Finansbank selects KXEN data mining solution

Finansbank - Turkey's fifth largest financial institution - is using data mining technology from KXEN to help it better address a growing market for loans and credit, and at the same time stimulate new activity among dormant customers.

According to Kunter Kutluay, Finansbank's Director of Marketing and Risk Analytics, the benefits of deploying KXEN's technology are broad: "We saw an opportunity to improve our interactions with customers through data mining, simultaneously increasing customer lifetime value, and making Finansbank more relevant to our clients," he says.

It was after an extended evaluation of analytics tools that the Finansbank team chose KXEN's Automated Data Mining. Based on breakthrough mathematical thinking, it impressed the team with its ease of use by non-experts, the quality of the analytical models it produced, and the sheer speed of its operation.

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Data mining: Three steps to mining unstructured data

The business value of unstructured data can be left unexploited when data mining is executed with an inadequate, static data model designed for structured data. The authors of this chapter excerpt detail a three-phase process intended to make data mining and analyzing unstructured data more streamlined.

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What Is Enterprise Data Integration

Enterprise data integration is the process of combining information from various business data resources on demand to fulfill particular enterprise requirements. It also includes the sharing of data among various business applications. Enterprise data integration is considered as one of the most needed Customer Relationship Management (CRM) practices. Today, enterprise data integration is widely practiced by all companies and business groups, especially Internet-based companies. There are also many types of data integration systems and software programs designed for this purpose.

There are many advantages of enterprise data integration. This includes reduction in data accumulation, elimination of duplicate data, decrease in time expenditure in capturing data, quick data delivery, fast data sharing, time and capital saving by automated data entry, escape form manual report preparing and printing, better product marketing, on demand data availability, better customer data integration, better customer contact management, enhancement in sales force automation processes (SFA), and simplification of all business procedures.

Enterprise data integration cover a range of data management techniques such as MDI (Master Data Management), EII (Enterprise Information Integration), ETL (Extract-Transform-Load), EAI (Enterprise Application Integration), CDI (Customer Data Integration) and SOA (Service Oriented Architecture). The general processes involved in enterprise data integration procedure are data consolidation, data federation and data propagation or data migration. Automated customer contact management, leads generation, task management and account management are some applications of enterprise data integration.

The enterprise data processing systems and software programs, commonly known as enterprise data integration solutions are talented to accessing multiple remote databases in tandem, providing real-time meaningful information and resources. They are programmed to put right information in right places. The main data storing devices are consolidation repositories, data warehouses and data marts. The enterprise data entry software programs are equipped with advanced communication tools, either internet-linked or local network-linked, which help in integrating all resources.

Generally there are five levels in an enterprise data integration procedure. That are, enterprise portals or user interfaces that include customer contact sites such as payment processing solutions, sale systems and bookkeeping systems; collaboration tools or software programs that coordinates all proceedings; business process management systems; enterprise applications integration tools and systems and enterprise information integration tools.

Well implemented enterprise data integration solutions eliminate data latency, false/duplicate data entry and data pollution. A perfect solution must be able to obtain data from all company resources and from all data formats like excel spread sheets, PDF files, company sales graphs and pictures, and from other application resources. The data integration solution must provide all wanted information from any where quickly and smoothly.

The fundamental step in enterprise data integration is the automation of all data works. All large sized companies and corporations now have their own data integration centers or resource management departments for automating all customer information related practices. These departments will design customized integration tools and best practices to help corporation’s integration architecture. On the other hand, for medium and small sized companies with small capital investment, managing a separate department can be difficult. For these companies, now there are some enterprise data integration service/software providers offering their service.

Before implementing an enterprise data integration system, the company must design data integration architecture for the company using all their data resources. For that they have to track all operating business unites with in the organization, and have to give priorities to them. Healing broken data links, organizing a data source system - from which one can access resources, and information hubs, can greatly help in proper data integration.

Today there are many data integration software vendors and service providers in the market. You can find them by just searching on Internet. If you are looking for enterprise data integration software, look for one software vendor who offers customized software packages. Open source software packages are also available; you can customize them if you have enough technical assistance. If you are looking for an online service provider, enquire that the provider offers proper security to all your information. Also make sure that the online service provider has enough data integrating capacity.

This article has been published by eSalesTrack.com , a US based provider of on-demand CRM (Customer Relationship Management) and other application software such as Sales Force Automation and Data Integration Service.

Source : http://www.articledashboard.com/

Importance of Data Mining in today's business world

What is Data Mining? Well, it can be defined as the process of getting hidden information from the piles of databases for analysis purposes. Data Mining is also known as Knowledge Discovery in Databases (KDD). It is nothing but extraction of data from large databases for some specialized work.

Data Mining is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, e-commerce, investment trend in stocks & real estates, telecommunications and so on. Data Mining is based on mathematical algorithm and analytical skills to drive the desired results from the huge database collection.

Data Mining has great importance in today's highly competitive business environment. A new concept of Business Intelligence data mining has evolved now, which is widely used by leading corporate houses to stay ahead of their competitors. Business Intelligence (BI) can help in providing latest information and used for competition analysis, market research, economical trends, consume behavior, industry research, geographical information analysis and so on. Business Intelligence Data Mining helps in decision-making.

Data Mining applications are widely used in direct marketing, health industry, e-commerce, customer relationship management (CRM), FMCG industry, telecommunication industry and financial sector. Data mining is available in various forms like text mining, web mining, audio & video data mining, pictorial data mining, relational databases, and social networks data mining.

Data mining, however, is a crucial process and requires lots of time and patience in collecting desired data due to complexity and of the databases. This could also be possible that you need to look for help from outsourcing companies. These outsourcing companies are specialized in extracting or mining the data, filtering it and then keeping them in order for analysis. Data Mining has been used in different context but is being commonly used for business and organizational needs for analytical purposes

Usually data mining requires lots of manual job such as collecting information, assessing data, using internet to look for more details etc. The second option is to make software that will scan the internet to find relevant details and information. Software option could be the best for data mining as this will save tremendous amount of time and labor. Some of the popular data mining software programs available are Connexor Machines, Free Text Software Technologies, Megaputer Text Analyst, SAS Text Miner, LexiQuest, WordStat, Lextek Profiling Engine.

However, this could be possible that you won't get appropriate software which will be suitable for your work or finding the suitable programmer would also be difficult or they may charge hefty amount for their services. Even if you are using the best software, you will still need human help in completion of projects. In that case, outsourcing data mining job will be advisable.

Scott Naxton is a freelance journalist having experience of many years writing articles and news releases on businesses like outsourcing, internet marketing, health and insurance. He is also associated with KPO, Outsourcing and knowledge process outsourcing.

Source: http://www.articlealley.com/