Chapter-1
Introduction
This chapter gives the overview of the Association Rule Mining. It gives the importance of the Market Basket Analysis and its usefulness in increasing the sales of the supermarket. This chapter also provides an overview of the data mining process used in market basket analysis and the proposed approaches. The works of a few scientists are cited and utilized as proof to confidence the ideas clarified in the theory. Every such proof utilized is recorded as a part of the reference area of this thesis.
1.1 Overview
Currently the world has a wealth of data, stored all over the planet (the Internet and Web are prime examples), but it is needed to be understand that data. It has been stated that the amount of data doubles approximately
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Data mining has emerged as an important method to discover useful information, hidden patterns or rules from different types of datasets. Association rule mining is one of the dominating data mining technologies. Association rule mining is a process for finding associations or relations between data items or attributes in large datasets. Association rule is one of the most popular techniques and an important research issue in the area of data mining and knowledge discovery for many different purposes such as data analysis, decision support, patterns or correlations discovery on different types of datasets. Association rule mining has been proven to be a successful technique for extracting useful information from large datasets. Various algorithms or models were developed many of which have been applied in various application domains that include telecommunication networks, market analysis, risk management, inventory control and many others …show more content…
Nonetheless, there is no viable strategy to use these databases productively and to locate the important relationship in the middle of them. Association rule mining finds fascinating Association or connection among a lot of data things. With immense measures of data always being gathered and amassed, numerous enterprises and stores are demonstrating enthusiasm for mining relationship from this substantial accumulation of business exchange records, as it can help with numerous business basic leadership procedures, for example, index plan, cross-advertising and
The protests that took place in 2014 to campaign for Arthur T.’s job back is one of the most uplifting business stories to date. In the book We Are Market Basket by Daniel Korschun and Grant Walker the most important aspects of the book are the policy of Market Basket which puts the customer as their first priority, the warehouse workers igniting the protest, and the role of Rafaela Evans. The book also provides lessons you can apply to your own life; at the same time, it provides a clearer understanding to the business world.
CarMax faces challenges from several fronts that could threaten to disrupt their growth plans and their position as a disruptor in the used car market. The biggest challenge they face is being able to continuously secure a study supply of high quality used cars, due to the extremely competitive nature of the used car market. CarMax offers cutting edge technology to help the company identify buying trends, pricing trends, and consumer preferences down to the zip code that gave them a large competitive advantage, as “data mining” has matured and competitors have developed their own software tools, eroding the competitive advantage to CarMax.
According to Lisa Arthur, big data is as powerful as a tsunami, but it’s a deluge that can be controlled. In a positive way it provides business insights and value. Big data is data that exceeds the processing capacity of conventional database systems. It is a collection of data from traditional and digital sources inside and outside a company that represents a source of ongoing discovery and analysis. The data is too big, moves to fast, or doesn’t fit the structures of the database architecture. Daily, we create 2.5 quintillion bytes of data. In the last couple years we have created 90% of data we have in the world. This data comes from many places like climate information, social media sites, pictures or videos, purchase transaction records, cell phone GPS signals, and many more places. From the beginning of recorded time through 2003 users created 5 billion gigabytes of data. 2011, the same amount was created every couple days. 2013, we created that same amount every ten minutes. Some users prefer to constrain big data into digital inputs like web behavior and social network interactions. The data doesn’t exclude traditional data that is from product transaction information, financial records and interaction channels.
DeMoulas Supermarket, more famously known as Market Basket, is a retail conglomerate based in Tewksbury, Massachusetts. Founded in 1917 by Greek immigrants, the Market Basket chain has expanded into 75 stores – with branches located in Massachusetts, Maine, and New Hampshire.
Big Data is a popular phrase used to describe a massive amount of both structured and unstructured data. Big data is difficult to process with traditional database and software techniques because of large quantity of data. Volume, velocity, variability and variety are three characteristics of Big Data.
The information that can be extracted from the business information software is endless. In the article written by Alison Dragoon, Business Intelligence Get Smart(er), she states the following about data usage; ? ?[Unused data] is still a great source of untapped productivity and competitive advantage for most companies," he says. Just how much data is going unused? Downes guesses companies are extracting value from only about 20 percent of their data.? With this stated by placing all pertinent information into one database allows personnel throughout the company to pull data that will assist in their daily duties. This data can be arranged to track the life cycle of any product from birth to grave. By tracking an item in this fashion allows us to alleviate faulty products in this process or to allevia...
* Data - how much data will be obtained and how will you store and
With the world of digital data growing exponentially year on year, the above quote could just represent a mere drop in the ocean when accounting for the time workers spend looking for information. The next question is, once the information has been found, can it then actually be interpreted and understood within its original context and in the context required? Without adequate systems to deal with the data deluge, and efficient working practices around ingestion, and storage and retrieval, many digital objects can be lost forever, floating in a digital ether, costing money not only in storage, but in the potential recreation of an existing asset, as well as in lost time searching and retrieving content.
A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.
...ch Reips. ““Big Data”: Big Gaps of Knowledge in the Field of Internet Science.” International Journal of Internet Science 7.1 (2012): n. pag. Web. 16 Mar. 2014.
At the present time, the world has been changing rapidly because technology was invented to help people's lives. It has converted how people connect and communicate with each other. It is really easy to acquire knowledge from all areas around the world. As a result, the quantity of global information increases rapidly. Some data is difficult and complex to understand such as technological, scientific or statistic information.
The dynamics of our society bring many challenges and opportunities to the business world. Within the last decade, hundreds of jobs have emerged particularly in the technology sector to help keep up with the ever-changing world and to compete on a larger and better scale than the competition. Two key job markets and the basis of this research paper are business intelligence or BI and data mining or DM. These two fields play a very important role in small to large companies and are becoming higher desired sectors within the back offices of the workplace. This paper will explore what the meaning of BI and DM really is, how they are used and what we can expect as workers and learners of the technology and business fields for the future.
A laptop that is filled with thousands of pictures, videos, music, newspapers, magazines, and documents from today. Imagine a laptop that has information about the every country in the world without even connecting to the internet. The laptop would basically reflect the today’s world. There would be many informations about each country in the world, such as their language and important facts about their country. There would be a file for every country, and it would have data for each country.
Big data is a concept that has been misunderstood therefore I will be writing this paper with the intentions of thoroughly discussing this technological concept and all its dimensions with regard to what constitutes big data and how the term came about. The rapid innovations in Information Technology have brought about the realisation of big data. The concept of big data is complex and has different connotations but I intend to clarify its functions. Big data refers to the concept of a collection of large and complex amounts of data that are found extremely difficult to notate or even process by most on-hand devices and database technologies.
Data can be considered as raw and unorganized particulars. Data has little to no meaning when observed and can be something simple and seemingly random and useless, but can achieve meaning if sorted and organized. Data can be in the form of numbers, characters, symbols, or even pictures.