Info DP/Systems chapter 3
Knowledge Management (K M)
- Creates value from intellectual capital and shares knowledge with those who need that capital - Improves process quality - Increases team strength
What are three techniques for processing BI data?
- How recently (R) a customer has ordered - How frequently (F) a customer ordered - How much money (M) the customer has spent
unsupervised data mining
Analysts do not create a model or hypothesis before running the analysis.
Dynamic Reports
BI documents that are updated at the time they are requested.
Project Management
Build in-store cafés. Expand to other locations.
What are three techniques for processing BI data? Data mining goal
Classify and predict
What are three techniques for processing BI data? Reporting Goal
Create information about past performance
Data Type: Data format
Data Warehouse: Cleaned and Filtered data
Data Type: Data time frame
Data Warehouse: Historical data
Data Type: Sources
Data Warehouse: Operational systems and purchased data
Data Type: Data Structure
Data Warehouse: Structured data
Data Type: Users
Data Warehouse: Used by business analysts
How do organizations use data warehouses and data marts to acquire data?
Dirty data Missing values Inconsistent data Data not integrated
Goal:
Enable employees to use organization's collective knowledge
What are three techniques for processing BI data? Big Data goal
Find patterns and relationships in Big Data
Problem Solving
How can we increase sales? How can we reduce food waste?
Data Discovery/ Data Visualization
In an effort to make finding patterns and relationships among data more user-friendly, processes have been developed to allow users to visually analyze and explore data
Examples of Consumer Data That Can Be Purchased
Name, address, phone Age Gender Religion income Education Voter Registration Home ownership Vehicles Magazine subscriptions
cluster analysis
One common unsupervised technique
What are three techniques for processing BI data? Reporting Characteristics
Process structured data by sorting, grouping, summing, filtering, and formatting
Deep Learning
This multilayered neural network technique was applied to learning tasks and is now commonly known
How do organizations use data warehouses and data marts to acquire data?
Too much data - Too many attributes - Too many data points
What are three techniques for processing BI data? Data mining Characteristics
Use sophisticated statistical techniques to find patterns and relationships
What are three techniques for processing BI data? Big Data Characteristics
Volume, velocity, and variety force use of MapReduce techniques Some applications use reporting and data mining as well
BI server
Web server application that is purpose-built for the publishing of business intelligence.
Deciding
Which customers shop at each location? Create custom marketing plans per store.
Informing
Which products are selling quickly? Which products are most profitable?
How do organizations use data warehouses and data marts to acquire data?
Wrong granularity Too fine Not fine enough
reporting application
a BI application that inputs data from one or more sources and applies reporting operations to that data to produce business intelligence
corpus of knowledge
a large set of related data and texts.
Online Analytical Processing (OLAP)
a second type of reporting application, is more generic than RFM. OLAP provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data.
RFM Analysis
a technique readily implemented with basic reporting operations, is used to analyze and rank customers according to their purchasing patterns
natural language processing (NLP)
ability of a computer system to understand spoken human language, to answer questions
Hadoop
an open source program supported by the Apache Foundation that manages thousands of computers and that implements MapReduce
Static Reports
are BI documents that are fixed at the time of creation and do not change.
Business Intelligence
are information systems that process operational, social, and other data to identify patterns, relationships, and trends for use by business professionals and other knowledge workers.
superintelligence
capable of intelligence more advanced than human intelligence.
Structured data
data in the form of rows and columns
supervised data mining
data miners develop a model prior to the analysis and apply statistical techniques to data to estimate parameters of the model
push publishing
delivers business intelligence to users without any request from the users; the BI results are delivered according to a schedule or as a result of an event or particular data condition.
machine learning
extraction of knowledge from data based on algorithms created from training data.
weak AI
focused on completing a single specific task.
Content management systems (CMS)
information systems that support the management and delivery of documents including reports, Web pages, and other expressions of employee knowledge.
data lake
is a central repository for large amounts of raw unstructured data. Data lakes are similar to data warehouses, but they are used for different purposes.
Neural network
is a computing system modeled after the human brain that is used to predict values and make classifications.
data mart
is a data collection, smaller than the data warehouse, that addresses the needs of a particular department or functional area of the business.
OLAP Report
is that the user can alter the format of the report.
artificial intelligence (AI)
is the ability of a machine to simulate human abilities such as vision, communication, recognition, learning, and decision making in order to achieve a goal.
Data Mining
is the application of statistical techniques to find patterns and relationships among data for classification and prediction.
measure
is the data item of interest.
BI analysis
is the process of creating business intelligence. The three fundamental categories of BI analysis are reporting, data mining, and Big Data.
regression analysis
measures the effect of a set of variables on another variable
Functions of a data warehouse
obtain data, cleanse data, organize and relate data, catalog data
Acquire Data
obtain, cleanse, organize and relate, catalog
Data Extraction/ Cleaning Preparation Programs
operational databases, other internal data, external data
Data Sources
operational databases, social data, purchased data, employee knowledge
Publish Results
print, web servers, report servers, knowledge management systems, content management systems
Exception reports
produced when something out of predefined bounds occurs.
Perform Analysis
reporting, data mining, big data
pull publishing
requires the user to request BI results. Publishing media include print as well as online content delivered via Web servers, specialized Web servers known as report servers, automated applications, knowledge management systems, and content management systems.
Granularity
term that refers to the level of detail represented by the data. Granularity can be too fine or too coarse.
strong AI
that can complete all of the same tasks a human can. This includes the ability to process natural language; to sense, learn, and interact with the physical world; to represent knowledge; to reason; and to plan
reporting analysis
the process of sorting, grouping, summing, filtering, and formatting structured data