Database Mining

The term database mining refers to the process of extracting information from a set database and transforming that into understandable information. The data mining process is also known as data dredging or data snooping. The consumer focused companies into retail, financial, communication, and marketing fields are using data mining for cost reduction and increase revenues. This process is the powerful technology, which helps the organisations to focus on the most important and relevant information from their collected data. Organisations can easily understand the potential customers and their behaviour with this process. By predicting behaviours of future trends the recruitment process outsourcing firms assists the multiple organisations to make proactive and profitable decisions in their business. The database mining term is originated from the similarities between searching for valuable information in large databases and mining a mountain for a vein of valuable crystal.

Recruitment process outsourcing firm helps the organisation for the betterment of their future by analyzing the data from distinctive dimensions or angles. From the business point of view, the data mining and data entry services leads the organisation to increase their profitability and customer demands. Data mining process is must for every organisation to survive in the competitive market and quality assurance. Now a day the data mining services are actively utilised and adapted by many organisations to achieve great success and analyse competitor growth, profit analysis, budget, and sales etc. The data mining is a form of artificial intelligence that uses the automated process to find required information. You can easily and swiftly plan your business strategy for the future by finding and collecting the equivalent information from huge data.

With the advanced analytics and modern techniques, the database mining process uncovers the in-depth business intelligence. You can ask for the certain information and let this process provide you information, which can lead to an immense improvement in your business and quality. Every organisation holds a huge amount of data in their database. Due to rapid computerisation of business, the large amount of data gets produced by every organisation and then database mining comes in the picture. When there are problems arising and challenges addressing in the database management of your organisation, the fundamental usage of data mining will help you out with maximum returns. Thus, from the strategic point of view, the rapidly growing world of digital data will depend on the ability of mining and managing the data.

Source: http://ezinearticles.com/?Database-Mining&id=7292341

Data Mining and Financial Data Analysis

Introduction:

Most marketers understand the value of collecting financial data, but also realize the challenges of leveraging this knowledge to create intelligent, proactive pathways back to the customer. Data mining - technologies and techniques for recognizing and tracking patterns within data - helps businesses sift through layers of seemingly unrelated data for meaningful relationships, where they can anticipate, rather than simply react to, customer needs as well as financial need. In this accessible introduction, we provides a business and technological overview of data mining and outlines how, along with sound business processes and complementary technologies, data mining can reinforce and redefine for financial analysis.

Objective:

1. The main objective of mining techniques is to discuss how customized data mining tools should be developed for financial data analysis.

2. Usage pattern, in terms of the purpose can be categories as per the need for financial analysis.

3. Develop a tool for financial analysis through data mining techniques.

Data mining:

Data mining is the procedure for extracting or mining knowledge for the large quantity of data or we can say data mining is "knowledge mining for data" or also we can say Knowledge Discovery in Database (KDD). Means data mining is : data collection , database creation, data management, data analysis and understanding.

There are some steps in the process of knowledge discovery in database, such as

1. Data cleaning. (To remove nose and inconsistent data)

2. Data integration. (Where multiple data source may be combined.)

3. Data selection. (Where data relevant to the analysis task are retrieved from the database.)

4. Data transformation. (Where data are transformed or consolidated into forms appropriate for mining by performing summary or aggregation operations, for instance)

5. Data mining. (An essential process where intelligent methods are applied in order to extract data patterns.)

6. Pattern evaluation. (To identify the truly interesting patterns representing knowledge based on some interesting measures.)

7. Knowledge presentation.(Where visualization and knowledge representation techniques are used to present the mined knowledge to the user.)

Data Warehouse:

A data warehouse is a repository of information collected from multiple sources, stored under a unified schema and which usually resides at a single site.

Text:

Most of the banks and financial institutions offer a wide verity of banking services such as checking, savings, business and individual customer transactions, credit and investment services like mutual funds etc. Some also offer insurance services and stock investment services.

There are different types of analysis available, but in this case we want to give one analysis known as "Evolution Analysis".

Data evolution analysis is used for the object whose behavior changes over time. Although this may include characterization, discrimination, association, classification, or clustering of time related data, means we can say this evolution analysis is done through the time series data analysis, sequence or periodicity pattern matching and similarity based data analysis.

