Managing Knowledge and Data
✳The amount of data increases exponentially.
✳Data are scattered and collected by many individuals using various methods and devices.
✳Data are obtained from multiple sources : internal sources (for example, corporate databases and company documents), personal sources (for example, personal thoughts, opinions, and experiences), and external sources (for example, commerical databases, government reports, and corporate websites). Data also downloaded from the web, in the form of clickstrem data. Clickstrem data are produced by visitors and customers when they visit a website and click on hyperlinks.
✳Data security, quality, and integrity are critical ⇨ Information systems that do not communicate with each other can result in inconsistent data.
✳Data degrade over time⇨ Examples {customers move to a new address} or {employees are hired and fired}.
✳Data rot⇨ Problems with media on which the data are stored.
Data Governance :
Data governance
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Master Data Management
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Master Data
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Transaction Data
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is an approach to managing information across an entire organization. It involves a formal set of business processes and policies that are designed to ensure that the data are collected, handled, and protected in a certain, well-defined fashion.
One strategy for implementing data governance is master data management.
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Is a Process/ method that spans all of an organization's business process and applications. It provides companies with the ability to store, maintain, exchange, and synchronize a consistent, accurate, and timely "single version of the truth" of the company's master data.
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are a set of core data, such as customer, product, employee, vendor, and geographic location that all of the enterprise's information systems.
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are generated and captured by operational systems, describe the activities, or transactions, of the business. In contrast, master data involve multiple transactions and are used to categorize, aggregate, and evaluate the transaction data.
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The Data Approach :
Database are arranged so that one set of the software programs- the Database Management System (DBMS)- provide all users with access to all the data.
DBMSs minimize the problems :
☆ Data redundancy : The same data are stored in many places.
☆ Data isolation : Applications cannot access data associated with other applications.
☆ Data inconsistency : Various versions of the data do not agree.
In addition, DBMSs maximize the following strengths :
☆ Data security : because data are "put in one place" in databases, there is a potential for losing a lot of data at once. Therefore, databases have extremely high security measures in place to deter mistakes and attacks.
☆ Data integrity : Data meet certain constraints, such as no alphabetic characters in a social security number field.
☆ Data independence : Applications and data are not linked to each other, so that all applications are able to access the same data .
The Data Hierarchy :
Byte : A group of eight bits that represents a single character. A byte can be a letter, a number, or a symbol.
Field : A grouping of logically related characters into a word a small group of words or complete number.
Record : A logical grouping or related Fields, such as the student's name, the courses taken, the date, and the grade.
File (table) : A grouping of logically related records.
Designing the Database :
Entity : A person, place, thing, or event about which information is maintained in a record.
Instance : A particular entity within an entity class.
Attribute : each characterise or quality describing a particular entity.
Primary keys : The identifier fielder attribute that uniquely identities recode .
Secondary Key : An identifying information but typically dose not identify the file with complete accuracy.
Entity-Relationship Modeling :
☆Entity-relationship(ER) modeling : the process of designing a database by organizing data entities to be used and identifying the relationship among them.
☆Entity-relationship(ER) diagram : Document that shows data entities and attributes and relationship among them
Entity classes : groups of entities of a certain type.
Identifiers : attributes that are unique to that entity instance.
Type of Relationships :- One-to-One [1:1].
- One-to-Many [1: M].
- Many-to-Many [M:M].
Database Management Systems :
Database Management Systems(DBMS):
Database Management Systems(DBMS): a software that provides users with tools to add, delete, access, and analyze data stored in one location.
e.g : Microsoft Access, & Oracle.
Relational Database Model:
Relational Database Model: based on the concept of two-dimensional tables. A relational database generally is not big table -usually called a flat file- that contains all of the records and attributes.
★Query Languages :
Structured Query Language(SQL): is the most popular query language. It allows users to perform complicated searches (request information) by using relatively simple statements or keywords.
Query By Example(QBE): allows users to fill out a grid or template to construct a simple or description of the data he or she wants.
★Data Dictionary : Collection of definitions of data elements, data characteristics that use the data elements, and individuals, business functions, applications, and reports that use the data elements.
⇨Defines the format necessary to enter the data into the database.
⇨Provides information on each attributes.
⇨Provides information on how often the attribute should be updated.
⇨Metadata : data about the data.
★Normalization : A method for analyzing and reducing a relational database to its most streamlined form for minimum redundancy, maximum data integrity, and best processing performance.
