UMKC Business Intelligence Paper

User Generated

ncngucv

Business Finance

University of Missouri Kansas City

Description

Have 2 things to be done as numbered and explained below

1) Text Analytics, Text Mining, Web Analytics, Web Mining, and Social Analytics

Go to teradatauniversitynetwork.com or locate white papers, Web seminars, and other materials related to text mining.

Go to ibm.com. Find and download at least three white papers on Web analytics.

Create a WORD document in APA format of at least 500 words (1-2 pages) on how these concepts and technologies work and how they can be used to support day-to-day decision making. Make sure you cite the sources above in your paper and include References at the bottom of your paper with the exact URL where you found the sources.


2) Compare and contrast SaaS, PaaS, and IaaS, and provide an example of each(Cloud Computing)

Must be 400 words that cites sources and follows APA formatting.

Explanation & Answer:
400 words
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Attached.

Running head: BUSINESS INTELLIGENCE AND CLOUD COMPUTING

Business Intelligence and Cloud Computing
Student's Name
Institutional Affiliation

1

BUSINESS INTELLIGENCE AND CLOUD COMPUTING

2

Question One: Business Intelligence
Due to extensive clientele, businesses and other organizations receive numerous texts
which are cumbersome to process as result text analytics and text mining have been deployed to
enhance text processing. The two concepts or technologies are used for textual analysis and, more
often, they complement each other (Larson & Chang, 2016). Just to mention, textual analysis is
the analysis of the large volume of texts which are usually unstructured using tools and algorithms
such as Natural Language Processing (NLP), among others. Most text analytics experts a solid
background on computational linguistics and possess management knowledge while text mining
are proficient in data mining statistics

Text analytics emanated from the discipline of computational linguistic and perform text
analysis by the aid of a professional linguist. Important to note, it works by encoding human
understanding into a series of linguistic rules which are of high precision. However, these sets of
regulations have drawbacks; for instance, do not automatically adapt to new situations make it
fragile for use in all environment. While text mining cuts across three disciplines, such as statistics,
data mining, and machine learning. Data mining technology can create models from data, train
those models on how to learn; as a result, they can adapt, thus uncovering insights. These
methodologies can be used to solve textual analysis problems by identifying facts, relationships
and assertions that would otherwise remain buried in the mass of big textual data.

Web analytics are tools that are involved in...


Anonymous
Super useful! Studypool never disappoints.

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Related Tags