Data Resource Management – Structures, Types and Foundation

About Data Resource Management

The process of organizing, storing, and managing data to guarantee its security, accuracy, and accessibility is known as Data Resource Management or DRM. Data Resource Management includes methods, resources, and guidelines for efficiently gathering, preserving, and applying data as a useful organizational resource. Data Resource Management facilitates decision-making, boosts operational effectiveness, and guarantees adherence to privacy and data governance laws.

Fundamental Data Concepts

• Character: The most logical element is a character, which consists of a single alphabetic, numeric, or other symbol. E.g. a, 1, * etc.
• Field: field or data item also known as column. A field consists of a grouping of related character. E.g. First name, salary, city etc.
• Record: A record represents a collection of attributes that describes a single instance of an entity. E.g. person’s payroll which consists of data fields describing attributes such as person’s name, rate of pay etc.
• File: A group of related records is a data file. When it is independent of any other files related to it, a single table may be referred to as a flat file.
• Database: A database is an integrated collection of logically related data elements. A database contains data elements describing entiites and relationship among entities.

Database Structures

The relationship among the many individual data elements stored in databases are based on one of several logical data structures, or models.
DBMS are packages are designed to use a specific data structure to provide end user with quick, easy access to the information stored in database.
The fundamental data structures are:

Hierarchical Model

• It is one of the oldest method for organizing and storing data and is still used by some organization.
• It is organized in a pyramid fashion, like the branches of tree extending downwards.
• It has a parent child relationship where a parent can have more than a children.
• They can be accessed and updated rapidly.
• They are so rigid that adding a new field or record requires that the entire database be redefined.

Network Model

• Represents complex logical relationship and allows many-to-many relationship.
• It is more like graph than tree in structure.
• A network model consists of collection of record which are interrelated to each other with the help of relationship.
• Children can have multiple parents and parents can have multiple children

E-R Model

• An entity- relationship model is a systematic way of describing and defining a business process.
• The E-R model is a way of graphically representing the logical relationships of entities in order to create database.
• The data modelers prepares the ER diagram and is verified with the functional domain experts to ensure that all the requirements are properly incorporated in the conceptual design.
• We can easily map ER diagram to a relational schema.
• The basic construct of ER model are entity, attributes and relationship.

Definitions:

Entities: An entity is thing or object in the real world that is distinguished from all other objects. An entity may be concrete such as person, book or abstract such as account, loan etc.

Attributes: An entity is represented by a set of attributes. It corresponds to field in a table. For each attribute there is a set of permitted values called the domain or value set of the attribute.

Relationship: A relationship describes an association among entities. The relationship may be one to one, one to many and many to many.

Relationship between Entities

• One to one (1:1) : one instance of an entity is associated with one other instance of another entity (B). Eg. A student is identified by unique student id
• One to Many (1:N): one instance of an entity A is associated many instances of entity B. A company with many employees.
• Many to many (N:N): one instance of entity A is associated with many instance of entity B and one instance of entity B is associated with many instance of entity A. eg. A project is associated with many employees and a employee is associated with many projects.

Relational Model

• Relational data model is the primary data model, which is used widely around the world for data storage and processing. This model is simple and it has all the properties and capabilities required to process data with storage efficiency.
• Concepts
• Tables − In relational data model, relations are saved in the format of Tables. This format stores the relation among entities. A table has rows and columns, where rows represents records and columns represent the attributes.
• Tuple − A single row of a table, which contains a single record for that relation is called a tuple.
• Relation instance − A finite set of tuples in the relational database system represents relation instance. Relation instances do not have duplicate tuples.
• Relation schema − A relation schema describes the relation name (table name), attributes, and their names.
• Relation key − Each row has one or more attributes, known as relation key, which can identify the row in the relation (table) uniquely.
• Attribute domain − Every attribute has some pre-defined value scope, known as attribute domain.

