LU3 pt. 2 Flashcards
What is Online Analytical Processing (OLAP)?
It supports multidimensional data analysis,
enabling users to view the same data in different ways using multiple dimensions.
Different dimensions can mean: product, pricing, cost, region
What is data mining?
It is discovery-driven; it provides insights into corporate data
that cannot be obtained with OLAP by finding hidden patterns and relationships in
large databases and inferring rules from them to predict future behaviour.
Patterns and rules are set to guide decision making and forecast the effect of
these decisions.
What are types of data obtained from data mining?
A. Associations: occurrences linked to a single event;
for instance normally cola are sold 65%, but when it is a promotion, it is sold 80% => this leads toward a
better understanding of decision making.
B. Sequences: events are linked over time;
when you buy a house, in two months you will buy a refrigerator; it shows patterns.
C. Classification: recognises patterns that describe the group to which an item
belongs by examining existing items that have been classified and by inferring a set of rules.
D. Clustering: works in a manner similar to classification when no group have yet
been defined.
E. Forecasting uses predictions in a different way than the other ones;
It uses a series of existing values to forecast what other values will be. e.g. sales figures in
future.
XXX XXX, most in the form of text files, is believed to account for more than 80% of useful organisation information and it is one of the major sources of big data that firms want to analyse.
XUNSTRUCTURED DATAX, most in the form of text files, is believed to account for more than 80% of useful organisation information and it is one of the major sources of big data that firms want to analyse.
What is text mining?
Tools which are available to help businesses analyse their data. They
are able to extract key elements from structured big data sets, discover patterns and
trends.
What is sentiment analysis?
Software which is able to mine text comments in an email message,
blog, social media conversations or survey to detect favourable and unfavourable opinions about specific subjects.
What is web mining?
It’s a rich source of unstructured big data for revealing patterns and
trends , etc., and customer behaviour. It’s the discovery and analysis of useful patterns and information from World Wide Web.
What is web content mining?
It’s the process of extracting knowledge from the content of webpages, which may include text, image, audio and video data.
What is web structured mining?
Examining data related to the structure of a particular
website.
What is web user mining?
Examining user interaction data recorded by a web server whenever requests for a website’s resources are received.
Business Intelligence (BI) is:
The infrastructure for warehousing, integrating, reporting, and analysing data that come from business environment, including big data. (Databases, data warehouses, data marts, HADOOP, and analytical platforms)
Business Analytics (BS) is:
A vendor-defined term which focusses on tools and techniques for analysing and understanding data. (OLAP. statistics, models and data mining)
The six elements of the business intelligence environment:
I. Data from business environment: business must deal with both structural and unstructured data from many different sources, including big data.
II. Business intelligence infrastructure: foundation of BI is a powerful database
system that captures all the relevant data to operate the business.
III. Business analytics toolset: a set of software tools are used to analyse data and produce reports, responses to questions posed by managers and track the progress using KPI.
IV. Managerial users and methods: BI hardware and software are only as intelligent as the humans. Managers impose order on the analysis of data using a variety of managerial methods that define strategy business goals.
V. Delivery platform (MIS, DSS, ESS): the results for business intelligence and
analytics are delivered to managers and employees in a variety of ways,
depending on what they need to know to perform their jobs.
MIS, DSS, ESS= deliver information and knowledge to different people and levels in the firm: operational employees, middle and senior executives
VI. Users interface: business analytics software suits future data visualisation tools; using iPad, iPhones, etc.
Business Intelligence and (6) analytic functions promising to deliver correct, nearly real-time information to decision makers and analytic tools helping them to quickly understand the info and to take action:
I. Production reports: predefined reports
II. Parameterised reports: you might want to enter region and time of day to understand how sales of a product vary by region or time
III. Dashboards: visual tools for presenting performance data
IV. Ad hoc query/search/report creation: allows user to create their own reports based on queries and search
V. Drill down: ability to move from a high-level summary to a more detailed view
VI. Forecast, scenarios, models: include ability to perform linear forecasting, and what-if scenario analysis and analyse data using standard statistical tools
Predictive analytics:
Uses statistical analysis, data mining techniques, historical
data, and assumptions about future conditions to predict future trends and
behaviour patterns.
