Data mining is a practice that will automatically search a large volume of data to discover behaviors, patterns, and trends that are not possible with the simple analysis. Data Mining should allow businesses to make proactive, knowledge-driven decisions that will make the place better ahead of their competitors.
Data warehouse, from its mandate to store a large volume of data including the last years of data. The data warehouse is used for descriptive analysis What happened and diagnostic analysis Why it happened. However, business needs to do analysis beyond that. Data mining can be utilized for Predictive Analysis What will happen and Prescriptive Analysis How can we make it happen.
SQL Server is mainly used as a storage tool in many organizations. People are looking at data warehousing with SQL Server. There are a few tasks used to solve business problems. SQL Server Data Mining has nine data mining algorithms that can be used to solve the aforementioned business problems. The following are the list of algorithms that are categorized into different problems. Classify: Categorized depending on the various attributes. For example, whether a customer is a prospect customer depending on other data such as Age, Gender, Marital Status, Occupation, Education Qualification, etc.
Estimate: Estimation will be done using the parameters. For example, house prices will be predicted depending on the house location, house size, etc. Cluster: also named as segmentation. Depending on the various attribute natural grouping is done.
Customer Segmentation is the classical business example for the clustering. Forecast: Predict continuous variable for with the time. Predicting sales volume for the next couple of years is a very common scenario in the industry. Associate: Finding common items or groups in one transaction. The transaction can be a supermarket sales, or medicine or online sales. In this article series, we will be using a sample data set which you can download and run through with the article.
There are fact and dimension tables in the sample database. However, we will be using the below-listed views predominantly here. Let us create a data mining project. Following is the Solution Explorer for the created project.
We need to configure the data source to the project as shown below. The data source makes a connection to the sample database, AdventureWorksDW After providing the credential to the source database, next is to provide the credentials to the Analysis service to connect to the database.
Analysis service will be used to store the data mining models and analysis service only use windows authentication. Any of the four options can be used to provide the necessary connection.
With this, you have configured the data source to the project and of course, you can modify them later. It is written using java language. The fast miner can be used for predictive analysis, business application, education and research, commercial applications, etc. It increases the speed of delivery as it follows the template framework. It not only increases the delivery speed but also reduces errors while transforming.
It is open-source software written in python language. Orange is the best software for analyzing data and machine learning. These components are called widgets. These widgets are used for reading data, analyzing components, allowing users to select the features, and showing the data. With orange, data formatting and moving them with the help of widgets becomes fast and easy.
The University of Waikato develops weka. It is an open-source software used for predictive modelling and analysis of data. Weka has a GUI interface that provides easy and interactive access to users. It supports SQL and allows a user to connects to the database, and performs operations by firing query. It stores data in a flat-file format. It is built by combining data mining and machine learning components. It has been used for pharmaceutical research, business intelligence, and financial analysis.
It is not open-source software; it is licensed software, and we have to purchase the license to use this. Small and large organizations use Sisense to handle the data. As it also supports widgets like orange, it is easy to move data and creates reports by dragging and dropping. Not even technical people can work with Sisense as its GUI based.
With the help of widgets, Sisense generated words are in the form of bar chart, pie chart, line chart, etc. Yes, you are right. You can derive business intelligence by discovering correlations and network of patterns so that you can work out the future trends based on the past data. This can help you shape your business strategy.
With the growing importance of web mining, the web mining tools have also rapidly come up. There are several tools and software available to work out the business insights and intelligence. You can also leverage a tool like Scrapy to mine content, for instance web scrapping. With a variety of tools at your disposal, you can get it all mixed up. But before you understand different tools, it would be great to explore web mining a bit and see how it works. Well, in simple terms, web mining is the way you apply data mining techniques so that you can extract knowledge from web data.
This web data could be a number of things. Once you have the extracted information, you could analyze it to derive insights as per your requirement. For instance, you could align your marketing or sales strategy based on the results that your web mining throws up. Since you have access to a lot of data, you have got your finger on the market pulse. You can study customer behavior patterns to know and understand what the customers want. You can correlate it to your own business structure and strategy to see how you can reconfigure things at your end.
With this sort of analysis of data, you can discover internal bottlenecks and troubleshoot. Overall, you can get ahead of everyone in terms of how you anticipate the industry trends and plan accordingly. Web content mining has seen rapid development primarily because the web has seen a rapid growth of content.
Considering the fact that there are billions of web pages with lots and lot of such data, and the web pages are getting added on a continuous basis. In addition to this, an average user is no longer just a consumer of information but a disseminator and creator of content.
A web page has a lot of data; it could be text, images, audio, video or structured records such as lists or tables. Web content mining is all about extracting useful information from the data that the web page is made of. Web content mining applies the principles and techniques of data mining and knowledge discovery process. Web structure mining focuses on creating a sort of structural summary about web pages and websites.
Based on the hyperlinks and document structure, such a structural summary is generated. What web structure mining accomplishes that it discovers association of hyperlinks at document level.
Algorithms like Pagerank and hyperlink induced search algorithm are employed to achieve this. Web structure mining is particularly useful in improving marketing strategies by discovering relationship and link hierarchy between web pages. Web usage mining focuses its attention on the users. It is used to work out the analysis of website users based on the web site logs. Different logs like web server log, customer log, program log, application server log etc.
Web usage mining attempts to find out useful information based on the interaction of users. Web usage mining is important because it can help organizations find out the life-time value of clients, design cross-marketing strategies across products and services, evaluate the efficacy of promotional campaigns, optimize the functionality of web-based applications and provide more personalized content to visitors for their web space.
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It eliminates your biggest fear- getting blocked. With ProWebScraper, you are never going to get blocked. You can simply relax and continue scraping web data. If you have bulk web data scraping in mind, ProWebScraper is the tool for it. Leave the technicalities to ProWebScraper, you can just peg away at web data! Google Analytics is considered to be one of the best business analytics tool.
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