Database Development

The process of planning, building, and maintaining an organized system to effectively store, manage, and retrieve data is known as database development. There are multiple steps involved, such as:

• Finding users, data needs, and business objectives is known as requirement analysis.
• Data modeling is the process of creating a logical framework to specify relationships and data flow, such as Entity-Relationship (ER) diagrams.
• Developing a physical framework and specifying tables, schemas, keys, and relationships is known as database design.
• Implementation: Building the database with a Database Management System (DBMS) such as MySQL, Oracle, or MongoDB.
• Testing: Verifying performance, security, and data integrity.
• Deployment and Maintenance: Putting the database into use and keeping it updated and optimized on a regular basis.
• Database construction guarantees corporate process support, efficient retrieval, and well-organized data storage.

Types of Databases

Development in Information technology and its business application have resulted in the evolution of several major types of databases.
The major conceptual categories of databases may be found in many organizations.

Operational Database

• It stores data needed to support the business process and operation of a company.
• They are also known as subject database, transaction database and production databases.
• E.g. are customer database, human resource database, inventory database, and other database containing data generated by business operations.

Distributed Databases

• Many organization replicate and distribute database copies or parts of databases to network server at a variety of sites.
• The distributed database resides on network servers on world wide web, corporate intranets and extranets, or on any company network.
• The primary aim of distributed database is protection of data and meet the storage requirements.
• The primary challenge is to maintain data accuracy and integrity.
• The updating of data in distributed system can be done in two ways replication and duplication.

External Database

• Access to information from external databases is available from commercial online services from many sources on the world wide web.
• Websites provides an endless variety of hyperlinked pages of multimedia documents in hypermedia database to access.
• One can view or download abstract or complete copies of hundreds of newspaper, magazines, newsletter, research paper, and other published material.
• Using google and other search engine is an example for use of external database.

Hypermedia Databases

• A website stores information in hypermedia database consisting of hyperlinked pages of multimedia.
• From data management point of view the set of interconnected multimedia pages on the web site is a database of interrelated hypermedia page elements, rather than interrelated data records.
• The web server software acts as a database management system to manage the transfer of hypermedia files for downloading by the multimedia plug-in of web browser.

Technical Foundation of Database Management

The fundamental ideas, resources, and technologies that make it possible to store, retrieve, and manipulate data effectively make up the of Technical Foundation of Database Management. Here are the essential elements:

Database Management Systems (DBMS)

• Software that makes database construction, administration, and utilization easier.
• Types:
• SQL is used by relational database management systems (RDBMS) (e.g., PostgreSQL, SQL Server) to handle structured data.
• Unstructured or semi-structured data is handled by NoSQL DBMSs (such as CouchDB and Neo4j).
• In-memory database management systems, like Redis, store data in RAM to maximize speed.

Query Languages

• Database interaction tools for retrieving and modifying data.
• The standard for RDBMSs is Structured Query Language (SQL).
• Languages for NoSQL queries: varied according to the database (e.g., MongoDB’s JSON queries).

Data Storage and Indexing

• Data storage refers to the actual physical arrangement of data on disk or in memory.
• Indexing: Techniques like hash indexes and B-trees that expedite data retrieval.

Transaction Management

• Guarantees the dependability and consistency of data when it is being accessed concurrently.
• ACID (Atomicity, Consistency, Isolation, Durability) is a key principle.

Backup and Recovery

• Procedures to stop data loss and recover data after an error.
• Include differential, incremental, and full backups.

Security

• User roles and permissions make up access control.
• Encryption: Safeguards private information.
• Authentication: Confirms the identities of users using biometrics and passwords.

Scalability and Performance Optimization

• Increasing a single server’s capacity is known as vertical scaling.
• Increasing the number of servers to spread the load is known as horizontal scaling.
• Optimizing database settings, queries, and indexes is known as performance tuning.

Data Warehouses

• The data warehouse stores data that have been extracted from the various operational, external and other database of an organization.
•  They store current and historical data and are used for creating analytical reports for knowledge workers throughout the enterprise. Examples of reports could range from annual and quarterly comparisons and trends to detailed daily sales analysis.
• The data stored in the warehouse is uploaded from the operational systems (such as marketing, sales, etc.)
• Data warehouse may be divided into data marts, which holds subsets of data from the warehouse that focus on specific aspect of company such as a department or a business process.
• The data from various operational and external database are captured, cleaned , transformed into data that can be better used for analysis.
• The data in data warehouse is static due to complex pattern or historical trends that might be otherwise go unnoticed with dynamic data that change constantly.

