled and protected in a certain, well-defined fashion.

Master data management: a process/method that provides an organizations with the ability to store, maintain, exchange and synchronize a consistent, accurate and timely ‘single version of the truth’ for the organization's core 

Master data: a set of core data [customer, employee, vendor, geographic location] that span all enterprise information systems.

Transaction data: data that are generated and captured by operational systems 

                                  


    Database

 A database is an organized collection of data. The data is typically organized to model aspects of reality in a way that supports processes requiring information. For example, modelling the availability of rooms in hotels in a way that supports finding a hotel with vacancies

• Data redundancy: The same data are stored in many places
• Data isolation: Applications cannot access data associated with other                                                applications
• Data inconsistency: Various copies of the data do not agree

Database Management Systems

A database management system (DBMS) is a collection of programs that enables you to store, modify, and extract information from a database. There are many different types of DBMS, ranging from small systems that run on personal computers to huge systems that run on mainframes. The following are examples of database applications:

computerized library systems

automated teller machines

flight reservation systems

computerized parts inventory systems

                              

     Data Hierarchy



                                                 
     

  Bit: a binary digit, or a “0” or a “1” - The smallest unit of data     a computer can handle

  Byte: eight bits and represents a single character (e.g., a            letter,number or symbol

  Field: is a group of related characters (e.g., student’s name,        age,  mobile number)

  Record: a group of logically related fields (e.g., student in               a university database)

  File (or table): a group of  related records

  Database: a group of  related files.          

Designing the Database

      Database design is the process of producing a detailed data model of a database. This logical data model contains all the needed logical and physical design choices and physical storage parameters needed to generate a design in a data definition language, which can then be used to create a database. A fully attributed data model contains detailed attributes for each entity

        Entity: a person, place, thing, or event about which information is maintained.                 [A record generally describes an entity]

Attribute: a particular characteristic of a particular entity

Primary key (Key field): a field that uniquely identifies a record, so that it can                                       be retrieved and updated

Entity-Relationship Modeling

One-to-One [1:1]

One-to-Many [1:M]

 Many-to-Many [M:M]

                            

                           

   Data Warehouses and Data Mart

   Data Warehouse:

• Holds multiple subject areas
• Holds very detailed information
• Works to integrate all data sources
• Does not necessarily use a dimensional model but feeds dimensional models.

 Data Mart

• Often holds only one subject area- for example, Finance, or Sales
• May hold more summarized data (although many hold full detail)
• Concentrates on integrating information from a given subject area or set of source systems
• Is built focused on a dimensional model using a star schema

                                      

                                 

Knowledge Management

Knowledge is a familiarity, awareness or understanding of someone or something, such as facts, information, descriptions, or skills, which is acquired through experience or education by perceiving, discovering, or learning.

Explicit knowledge: codified (documented) in a form that can be distributed to others                                   (CEPS student’s handbook)

Tacit knowledge: a set of  insights, expertise and skills Knowledge that people carry

                                 in their heads,but difficult to write down in a document  

      

Knowledge management (KM) is the process of capturing, developing, sharing, and effectively using organisational knowledge. It refers to a multi-disciplined approach to achieving organisational objectives by making the best use of knowledge