⇨Normalized data is when attributes in the table depend only on the primary key.
Data Warehouses and Data Marts :
☆Data Mart: A low-cost scaled-down version of a data Warehouse designed for the end-user needs in a small organization or in strategic business unit(SBU) or department in large organization.
e.g : Marketing and sale data mart to deal with customer information.
Advantages of data mart :
◆Far less costly than a data warehouse (around R.O.40000)
◇Can be implemented more quickly (around 3 months)
◆More rapid response and easier to learn and navigate.
The basic characteristics of data warehouses and data marts include :
✳ Organized by business dimension or subject⇨data are organized by subject(for example, by customer, product, price, and region )
✳ Use online analytical processing⇨online analytical processing(OLAP) involves the analysis of accumulated data by end users.
✳ Integrated⇨data are collected from multiple systems and are integrated around subjects.
✳ Time variant⇨data warehouses and data marts maintain historical data which can be used for identifying trends, forecasting, and making comparisons over time.
✳ Nonvolatile⇨it means that only IT professionals can change or update the data.
✳ Multidimensional⇨multidimensional structure which consists of more than two dimensions. A common representation for this structure is the data cube.
A Generic Data Warehouse Environment :
The environment for data warehouses and marts includes the following
↖Source systems that provide data to the warehouse or mart.
↘Data integration technology and processes that are needed to prepare the data for use.
↖Different architectures for storing data in an organization's data warehouse or mart.
↘Different tools and applications for the variety of users.
↖Metadata, data quality, and governance processes must be in place to ensure that the warehouse or mart meets its purposes.
The Benefits of Data Warehousing :
- End users can access data quickly and easily via web browsers because they are located in one place.
- End users can conduct extensive analysis with data in ways that may not have been possible before.
- End users have a consolidated view of organizational data.
The Problems with Data Warehousing :
- Very expensive to build and to maintain (around R.O. 400000).
- Incorporating data from obsolete (old) mainframe systems can be difficult and expensive.
- People in one department may be reluctant to share data with other department.
Knowledge Management :
- Explicit Knowledge : deals with more objective, rational, and technical knowledge. In other words is the knowledge that has been codified (documented) in a form that can be distributed to others or transformed into a process or a strategy.
- e.g : (CEPS student's handbook)
- Tacit Knowledge : is the cumulative store of subjective or experiential learning. In other words it is a set of insights, expertise and skills knowledge that people carrybin their hands, but difficult to write down in a document.
Knowledge Management (KM) : A process that helps organization identify, select, organize, disseminate, transfer, and apply information and expertise that are part of the organization's memory and that typically resid within the organization in an unstructured manner.
➡KM is not a technology. It a process supported by IS.
The Advantages of KM :
⇨to develop best practices, the most effective and efficient ways of doing things and to make these practices readily available to a wide range of employees.
⇨KM fosters innovation by encouraging the free flow of ideas, novel approaches and better ways of solving problems.
⇨KM improves customer service by streamlining response time.
⇨KM boost revenue by getting products and services to market faster.
⇨KM enhance employee retention rates by recognizing the value of employees knowledge.
MindTools
Knowledge Management Systems (KMSs) : the use of information technologies to systematize, enhance, and expedite intrafirm and interfirm knowledge management and knowledge sharing.
A functioning KMS follows a cycle that consists of six steps :
- Create knowledge ⇨ knowledge is created as people determine new ways of doing things or develop know-how. Sometimes external knowledge is brought in.
- Capture knowledge ⇨ new knowledge must be identified as valuable and be represented in a reasonable way.
- Refine knowledge ⇨ new knowledge must be placed in a context so that it is actionable. This is where tacit qualities (human insights) must be captured along with explicit facts.
- Store knowledge ⇨ useful knowledge must then be stored in a reasonable format in a knowledge repository o that other members of the organization can access.
- Manage knowledge ⇨ like library, the knowledge must be kept current. To accomplish this objective, knowledge must be reviewed regularly to verify that it is relevant and accurate.
- Disseminate knowledge ⇨ knowledge must be made available in a useful format to anyone in the organization who needs it, anywhere and anytime.
Knowledge Sharing :
Knowledge Sharing tools :
◆Portals.
◇Discussion groups - FAQ.
◆E-mail.
◇Blogs/ wikis.
◆Podcasts.
Resistance to sharing knowledge :
◆Reluctant to show that they do not know.
◇Employee competition.
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