Decision Structures and Information Systems

Course Code: CIS 267

The information systems are being used in many organizations to help effective management of business operations. The information systems facilitate the sharing information and provide transparency in business operations. The business use different information systems within the organizations like communication channels Gmail, IM, and the one drive and drop box for sharing of documents and process focused information systems like quick books for accounting, Supply Chain Management Systems for effective relationship and supplies management of customers and suppliers. With the information systems in the organizations there are various kinds of data that is collected from these systems. The data from the transaction processing systems is usually in the structured format. The data that is stored in the data warehouses is usually semi structured data it holds past and the current data and it has some structure like sales, orders and other such keys. The unstructured data is mainly used for analytical processing. These decision structure have various information systems associated with them and they support the business functions.

Decision Structure

The data is of various forms including structured, semi structured and the unstructured data. The structured data retains the relationship within the database between entities and the data is mainly operational data used in the transaction processing systems. The semi-structured data is not in the format as the structured data but it retains some relationships from the relational database. The data is stored with specific keys that define the properties of the data like in a key value database the key, sales holds the data for the sales for an organization. Data in NoSQL databases or a JSON documents hold the data in the semi-structured format. The unstructured data is collected from all the mediums including satellite images, the internet data like people comments, likes dislikes organizational data. In short, data of any kind emails, media everywhere is part of unstructured data.

The unstructured data is a data that is in many forms like comments, likes, documents, blogs, media and many others. The data that is found anywhere on the internet can be considered an unstructured data. The data that is found online is of great use. The unstructured data contains information that if analyzed properly can add great value to organizations. The data can be used to analyze and predict future trends. The data 70% of the time is in the unstructured format . The retrieval of the data patterns from the unstructured data can be difficult. The pattern determination can be tricky on the data of such large data. The data scientist and data analysts are creating information systems that use the unstructured data to help in decisions making some of the information systems include the decision support system. The business intelligence agents and the data analytics use the text data, machine data and other data to find patterns and trends in the data. Big data platforms are now being used to analyze the data. The Hadoop clusters, NoSQL databases and other are being used to manage large volumes of data.

Unstructured Data and Information Systems

Decisions support systems are designed to help decision-making processes for an organization. The DSS systems are designed to provide specific support to the organization’s semi structured decisions. Some of the commons Decisions Support Systems being used in the organizations include Knowledge Management Systems, Communication driven systems and data driven systems, and others. The systems are built to assist the management in decision-making as the system take input about a certain type of decision-making process like customer dislikes for products of the organization.

The DSS systems provide decipherable information in forms of charts and graphical representation. Data Driven DSS systems like Online Analytical Processing Systems are based on query processing of the data to determine solutions to the complex problems of the organization. The OLAP systems analyze the business data to find the trends for budget forecasting or knowledge discovery. The KMS systems like Feedback Database systems collect data from the users, the customers, and the employees. The data is then analyzed to form decision that incorporate the feedback received. The data can then be used to create better customer care and support.

Information Systems

The three main types of information systems that are currently being used are the Decisions Support Systems, Management Information Systems, Transaction Processing Systems. The three examples of information systems will include OLAP, Inventory Management System and Customer Relationship Management System. These three information systems are being used in many organizations to support various business processes. The CRM systems are used to gather input from the customers and resolve the customer queries. The customers input is taken and fed into the system. The CRM system has a customizable dashboard that allows the managers and business decision makers to help make decisions.

Inventory Management system is system that is an example of transaction processing system that helps in keeping track of the inventory items in the organization. The system mainly comprises of structured data and the inventory transactions are based on relational databases. The OLAP is an online analytical system that analyzes the information within the DDS systems to help find trends and patterns especially sales, marketing and reporting on other various business functions. Data mining concepts are used in the OLAP systems to predict data trends and find user patterns. The system helps the managers and upper level management in figuring out the best decisions for the organization.

Comparison and Contrast of Information Systems

Customer Relationship Management Systems are designed to help the organization better understand their customers. The CRM focuses data are designed to keep track of the data collected from the users. They track sales the customer feedback. The data can easily be visualized in the forms of charts and reports. The data is available to the required personnel’s. This increases productivity and helps in effective decision making. CRM is a scalable solution as it can be expanded based on the increase of the needs of the organization. Data mining can be used on the data collected to find the data trends by analyzing data in real time. The system helps in improving customer relationships and provides critical information for making business specific decisions.

One con that comes into account when talking about the CRM systems is the lack of human element from the business. The data is being collected form the customers via an online portal and the data is often stored in the online storage. With online storage it comes with at threat to the data. The data integrity and confidentiality is imperative in online storages.

Business intelligence systems are being used in many organizations one such system is the OLAP systems. OLAP systems are designed to help in analyzing data and perform multidimensional analysis for decision making. The systems are mainly used by the knowledge workers to help them in making organizational decisions. The OLAP systems are designed to making long term decisions for long term future . The pros of the OLAP systems is to determine how to determine the data patterns as the data in the OLAP systems is unstructured. The data processing for a particular decision takes time and resources. The query processing in OLAP system is time consuming. Data results might carry inaccuracies if proper data algorithms are not used.

The data in the inventory management system are operational data and the data and the system helps in handling the day to day customer requests and the usage demand of the organizations. It helps in managing the supplies of the organization according to the demand. The cons as such in these systems are the common data inaccuracy and human error.

Solutions

The information systems are very important in any organization. They help in making the management of the daily operations more efficient and effective. There are various security risks involved in the information systems but their advantages far outweigh the risks. For information security the organizations need to implement security measures to ensure that the data within the systems is protected there are firewalls and antiviruses to ensure the integrity of the systems and the network. The secure and strong passwords on the systems will ensure that the data within the systems is secured. Access rules can be implemented to ensure that the data within the system is accessed by user’s according to their access rights. The information systems have become a commodity but there are certain security protocols if implemented will ensure certain level of security of the information systems.

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