Data bases and data warehouse

Introduction:

Information resources are central to any organization’s success. And these resources are growing at an astounding rate. Data stored in digital format are multiplying everywhere on a vast array of physical media, ranging from the organization’s own computers to hosts that might be located anywhere on the planet. People understand that some information is powerful and valuable, but far more is useless junk that should be tossed.  What strategy are there to manage information resources so that what is important is secure, organized, and easily accessible to managers, employees, customers, suppliers, and other stakeholders?

The Nature of Information Resources: 

Information resources can be described as Structured information: This is reasonably ordered; in that it can be broken down into component parts and organized into hierarchies. Unstructured Information: This information has no inherent structure or order, and the parts can’t be easily linked together, except perhaps by stuffing them in a manila folder or box. It is more difficult to break down, categorize, organize, and query. Semi Structured Information: Information that shows at least some structure but don’t have the strong structure, enforced by advance planning, to clearly define entities and their relationships, and they lack controls about completeness and formatting. Meta Data: This is data about data, and it clarifies the nature of the information. For structured information, metadata describes the definitions of each of the fields, tables, and their relationships

Quality of Information: Not all information has high quality, as anyone who surfs the net knows. Here are the most important characteristics that affect quality: Accuracy, Precision, Completeness, Timeliness, Bias, Duplication.

Developing and Managing a Rational Data Base: Managing information with the help of computers relies on the use of Tables, Records, and Fields, and each field should have a data definition.

Rise and fall of file processing system: Early attempts to manage digital information resources used file processing systems, in which each department maintained its own records. Although they were very valuable, file processing systems had several disadvantages, including data duplication, lack of integration among departmental systems, inconsistent data definitions across departments, and data dependence etc

Data Bases: The database approach is an integrated collection of information that is logically related, stored in such a way as to minimize duplication, facilitate rapid retrieval, addresses these disadvantages and creates a shared resource with minimal redundancy. Database management software (DBMS) is used to create and manage the database. This software provides tools for ensuring security, replication, retrieval, and other administrative and housekeeping tasks. Data Base Architecture: Several different database architectures have been developed such as One to one (1:1), One to Many (1:M), Many to Many (M:M). However, the Rational database is the most widely used. It organizes information into tables of records that are related to one another by linking a field in one table to a field in another table with matching data. The approach separates the data from the paths to retrieve them, thus making the database less dependent on the hardware and its particular operating system. Other common relational DBMSs include Microsoft SQL, Server, Oracle, and MySQL, XML data types, as well as spatial information and mapping coordinates.

Developing and Maintaining a Rational Data Base: 

The first step begins with planning the Data model: To identify the entities (table), their attributes(fields), and their relationships. Assign a Primary key: Primary keys ensure that each record in a table is unique. Next, Normalization: refine the entities and their relationships to minimize duplication of information in the tables. Relationships and Foreign keys: This help establish relationships among tables. Complex relationship: This helps to Normalize uncover many-to-many relationships as well. Performance Tuning and Scalability The database needs tuning for optimal performance, and the tuning process takes into account the way the end users access the data. Scalability refers to a system’s ability to handle rapidly increasing demand. Integrity, Security, and Recovery: The DBA manages the rules that help ensure the integrity of the data. Documentation: documented using a database schema (A graphic that documents the data model and shows the tables, attributes, keys, and logical relationships for a database).

Accessing the Data Bases and Retrieving Information: Most databases are accessed through application software, which serves as a user-friendly gateway to the underlying tables. The database management system (DBMS) provides tools for monitoring and maintaining the database in areas such as documentation, performance tuning, disaster recovery, and security. Information is retrieved from the database using query languages, such as Structured query language (SQL). Other Access and Retrieval Tools are the Interactive voice response (IVR), Natural language query system.

Data Warehouse and Big Data: The data warehouse draws information from multiple sources to create one information storehouse that can be used for reporting, analysis, and research. Sources can be both internal and external. Extract, transform, and load (ETL) are the three steps used to create the warehouse, which is refreshed with updated information daily or more often. Big Data refers to immense data collections that feature the three “Vs” (high volume, velocity, and variety). Relational databases and data warehouses may be used to analyze these collections and conduct data mining, along with newer technologies such as NoSQL databases and software that supports distributed processing across thousands of computers.

Multiple Data Bases and the Challenge of Integration: As organizations grow and expand, or when two companies merge, they often wind up with many databases rather than a single integrated one. Employees also launch their own shadow systems (these are smaller databases developed by individuals or departments that focus on their creator’s specific information requirements) to manage just the information they need, without the help or oversight of central IT staff. Integration strategies, such as master data management, are needed to coordinate how data are entered and provide enterprise-wide summaries for strategic planning. A data steward helps maintain data consistency across the organization.

The Challenges of Information Management: Enterprise information management is not just about technology. It involves a variety of challenges that touch on the human element. Data ownership issues arise, for example, because data have to be shared by all the stakeholders in the organization. Ownership issues also play a major role for databases without boundaries, such as Craigslist, in which most records are entered by people outside the enterprise. Leadership, cooperation, negotiation, and a well-designed database are all needed to balance all the stakeholders’ requirements.