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CHAPTER 5 : BUSINESS INTELLIGENCE - Coggle Diagram
CHAPTER 5 : BUSINESS INTELLIGENCE
Business Intelligence User Models
a model that offers opportunities for businesses to transform raw data into meaningful and useful information, in order to build an effective strategic plan, as well as create tactical and operational insights for decision-making within a given timeframe
Implementation of Business Intelligence
Data warehouse
A database that stores current and historical data from many core operational transaction systems
Consolidates and standardizes information for use across enterprise, but data cannot be altered
Provides analysis, graphical and reporting tools
Data marts
Subset of data warehouse
Summarised or focused portion of data for use by specific population of users
Typically focuses on single subject or line of business
Hadoop
An open-source software framework managed by the Apache Software Foundation
Enables distributed parallel processing of big data across inexpensive computers
Using distributed file system data storage and NoSQL database
Used by Facebook, Yahoo, Uber, Netflix
In-Memory Computing
Relies primarily on a computer’s main memory (RAM) for data storage (the conventional DBMS use disk storage systems)
Analytic Platforms
Specialized high-speed analytic platforms developed by commercial database vendors using both relational and non-relational technology that are optimized for analysing large data sets
Preconfigured hardware-software systems that are specifically designed for query processing and analytics
Data Lake
A repository for raw unstructured data or structured data that for the most part has not yet been analysed, and the data can be accessed in many ways
Artificial Intelligence
Three Types of Artificial Intelligence
2. Artificial Narrow Intelligence (ANI)
which has a narrow range of abilities
the only type of artificial intelligence we have successfully realized to date.
Goal-oriented, designed to perform singular tasks
This type is commonly referred to as weak AI.
Narrow AI can either be reactive, or have a limited memory.
EXAMPLE: Siri (Apple), Google search, Cortona (Microsoft), Drone robot, Self-driving cars
1. Artificial general intelligence (AGI)
Strong AI or deep AI, is the concept of a machine with general intelligence that mimics human intelligence and/or behaviours, with the ability to learn and apply its intelligence to solve any problem
can think, understand, and act in a way
Challenges of AGI
Replicating Transfer Learning
Denote applying the knowledge learned in one domain to another. This is something that humans engage in every day and is an important part of society. For example, the knowledge of how to ride a bicycle is applied in riding a motorcycle.
Enabling Common Sense and Collaboration
Common sense is integral to human functioning, along with collaboration on tasks with other human minds. Due to the narrow nature of today’s algorithms, dependable collaboration has not been achieved, with common sense being a far-off reality.
Figuring Out Consciousness and Mind
human mind is still something that has not been decoded. These remain as significant obstacles to the creation and achievement of general artificial intelligence.
3. Artificial superintelligence (ASI)
more capable than a human
the hypothetical AI that doesn’t just mimic or understand human intelligence and behaviour; ASI is where machines become self-aware and surpass the capacity of human intelligence and ability.
a greater memory and a faster ability to process and analyse data and stimuli. Consequently, the decision-making and problem solving capabilities of super intelligent beings would be far superior than those of human beings.
Application of Artificial Intelligence
Used in different domains to give insights into user behaviour and give recommendations based on the data.
Example
Facebook uses past data of the users to automatically give suggestions to tag your friends, based on the facial features in their images.
Netflix uses past user data to recommend what movie a user might want to see next, making the user hooked onto the platform and increasing watch time
AI in our daily life
Computers that play chess
Self driving cars
Online shopping
Machine translations (subtitles and language detection)
Cybersecurity (recognising patterns and backtracking attacks)
AI in healthcare
Telemedicine (analyse symptoms etc)
Assisted diagnosis (read MRI scan etc)
Robot-assisted surgery
Vital Stats monitoring
AI in E-commerce
Chatbots
Filtering spam and fake reviews
Optimising search
Supply chain
AI in Human Resources
Hiring
Building work culture (analyse employee data and place in right teams)
Application and Implication of Artificial Intelligence
refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.
to aid human capabilities and help us make advanced decisions with far-reaching consequences
Applications and Tools
Once data have been captured and organised using the business intelligence technologies, they are further analysed using software for database querying and reporting, multidimensional data analysis (OLAP), and data mining
Online Analytical Processing (OLAP)
A multidimensional data analysis, enables rapid, online answers to ad hoc queries
Effective IT solution that is much used in the decision-making process of the business world.
With this system, it is possible to quickly make calculations for analyses and reporting, two important elements in the decision-making process.
The system has access to centralised business data which it rapidly analyses.
The insights formed here are used in the decision-making process.
Applications such as DSS and OLAP also appear in the Business Intelligence Model (BIM).
OLAP, not to be confused with OLTP, is often accompanied by huge quantities of data, Big Data.
Think of bank employees who analyse what the online banking behaviour of their customers looks like.
OLAP first requests data from the bank accounts of all customers, analyses user activity, and then presents the insights in a uncomplicated way.
Data mining
Finds hidden patterns, relationships in datasets, infers rules to predict future behaviour
Text mining
Extracts key elements from large unstructured data sets –emails, call centre transcripts, legal cases, service reports
Web mining
Discovery and analysis of useful patterns and information from web –customer behaviour, evaluate effectiveness of websites, Google looking at most searched words in search queries
Business Intelligence and Technology
Six elements
Data from business environment
Business must deal with both structured and unstructured data from many sources, including big data.
The data need to be integrated and organized
So, can be analyzed and used by human decision maker.
Example data from : call centers, website, mobile devices, socmed data, stores, suppliers & governmental & economic data
Business intelligence infrastructure
Data stored in transactional database or combined and integrated into enterprise data warehouse, series of interrelated data marts or analytic platform.
Business analytics toolset
used to analyzed data and produce reports, respond to questions manager pose and track the progress of business by using key indicators of performance.
Example : models, data mining, OLAP, reporting and query tools, big data analysis
Managerial users and methods
Managers impose order on the analysis of data using a variety of managerial methods that define strategic business goals and specific how progress measured
Example using business strategy, performance management, balanced scorecard and forecast.
Delivery platform – MIS, DSS, ESS
The result from BI and analytics are delivered to managers and employees in variety ways.
BI and analytics tools can integrate all information and brings to manager desktop or mobile platform.
Example platforms : MIS, DSS, ESS
User Interface
Business people often learn quicker from a visual representation of data than from a dry report with columns and row information.
Can be delivered reports on mobile phones, tablets and firm website.
Using data visualization tools, such as rich graphs, charts, dashboards ad map.
Example user interface : Reports, dashboards, desktop, mobile, web portal & socmed
The largest FIVE(5) providers of these products
Microsoft
SPSS
IBM
Oracle
SAP