Data collect from banking and financial sectors are often relatively complete, reliable and high quality, which gives the facility for analysis and data mining. Here we discuss few cases such as,

Eg, 1. Suppose we have stock market data of the last few years available. And we would like to invest in shares of best companies. A data mining study of stock exchange data may identify stock evolution regularities for overall stocks and for the stocks of particular companies. Such regularities may help predict future trends in stock market prices, contributing our decision making regarding stock investments.

Eg, 2. One may like to view the debt and revenue change by month, by region and by other factors along with minimum, maximum, total, average, and other statistical information. Data ware houses, give the facility for comparative analysis and outlier analysis all are play important roles in financial data analysis and mining.

Eg, 3. Loan payment prediction and customer credit analysis are critical to the business of the bank. There are many factors can strongly influence loan payment performance and customer credit rating. Data mining may help identify important factors and eliminate irrelevant one.

Factors related to the risk of loan payments like term of the loan, debt ratio, payment to income ratio, credit history and many more. The banks than decide whose profile shows relatively low risks according to the critical factor analysis.

We can perform the task faster and create a more sophisticated presentation with financial analysis software. These products condense complex data analyses into easy-to-understand graphic presentations. And there's a bonus: Such software can vault our practice to a more advanced business consulting level and help we attract new clients.

To help us find a program that best fits our needs-and our budget-we examined some of the leading packages that represent, by vendors' estimates, more than 90% of the market. Although all the packages are marketed as financial analysis software, they don't all perform every function needed for full-spectrum analyses. It should allow us to provide a unique service to clients.

The Products:

ACCPAC CFO (Comprehensive Financial Optimizer) is designed for small and medium-size enterprises and can help make business-planning decisions by modeling the impact of various options. This is accomplished by demonstrating the what-if outcomes of small changes. A roll forward feature prepares budgets or forecast reports in minutes. The program also generates a financial scorecard of key financial information and indicators.

Customized Financial Analysis by BizBench provides financial benchmarking to determine how a company compares to others in its industry by using the Risk Management Association (RMA) database. It also highlights key ratios that need improvement and year-to-year trend analysis. A unique function, Back Calculation, calculates the profit targets or the appropriate asset base to support existing sales and profitability. Its DuPont Model Analysis demonstrates how each ratio affects return on equity.

Financial Analysis CS reviews and compares a client's financial position with business peers or industry standards. It also can compare multiple locations of a single business to determine which are most profitable. Users who subscribe to the RMA option can integrate with Financial Analysis CS, which then lets them provide aggregated financial indicators of peers or industry standards, showing clients how their businesses compare.

iLumen regularly collects a client's financial information to provide ongoing analysis. It also provides benchmarking information, comparing the client's financial performance with industry peers. The system is Web-based and can monitor a client's performance on a monthly, quarterly and annual basis. The network can upload a trial balance file directly from any accounting software program and provide charts, graphs and ratios that demonstrate a company's performance for the period. Analysis tools are viewed through customized dashboards.

PlanGuru by New Horizon Technologies can generate client-ready integrated balance sheets, income statements and cash-flow statements. The program includes tools for analyzing data, making projections, forecasting and budgeting. It also supports multiple resulting scenarios. The system can calculate up to 21 financial ratios as well as the breakeven point. PlanGuru uses a spreadsheet-style interface and wizards that guide users through data entry. It can import from Excel, QuickBooks, Peachtree and plain text files. It comes in professional and consultant editions. An add-on, called the Business Analyzer, calculates benchmarks.

ProfitCents by Sageworks is Web-based, so it requires no software or updates. It integrates with QuickBooks, CCH, Caseware, Creative Solutions and Best Software applications. It also provides a wide variety of businesses analyses for nonprofits and sole proprietorships. The company offers free consulting, training and customer support. It's also available in Spanish.

Source: http://ezinearticles.com/?Data-Mining-and-Financial-Data-Analysis&id=2752017

Coal Mining: Timeless Black Gems

Coal is an abundant sedimentary rock and fossil fuel used primarily as an energy source for electricity and other industrial uses such as smelting and alloy production. Coal is seldom confused with charcoal, which is primarily of wooden origin. Coal was previously used as mere household heating commodities but when the industrial revolution began, coal mining started to became large-scale. It then became an important commodity to produce electricity as well as to provide primary energy for industries as well as transportation during the 18th century to the 1950s.