Data Mining

• In data mining the data warehouse are analyzed to reveal hidden patterns and trends in historical business activity.
• Data mining can discover new correlations, patterns, and trends in vast amounts of business data stored in data warehouse.
• This analysis can be used to help managers make decisions about strategic changes in business operation to gain competitive advantages in the market place.

Decision Support in Business

• To succeed in business today, companies need information system that can support the diverse information and decision-making needs of their managers and business professionals.
• The type of information required by decision makers in a company is directly related to the level of management decision making and the amount of structure in the decision situations they face.
• The level of managerial decision making that must be supported by information technology in successful organization are:

Strategic Management (SM)

• Board of directors executive committee of the CEO and top executives develop overall organizational goals, policies and objectives as part of strategic planning process.
• They also monitor the strategic performance of the organization and its overall direction in political, economic and competitive business environment.

Tactical Management (TM)

• Business professionals in self directed teams as well as business unit managers develop short and medium range plans, schedules and budgets and specify the policies, procedures and business objectives for their subunits of the company.
• They also allocate resource and monitor the performance of their organizational subunits, including departments, division, process teams, project teams and other workgroups.

Operational Management

• The members of self directed teams or operating managers develop short range plans such as weekly production schedules.
• They directs the use of resources and the performance of tasks according to procedures and within budgets and schedules they establish for the team and other workgroups of the organization.

Information Quality

• The characteristics of information products makes them valuable and useful to anyone.
• People need information of high quality that is information products whose characteristics, attributes or qualities make the information more valuable to them.
• Information should be having three dimension of time, content and form.

Time Dimension

• The important of information is valuable within the given time frame. It is summarized as:
• Timeliness: provided when needed.
• Concurrency: Up to date when provided.
• Frequency: As often as needed.
• Time Period: about past, present and future time periods.

Content Dimensions

• It is important to have complete content of any information. It is summarized as:
• Accuracy: free from errors
• Relevance: related to need of a specific recipient
• Completeness: All information necessary should be provided
• Conciseness: only necessary information
• Scope: can have broad or narrow scope
• Performance: reveal performance by measuring activities accomplished, progress made and resources accumulated.

Form dimension

• The structure and format of information is equally important. It is summarized as:
• Clarity: Easy to understand
• Detail: can be provided in detail or summary form
• Order: predetermined sequence
• Presentation: presented in narrative, numeric, graphic or other forms
• Media: form of printed paper documents, video display or other media.

Decision Structure

• Decision made at the operational management level tend to be more structured, those at the tactical level are more semi-structured and those at the strategic level are more unstructured.
• Structured decision involves situation in which the procedure to follow, when a decision is needed can be specified in advance. E.g. Inventory reorder decision
• Unstructured decision involves decision situation in which it is not possible to specify in advance the most of the decision procedure to follow. Long term strategic decision are unstructured.
• Some business decision procedure can be pre specified but not enough to lead to a definite recommended decision. E.g. decision involved in starting new line of ecommerce service.
• Information system must be designed to produce variety of information products to meet the changing needs of decision makers throughout an organization.
• Decision at strategic level may look decision support system to support their more unstructured planning and policymaking responsibilities.
• Decision at operational level may depend on MIS to supply more pre-specified internal reports that support their more structured responsibilities in day to day operations.

Decision Support Trends

• Using information system to support business decision making have been one of the primary thrust of the business use of information technology.
• Traditional managerial focus originating in classic management information system, decision support system and executive information system expanded during 90’s.
• The trend expanded with the dramatic growth of internet, intranet and extranet. The E-business and E-commerce also expanded the information and decision support use.
• Business Intelligence(BI) is rapidly becoming the mainstream idea for business decision making in the modern organization.
• Business are responding with a variety of personalized and Proactive web based analytical technique to support the decision making.

Frequently Asked Questions (FAQ)

Related Contents

Telecommunication and Network

Management Information System (MIS)