ISM 3541 Exam 1 FSU

Planning for Success Framework

- Scope

- Schedule

- Resources

Scope

Features, functionality

Schedule

Time and Prioritization

Resources

Cost, Budget, and human

Intelligence

The ability to acquire and apply knowledge and skills; a person or being with the ability to acquire and apply knowledge; the collection of information of military or political value

Analytics

The systematic computational analysis of data or statistics; information resulting from the systematic analysis of data or statistics

o Business Intelligence is on the decline and Business Analytics is on the rise

Academic View of Defining Analytics

- Increasing knowledge through progressive elaboration

- Markets for products and services have consumers and suppliers

- Data is stored and extended through the MIS and KIS constructs

- Analytics is a component of knowledge

Data is stored in a

Database

Data is extended to information via

Applications, queries and reports

Information is extended into knowledge through

Decision Making

Knowledge is extended into wisdom through

Smart decision based on high quality data and experience

Data Modeling

Descriptive modeling, predictive modeling, prescriptive modeling

Project Management Body of Knowledge

Process for defining the "schedule-scope-resources" boundaries that evolve through a concept of progressive elaboration over a period of time defined by a hard start date and end date

Descriptive Analytics

Leveraging known, historical data to create a story about how an object arrived in its current state

Predictive Analytics

Creating modules on objects based on attributes gathered from data sets to determine the future behavior of an object and being able to rationalize the prediction based on a formula or algorithm that incorporates risk and probability

Decision Analytics

Is "predictive analysis" on steroids where multiple paths for future behavior are guesstimated based on probability, risk, impact, and priority and is supported by an overall recommendation(s)

The world of business analytics is a

"Green Field"

"Green Field" implies that

We are in frontier discovery mode

Big Data (data science)

A strategy for many businesses and should be considered when developing a company's vision for where they are heading

App

An executable file that is stored locally on a device and conducts some processing of data locally and then passed back to the server

Web Application

A browser-based form that processes data through external servers and presents the results on the device's screen

How does a business ensure that it gets the most from the wealth of data?

- The firm's management must think data analytically

- The management must create a culture where data science methods, and data scientists, will thrive

The real opportunity and value is to gather data as a long-term strategic opportunity by

Leveraging Big Data

Protect Unique Intellectual Property

Data science intellectual property can include novel techniques for mining the data or for using the results

Protect Unique Intangible Collateral Assets

Your model is not what your data scientist design, it is what your engineers implement; therefore, the actual source of good performance of a successful data science solution is unclear to competitors

Hire superior data scientist and create culture for

All types of professionals to thrive

Writing Through Big Data (WtBD)

Feeding into various networks where knowledge is exchanged and consumed in a manner that decision-making methods are moving toward data-driven decision-making via dashboards built upon the Big Data generated

Takeaway

We are able to process more data through automated writing

Being a proficient communicator through _____ _____, which includes being able to tell a story in a picture, is an increasingly valuable skill

Digital content

Classification

Supervised method focused on predicting the target variable of a new unseen instance by determining which segment that the data point resides

Data visualization can be applied showing

Two attributes of interest in a data set

Logistical Regression

Supervised method has to do with predicting and applying probability to our model

Supervised Learning Method

The learner has access to data sets (training data) and creates and runs models off their interpretation of the data. Models are constantly adjusted as more data is included in the model

Unsupervised Learning Method

True research and development, where we have little clues in terms of the data and what the data represents. We are applying tools and techniques designed to take data from the subjective to objective perspective. This is the difference of opinion and fact. This type of style requires unbounded time and resources in order to evolve the model to take advantage of the learning that occurs

Cross-Industry Standard Process for Data Mining (CRISP-DM)

Very first process is business understanding, which is similar to the first step in most any problem-solving framework of identifying the problem first

Cross-Industry Standard Process for Data Mining (CRISP-DM) Steps

1. Outline storyboard (vision casting)

2. Extract and prepare supporting data source(s)

3. Analyze data - Phase 1 (data mining techniques)

4. Incorporate context - Phase 2 (modeling)

5. Populate and display output (data visualization)

Link Prediction

A qualitative approach to apply a data mining technique to a data set

Similarity Matching

Method of identifying similar individuals based on data known about them

Co-Occurence Grouping

An attempt to discover associations between individuals based on transactions involving them

Casual Modeling

Estimating approach based on the assumption that future value of a variable is a mathematical function of the values of the other variable(s). used where sufficient historical data is available, and the relationship (correlation) between the dependent variable to be forecasted and associated independent variable(s) is well known

Understanding how users may potentially access and provide Big Data is a consideration when selecting which technology to apply

True

Choose the model that best answers the question, "How did I get here?"

Descriptive

Writing through Big Data occurs through

Networks

Which approach to business analytics attempts to assign each unit in a population into a small set of classes where the unit belongs?

Classification

Consider the flow of data is a major consideration in analytics architecture

True

Data flow is not a major consideration

False

Considering the flow of wisdom is a major consideration in analytics architecture

False