Coal mining can be a very dangerous activity most especially when it involves mining underground. Gases produced can be very toxic or highly flammable, capable of explosions which can instantly kill a team of miners. Fortunately, technology has enabled companies the capacity to effectively protect their workers from the hazards of coal mining. But not only that, they can also do the same or even higher output even with significantly less number or workers.

Coal mining can involve mining underground by shaft mining or, for a more accessible and easier way, open pit mining the rock strata coal beds or coal seams. However, there are several other ways in coal mining.

Coals near the surface can be extracted by using open cut mining methods. Explosives are first used to break through the surface of the mining area and after which it is removed by draglines or by shovel and a truck. With the coal seam exposed, drills are utilized to fracture and thoroughly mine it in strips. Area mining involves drilling holes against the surface of the mining area and then planting the drill holes with explosives. When the surface is exposed, there will be a coal seam exposed. This can be extracted, mined and transported with trucks immediately. If it is still hard enough, this can also be drilled and blasted with explosives. The coal can then be collected until there is none left in the strip - then the process can be repeated to create a new mining strip. This coal mining method is most ideal for flat terrain.

One particular coal mining method is controversial. This is the mountaintop removal mining - and just as its name says, it's literally removing the mountain top, making the ridges and hill tops look like flattened plateaus. It is controversial because it drastically alters the topography as well as disturbing the ecosystem. Valleys will be filled the extracted prize and streams will be covered. The objective to coal mining was to extract these valuable energy sources, but is it really worth the damaging the environment or even risk worse consequences?

Source: http://ezinearticles.com/?Coal-Mining:-Timeless-Black-Gems&id=6333094

The Coal Mining Industry And Investing In It

The History Of Coal Usage

Coal was initially used as a domestic fuel, until the industrial revolution, when coal became an integral part of manufacturing for creating electricity, transportation, heating and molding purposes. The large scale mining aspect of coal was introduced around the 18th century, and Britain was the first nation to successfully use advanced coal mining techniques, which involved underground excavation and mining.

Initially coal was scraped off the surface by different processes like drift and shaft mining. This has been done for centuries, and since the demand was quite low, these mining processes were more than enough to accommodate the demand in the market.

However, when the practical uses of using coal as fuel sparked industrial revolution, the demand for coal rose abruptly, leading to severe shortage of the coal output, gradually paving the way for new ways to extract coal from under the ground.

Coal became a popular fuel for all purposes, even to this day, due to their abundance and their ability to produce more energy per mass than other conventional solid fuels like wood. This was important as far as transportation, creating electricity and manufacturing processes are concerned, which allowed industries to use up less space and increase productivity. The usage of coal started to dwindle once alternate energies such as oil and gas began to be used in almost all processes, however, coal is still a primary fuel source for manufacturing processes to this day.

The Process Of Coal Mining

Extracting coal is a difficult and complex process. Coal is a natural resource, a fossil fuel that is a result of millions of years of decay of plants and living organisms under the ground. Some can be found on the surface, while other coal deposits are found deep underground.

Coal mining or extraction comes broadly in two different processes, surface mining, and deep excavation. The method of excavation depends on a number of different factors, such as the depth of the coal deposit below the ground, geological factors such as soil composition, topography, climate, available local resources, etc.

Surface mining is used to scrape off coal that is available on the surface, or just a few feet underground. This can even include mountains of coal deposit, which is extracted by using explosives and blowing up the mountains, later collecting the fragmented coal and process them.

Deep underground mining makes use of underground tunnels, which is built, or dug through, to reach the center of the coal deposit, from where the coal is dug out and brought to the surface by coal workers. This is perhaps the most dangerous excavation procedure, where the lives of all the miners are constantly at a risk.

Investing In Coal

Investing in coal is a safe bet. There are still large reserves of coal deposits around the world, and due to the popularity, coal will be continued to be used as fuel for manufacturing process. Every piece of investment you make in any sort of industry or a manufacturing process ultimately depends on the amount of output the industry can deliver, which is dependent on the usage of any form of fuel, and in most cases, coal.

