Investing in data mining, data ware housing and data analytics capabilities
When an organization invests in these capabilities, it is able to make an analysis of large databases in which different business decision problems are solved. For example, data mining is some how a statistics extension that contains some artificial intelligence together with twists of machine learning. Just like statistics, these capabilities are not a solution to a business; they just provide an organization with a technology. For example consider a catalogue retailer with a role of deciding the receiver of information concerning a new product. The data mining processing information operation is stored in a data base containing the records of previous customer interactions as well as the features related to the customer that will include; their responses, zip code and even ages. Through use of this information, a model is built of customer behavior through which there can be prediction of which customer would have a high likelihood of responding to a new product. A data warehousing that is comprehensive, in which the operational data is integrated with a customer, the information in the market and supplier mostly has a high probability of resulting in information explosion. The relational technologies are highly likely of navigating data warehouses that is massive although it is not enough to have brute data navigation. There is a need of the new technology in information structuring and prioritization for end user problems that are specific; reap that can be made in data mining (Collen et al, 2004).
When an organization fails to invest in these capabilities, it has less ability in predicting the future behaviors and treads, a failure that results in reducing the ability of a business to make decisions that are knowledge driven and proactive. How else could a business be able to answer the business questions that have in the past been so time consuming in the process of providing for a resolution? This a question that influences this modern technology decision
Applications for electronic data interchange in health care
Value added networks: The activity of the organization in most basic forms resembles that of a regional post office. The transactions are received, the information concerning the “from” and “to” is examined and the transaction routed to the final recipient. Various additional services are provided by the value added networks that includes the documents retransmission, the third party information provision, together with solving the issues that relate to the telecommunications delay. Due to these together with other additional services that are provided by the value added networks, the use of value added networks is usually preferred by the businesses when the internet based protocols are being used by the trading partners. Similar functions of value added networks are performed by the health clearing houses although the additional legal restrictions governing the value added networks also are advantageous with replacement of the certificates in the AS2 transmissions.
Internet/ AS2 (Applicability Statement 2): This protocol is being migrated into by various health organizations in the effort aimed at cost reduction. Through the AS2, the business to business data is communicated by the vendor applications using the HTTP over the internet. Through the AS2, security is provided through the encryption of the data and digital signatories for the transport payload.
Web EDI: Own communication protocols are used by the internet to make sure that there is a secure transmission of the EDI documents. The Hyper Text Transfer Protocol Secure (HTTPS), File Transfer Protocol Secure (FTPS) together with the AS2 are the protocols that are most popular (Kantor & James, 1996).
In knowledge management, there are usually various practices and strategies which an organization uses in the identification, distribution, representation together with enabling insights and experiences adoption. Knowledge is usually comprised in such insights which are either embodied in an individual or in the practices and process of an organization. There are various frameworks through which the knowledge is distinguished. In one of the proposed framework in which the knowledge dimensions are categorized creates a differentiation between knowledge that is explicit and the knowledge that is tacit. The internalized knowledge is represented in the tacit knowledge that may be consciously known by an individual, such as how a particular task can be accomplished. The explicit knowledge on the other side is held by the individuals consciously in their mental focus, through which it can be easily communicated by an individual to the others (Alavi & Leidner, 2001)
Baking- in knowledge management into organizational workflows: Health care organizations are using the strategy of knowledge “baking- in” into the administrative and clinical workflows through which they are able to become knowledge enabled. For example, there is triggering of an alert when a new drug is ordered by a provider for a patient; a drug with negative interaction that had been ordered previously by a physician or already being taken by a patient. Reminders are use to remind a nurse when a patient is due to another particularly prescribed dose at a time that is prescribed. With system of medical record that is electronic, a “crick through” capability is provided by an organization that enables the accessibility to various medical informations.
Alavi, M and LLeidner, D. (2001). Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly 25 (1): 107–136
Collen, C. et al. (2004). Data Warehouse design to support Customer Relationship Management Analyses. Pages, 14- 21
Kantor, M. and James H. (1996). Electronic Data Interchange (EDI). National Institute of Standards and Technology. http://www.itl.nist.gov/fipspubs/fip161-2.htm. Retrieved 2008-05-13.