How we can differentiate data driven DSS and model driven DSS?

Asked By: Britt Overmohle | Last Updated: 22nd February, 2020
Category: technology and computing data storage and warehousing
4.9/5 (2,443 Views . 26 Votes)
Both datadriven DSS and Model driven DSS are tools for information analysis. However, Model driven helps users understand the impact of decisions by providing what-if analysis whereas data driven usually analyzes developments in the past to help user make their decision.

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Also, what is a model driven DSS?

Model-driven DSS include computerized systems that use accounting and financial models, representational models, and/or optimization models to assist in decision-making. Model-driven DSS use data and parameters provided by decision-makers to help in analyzing a situation, but such systems are not data intensive.

Also, what are the major types of models used in DSS? File drawer models are very simple models that merely present data in an organized format. Analytical models take the data and process it using a computational proves, to provide estimates the outcome of a decision.

Correspondingly, what is a data driven DSS?

Data-driven DSS is a type of DSS that emphasizes access to and manipulation of a time-series of internal company data and sometimes external data. A Data Warehouse is a database designed to support decision making in organizations.

Is the enterprise data warehouse part of a data driven decision support system?

No, a data warehouse is not a Decision Support System. A data warehouse is however usually the "driver" and dominant component for a Data-driven DSS. A data warehouse is an organized collection of large amounts of structured data. It is a database designed and intended to support decision making in organizations.

24 Related Question Answers Found

What are different types of DSS?

These can be categorized into five types: communications driven DSS, data driven DSS, document driven DSS, knowledge driven DSS and model driven DSS. A communication driven DSS supports more than one person working on a shared task.

What are the functions of DSS?

KEY DSS FUNCTIONS
Gupta and Harris observed that DSS is predicated on the effective performance of three functions: information management, data quantification, and model manipulation. "Information management refers to the storage, retrieval, and reporting of information in a structured format convenient to the user.

What is DSS and its characteristics?

DSS Characteristics :? Facilitation : DSS facilitate and support specific decision- making activities and/or decision processes. ? Interaction : DSS are computer-based systems designed for interactive use by decision makers or staff users who control the sequence of interaction and the operations performed.

What are the common DSS analysis techniques?

The main techniques that are mostly used in data-based DSS for analyzing the data are online analytical processing (OLAP) and data mining. Online Analytical Processing (OLAP): It is based on queries and can provide fast answers to complex business requests.

How do DSS help in tax planning?


The Tax DSS provides the capability to analyze trends in the collected revenue from various perspectives. The common perspectives available are Time, Business Type, Tax Type, Tax Period, and Geographical Location. The system accesses tax revenue assessed data based on specific criteria.

What is knowledge driven DSS?

About Knowledge-Driven DSS
These DSS are person-computer systems with specialized problem-solving expertise. The "expertise" consists of knowledge about a particular domain, understanding of problems within that domain, and "skill" at solving some of these problems. A related concept is Data Mining.

What are the most common models in a DSS software system?

The most common models in a DSS software system are (a)Libraries of statistical models(b)Statistical graphs from multiple information sources(c)Optimization models(d)OLAP tools (e)OLTP tools.

Why is it so important to include a model in a DSS?

Concisely DSS helps manager's to take decisions in complex situations. Better decisions means improving information provided. Decision models should be adopted in business field to improve working. Management decisions modeling involves the management and optimization models (Evolution).

Why is decision support important?

The goal of decision support is to create and help us use better information. There is a pressing need to use technology to help make important decisions better. Effective decision support provides managers more independence to retrieve and analyze data and documents to obtain facts and results, as they need them.

What is meant by OLAP?


OLAP (Online Analytical Processing) is the technology behind many Business Intelligence (BI) applications. OLAP is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical calculations, and predictive “what if” scenario (budget, forecast) planning.

What are the three types of clinical decision support systems?

Examples of various types of clinical decision support systems include diagnostic support such as MYCIN and QMR, alerts and reminders based on the Arden Syntax, and patient management systems that use computer representations of patient care guidelines.

How do companies use data to make decisions?

What Is Data Driven Decision Making? Data driven decision making (DDDM) is a process that involves collecting data based on measurable goals or KPIs, analyzing patterns and facts from these insights, and utilizing them to develop strategies and activities that benefit the business in a number of areas.

What is meant by decision support system?

A decision support system (DSS) is a computer-based application that collects, organizes and analyzes business data to facilitate quality business decision-making for management, operations and planning. DSS analysis helps companies to identify and solve problems, and make decisions.

How does transaction processing system work?

A Transaction Processing System (TPS) is a type of information system that collects, stores, modifies and retrieves the data transactions of an enterprise. Rather than allowing the user to run arbitrary programs as time-sharing, transaction processing allows only predefined, structured transactions.

Why is it important to understand DSS and AI as part of business?


Information technology provides a business with a Decision support system (DSS) and Artificial intelligence (AI) system, the combination of these IT systems helps you create information through online analytical process (OLAP) to facilitate decision making tasks that might require significant effort and analysis.

How DSS is used in business?

A decision support system (DSS) is a computerized program used to support determinations, judgments, and courses of action in an organization or a business. A DSS sifts through and analyzes massive amounts of data, compiling comprehensive information that can be used to solve problems and in decision-making.

How Decision Support System DSS helps in taking right decision explain with example?

DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, and personal knowledge, or business models to identify and solve problems and make decisions.