One might argue that coal usage leads to pollution and lower standards of hygiene for coal workers. This was arguably true in former years; however, newer coal mining companies are taking steps to assure that the environmental aspects of coal mining and usage are kept minimized, all the while providing better working environment and benefits package for their workers. If you can find a mining company that promises all these, and the one that also works within the law, you can be assured safety for your investments in coal.

Source: http://ezinearticles.com/?The-Coal-Mining-Industry-And-Investing-In-It&id=5871879

Data Mining vs Screen-Scraping

Data mining isn't screen-scraping. I know that some people in the room may disagree with that statement, but they're actually two almost completely different concepts.

In a nutshell, you might state it this way: screen-scraping allows you to get information, where data mining allows you to analyze information. That's a pretty big simplification, so I'll elaborate a bit.

The term "screen-scraping" comes from the old mainframe terminal days where people worked on computers with green and black screens containing only text. Screen-scraping was used to extract characters from the screens so that they could be analyzed. Fast-forwarding to the web world of today, screen-scraping now most commonly refers to extracting information from web sites. That is, computer programs can "crawl" or "spider" through web sites, pulling out data. People often do this to build things like comparison shopping engines, archive web pages, or simply download text to a spreadsheet so that it can be filtered and analyzed.

Data mining, on the other hand, is defined by Wikipedia as the "practice of automatically searching large stores of data for patterns." In other words, you already have the data, and you're now analyzing it to learn useful things about it. Data mining often involves lots of complex algorithms based on statistical methods. It has nothing to do with how you got the data in the first place. In data mining you only care about analyzing what's already there.

The difficulty is that people who don't know the term "screen-scraping" will try Googling for anything that resembles it. We include a number of these terms on our web site to help such folks; for example, we created pages entitled Text Data Mining, Automated Data Collection, Web Site Data Extraction, and even Web Site Ripper (I suppose "scraping" is sort of like "ripping"). So it presents a bit of a problem-we don't necessarily want to perpetuate a misconception (i.e., screen-scraping = data mining), but we also have to use terminology that people will actually use.

Source:http://ezinearticles.com/?Data-Mining-vs-Screen-Scraping&id=146813

There is No Need to Disrupt the Schedule to Keep the Kitchen Canopy and Extraction System Clean

After taking over a large and beautiful stately hotel its new owner quickly realised that the kitchen extract system would not be straightforward to maintain because the duct work for the extract system was somewhat ancient and therefore would be difficult to clean.

A prestige hotel needs to maintain a high level of hygiene as well as to minimise the risk of a kitchen fire.

So, if replacing the entire system is not an option what can the new owner do to find a solution that would meet exacting standards of cleanliness and ensure that the risk of a fire starting in the system is minimised while ensuring that the cleaning does disrupt the operation of the hotel and restaurant as a business?

Using an experienced specialist commercial cleaning service to asses the establishment, the types of food cooked, how and at what level of intensity is the first step.

It is difficult without this information to advice on how maintenance should be carried out.

The frequency of the cleaning cycle for a canopy and its components depends not only on the regularity and duration of cooking below but also on the type of cooking and the ingredients being used.

Where  the kitchen use is light canopies and extract systems may only need a 12-month cycle for maintenance and cleaning. However, in a busy hotel, kitchen activity is most likely to be heavy and the cleaning company may advise a three or four-month cycle.

Grease filters and canopies over the cookers should ideally be designed, sized and constructed to be robust enough for regular washing in a commercial dishwasher, which is the most thorough and efficient method of cleaning them yourself.

It's important to make sure when re-installing filters that they are fitted the right way around with any framework drain holes at the lowest, front edge. Of course, grease filters are covered with a coating of grease and can therefore be slippery and difficult to handle. Appropriate protyective gloves should be used when handling them.

The canopies and their component parts should be designed to be easy to clean, but if they are not, provided the cleaning intervals are fairly frequent, regular washing with soap or mild detergent and warm water, followed by a clean water rinse might be adequate. If too long a period is left between cleans, grease will become baked-on and require special attention.

