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It should offer a review of IT Emerging Technology and its important concepts. It will describe a sub-topic of IT emerging technology which you selected; you'll then need to elaborate on how the technology works, how it has been adopted by IT practical world at large, how it has been applied, and what shortcomings have been identified.


Data Mining and Database Technology (Web Mining, Text Mining, Sentimental Analysis for social media, tools, techniques, methods, applications etc.) Decades belonging the importance, use and relevance of IT are in the huge increase. The study, use and demand for IT is highly developing the each and every day, like, as per the ruling concern & now, this is a necessity for men. Using the highly developed systems, like, computers & telecommunications which refer the IT is going prosperously. Belonging those, there are many successful and popular IT sectors have born and now are controlling the economy. Besides, these telephonic and normal computer base information technologies, the power of data mining and database technology which literally refers to the huge concepts of IT are also crossing their distance of milestones day by day. And on behalf of that this paper is created.

Database Technology - The DT generally refers to the DBMS (Data Base Management System), is a highly decorated computer software application, that interacts with the user, other related applications, and the data itself, to capture and analyze the data. That term DATABASE refers to a huge collection of data. The collection of tables, information, queries, schemas, reports, different views and other many objectives. This supports one company by giving information which was previously loaded, but very difficult to find out. But by a query on the successful DTs, like, MySQL, Oracle, IBM DB and many more, the finder can easily get a single word of data from cores of data. Database Technology is highly recommended for all the big business groups, for keeping and retrieving their information. Like, if you having a hotel, which’s 90 rooms, are already booked among of the 115, then besides a manual research, you can easily allow a vacant room to your new customer by just typing only one query, which answers you which room is vacant. So, database technology makes easy and comfortable and it is a way to develop.

Data Mining- The term data mining refers to a huge concept, which defines and proves that DM is a pillar of the IT because without DM large companies will never be able to handle their stocks through IT. It helps companies to focus on the important issues in their data warehouse by its most powerful technologies. By data mining, one can examine the preexisting database in order to generate new information. This concept works like that, most of the valuable and international companies have a massive amount of data, now, the data mining technology can approach and implemented easily on the existing hardware and software paths to enhance and express the value of their existing resources. And the benefit is - it can be easily integrated with new systems, products as they are brought on-line. The performance also proves its potential while implanted on high-performance server/client or the parallel processing computers. The upgraded tools of data mining can easily analyze a massive database to deliver answers to such questions, like, “Which clients are most likely to respond to my next promotional mailing, and why”, which makes it easier to understand. As the best part of the use of data mining is, it can answer business questions, which is, on the other hand, is too time-consuming to resolve. As an overall review, it makes the system easy; it can explore the data with all its way, it is exploring the IT, and is helping the IT & IT business world.

Data mining is the new technology to extract out information from a given set of humongous data which was otherwise not apparent or was hidden and has the potential to direct big firms to focus on things important for their growth. Using these techniques businesses and companies has the ability to make data and fact driven decisions. Such decisions are made by the trends in behaviors and the predictions made by these analyses. The analysis offered by data mining is automated and have outreach outside the analyzes of past given by the tools typical of decision systems. Earlier there were queries which would require a lot of time to research on and hence were left out. Now Data mining tools have enabled the companies to get an answer to that too. Huge databases are scoured for finding the patterns which were otherwise not visible directly. It can also predict stuff that was not even expected by the experts because it was not apparent. Currently a lot of firms are collecting data for doing such analysis. This is because data mining techniques are easy to implement even if the platform is existing, be it software or hardware. This gives an extra edge to the information sources which can then be used to create new products as and when required. There are things that the companies need to know, like if they launch a promotion which segment of the customer will be swayed the most towards it. Such answers are achieved by the parallel processing computers.


Fayyad et.al. (1996) has shown the following six usage of data mining:

  1. Detection of the important changes in the overall data with one or more variables.
  2. Finding set of categories and clustering the data in them
  3. Mapping a given function variable to a real prediction variable using regression techniques.
  4. Sequencing the given data just like that of association rule
  5. Modeling a system describing the inter-dependencies of variables among them
  6. Analysis of the data provided and then grouping into various classes

Web Mining

When the above-described data mining techniques are used on the web pages to get relevant information the method utilized is called web mining. It is then classified on the basis of type of data used for this 

  1. Web Server Data: The data collected by the web server like the page access time of the IP of the user connected.
  2. Application Server Data: A little modification is done on the existing commercial applications servers and then they are used to track various kinds of business events and use the data collected thereby for various purposes.
  3. Application Level Data: Events can be defined in an application which do not exist currently, and data recording can be turned on for them thus creating the past of such of specially defined events

Text Mining

Text mining, or text data mining, is the method of gaining important insights from a given set of text. Methods like statistical pattern learning are used to extract information about trends and other patterns. This process usually involves restructuring the input text by removing some part or adding some and insertion of the text in a database. This is followed by finding patterns in this structured data and interpreting that pattern for useful purposes. Such analyzes also involve predictions, identifying patterns, finding distribution frequency, extracting information, analysis of clustering and associations within variables etc. The ultimate aim to make sure that the available text is turned as data which can then be easily analyzed using natural language processing (NLP). An example of the application could be scanning a document having usual handwriting and use it for normal search indexes or extract information out of it. Sentiment analysis Sentiment analysis usually known as opinion mining is using text analysis for extracting information and applying language processing for getting subjective information. Sentiment analysis is used in digital marketing and social media marketing for variety of applications. In general it gives you the overall attitude of a user for a product. This could be his/her personal judgment, the emotional state or whatever he/she wishes to express for the product.

Data Mining Tools

Some of the data mining tools as showed by Huang (2005) are:-

  1. 11 Ants:-used for business applications
  2. ADAPA- a framework to employ and integrate
  3.  Data Applied- A framework for Data Analysis
  4. Revolution R Enterprise- Based on an open source software R with many additional tools like Hadoop for big data and database coupling.

Data Mining Techniques

Data mining technique involve static machine learning, usage of databases and machine learning.

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