From ?Delivering Business Analytics?

Description
Please thoroughly and concisely answer both questions for this order.

1. Of the four types of business analytics covered in Attached topic notes (W06T2_Types of Analytics.doc), pick one and apply it to your organization. What is the purpose of the type of business analytics you selected and how might it be applied in your organization?

2. Please watch this Film “Moneyball” and Identify the specific type of business analytics that was used in the film, then describe what other types of business analytics could have been applied in the movie and for what benefit?

Here is the link:
FILM: Moneyball
The assignment is to watch the film “Moneyball”.
http://www.imdb.com/title/tt1210166/

Please read attached notes for reference. 1 page – 300 words are required. Please add citations and references page number for each citation in the paragraph. Example: (author name, year, p. xx). It?s required APA standard format. Prepare answer from your thoughts. This is master level degree so, the answer should be very clear and concise.

WEEK SIX
TOPIC 2: Types of Analytics

Contents
1. Data Analytics
2. Text Analytics
3. Business Analytics
4. Other Types of Analytics

As we have already discussed, analytics are ?the quantifiable informational inputs that use past data to identify possible trends that may provide valuable insight for future action?.1 But ?analytics? is a broad term, and there are several different types of analytics, depending on the data being analyzed, the specific application of the analytics, and the purpose of the analysis.

Below are the definitions and general applications of the most common types of analytics.

1. Data Analytics
Data analytics is the science of examining raw data with the purpose of drawing conclusions about that information.2 The category of ?data analytics? is the umbrella under which most types of analytics fall.

2. Text Analytics
Text analytics is often used interchangeably with the term ?text mining,? where both terms refer to the extraction of data or information from text.3 It is used for several purposes, such as summarization (trying to find the key content across a larger body of information or a single document), sentiment analysis (what is the nature of commentary on an issue), explicative (what is driving that commentary), investigative (what are the particular cases of a specific issue) and classification (what subject or what key content pieces does the text talk about).4

3. Business Analytics
Business analytics can be broken out into several different types: descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
Three of these types were covered in the Business Intelligence, Analytics and Decision Making course. The following charts will look familiar to those who have taken that course:

The chart above explains the purpose of each type of business analytics, while the chart below shows the hierarchy of value attached to each type.

Below are the definitions for the three types above, as well as another type, diagnostic analytics:

A. Descriptive Analytics:
Descriptive analytics are about the past: What happened?
This type of analytics helps organizations understand what happened in the past, whether it was 5 minutes ago or 10 years ago. Understanding and learning from the past can influence and/or instruct future action.

B. Diagnostic Analytics:
Diagnostic analytics are about the past: Why did it happen?
This type of analytics helps organizations understand why something in the past happened, so they can take action to a. ensure that it continues to happen, b. ensure that it doesn?t happen again, c. ensure that it happens less or more, or d. ensure that something new can happen.

C. Predictive Analytics:
Predictive analytics are about the future: What will happen?
This type of analytics helps organizations understand what can potentially happen in the future, by providing an estimation of the likelihood of a particular outcome. Predictive analytics can also help to identify future opportunities or risks.

D. Prescriptive Analytics:
Prescriptive analytics are about the future: How can we make it happen?
This type of analytics gives advice to an organization by providing a ?prescription? for future action, based on what is predicted to happen. Prescriptive analytics not only foresee what will happen and when, but also why it will happen, then it provides recommendations around what actions to take in order to leverage that information in the future.

So you can see that there is an order and progression with these four types of business analytics that can be used in succession or individually, depending on the business problem.

If used together in this natural progression, they form a cycle of analytics that can comprehensively and effectively utilize past data to guide future decisions and action. This can be a tremendously powerful strategic tool in the competitive landscape of today?s business environment.

4. Other Types of Analytics:
Below are some other types of analytics that have specific purposes and applications.

Social Analytics:
Also called ?social media analytics?, this type refers to the practice of gathering data from blogs and social media websites and analyzing that data to make business decisions. The most common use of social media analytics is to mine customer sentiment in order to support marketing and customer service activities.5

Web Analytics:
Web analytics refers to the process of analyzing the behavior of visitors to a particular web site. The use of web analytics is helps to a business to attract more visitors, retain or attract new customers for goods or services, and/or to increase the dollar volume each customer spends.6

Marketing Analytics:
Marketing analytics refers to the process that organizations can use to measure the effectiveness of marketing and advertising campaigns.

There are additional types of analytics as well, such as: risk analytics, fraud analytics, CRM analytics, loyalty analytics, operations analytics, HR analytics (also called workforce analytics), etc. As data growth continues to increase in the coming years, so will the types of analytics designed to analyze the data.

References:
1 Bateman, Leanne. Topic Note 1 from Week 6: W06T1_What are Analytics.doc, 2014.
2 http://searchdatamanagement.techtarget.com/definition/data-analytics
3 http://www.decisionanalyst.com/Database/TextMining.dai
4 http://www.gartner.com/it-glossary/text-analytics
5 http://searchbusinessanalytics.techtarget.com/definition/social-media-analytics
6 http://searchcrm.techtarget.com/definition/Web-analytics

Images:
Page 1: Image courtesy of http://b-i.forbesimg.com/louiscolumbus/files/2013/10/Analytics.png
Page 2: Image courtesy of Delen, Dursun and Demirkan, Haluk, ?Decision Support Systems, Data, information and analytics as services,? from Elsevier, published online May 29, 2012.
Page 2: Image courtesy of http://steinvox.com/blog/big-data-and-analytics-the-analytics-value-chain/
Page 3: http://timoelliott.com/blog/2013/02/gartnerbi-emea-2013-part-1-analytics-moves-to-the-core.html
Page 4: http://www.informationbuilders.es/intl/co.uk/presentations/four_types_of_analytics.pdf

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