No grease filtration is 100% efficient and therefore a certain amount of grease passes through the filters to be deposited on the internal surfaces of the filter housings and ductwork.

Left unattended, this layer of grease on the non-visible surfaces of the canopy creates both hygiene and fire risks.

Deciding on when cleaning should take place, and how often, is something an experienced specialist cleaning company can help with. The simplest guide is that if a surface or component looks dirty, then it needs cleaning.

Most important, however, is regular inspection of all surfaces and especially non-visible ones. The maintenance schedule for any kitchen installation should include inspections.

Copyright (c) 2010 Alison Withers

A regular maintenance and cleaning schedule is not impossible even in the kitchen of a hotel with an antiquated canopy and duct system with the help of a specialist commercial cleaning company to advise on how to do it without disrupting the work flow, as writer Ali Withers discovers.

Source: http://ezinearticles.com/?There-is-No-Need-to-Disrupt-the-Schedule-to-Keep-the-Kitchen-Canopy-and-Extraction-System-Clean&id=4877266

Commercial Kitchen Ventilation and Extraction - What You Need to Know

There are a number of things to consider when installing commercial kitchen ventilation and there are several different types of systems available - but all must comply with the "Standard for kitchen ventilation systems DW172". A commercial kitchen cannot operate effectively without a properly designed and functioning ventilation system. Getting the design of the correct system for YOUR premises can be complex. All systems are operation and site specific - how you move the air, where you move it to and what you have to do with it to ensure compliance not only with the relevant legislation, but also any local building and environmental constraints.

The factors that may need to be addressed include not only physically moving the air, but heat, humidity, smoke, fire, grease and odour. There are various filter and safety systems available that deal with any or all of these issues and the best system for you will depend on your site, its surroundings and your budget. You may also have to deal with noise from the fan(s) and any planning issues relating to external ducting.

In basic terms a ventilation system comprises a canopy over the production area with a fan linked by ducting to a filter bank within the kitchen extraction canopy which draws the air out to the external exhaust point. The fan is sized in direct relation to the amount of air that has to be moved, where it has to be moved to (the exhaust point) and how quickly (depending on the type of food being cooked).

In addition, mechanical provision must be made to replace 85% of the air that is being extracted. This is called "Make up Air", the other 15% is made up by natural means - general kitchen areas and windows etc.

Within the design, careful consideration must also be given to ensure adequate access for cleaning of the duct and servicing of the fans.

If the production equipment is gas, in accordance with British Standard (BS6173) you will have to fit a Gas Interlock system. This system automatically shuts off the gas supply to the cooking equipment in the event of a failure in the ventilation system.

You may also want to consider the installation of a Heat Recovery unit which reclaims the heat (and some of the fuel cost) from your kitchen that would normally be blasted straight out through from your extracton canopy.

Source:http://ezinearticles.com/?Commercial-Kitchen-Ventilation-and-Extraction---What-You-Need-to-Know&id=6438003

Websites Can Contractually Restrict Third Party Scraping of Their Data

E-commerce service providers can contractually prevent other websites from copying factual information from their website for commercial use, such as for price comparison purposes.

On 15 January 2015, the Court of Justice of the European Union (CJEU) confirmed in a preliminary ruling that websites not protected by a database right, are free to impose contractual restrictions on the use of their data. Interestingly, the CJEU acknowledged that the contractual restrictions could – if national law permits - be imposed through the website’s terms and conditions.

Let’s have a quick look at how this matter arose. Since the early days of online reservations, some websites discovered that they could attract a lot of visitors by comparing the online prices displayed by e-commerce websites selling competing goods and services. Originally such third party websites were called “content aggregators” and today one particular type, so-called “price comparison” websites, is widely-known.  To be able to aggregate such content and create added-value for the consumer, these websites use automated software that visits the e-commerce websites and copies the latter’s pricing information in real time. This practice is often referred to as “screen scraping” and frequently occurs in the online travel reservation business. Some of these third party websites do not only show the compared prices of airline tickets but act as an intermediary for booking travel packages, including car and hotel rental services on top of the airline ticket, often after adding a commission.

In response, low-cost airlines quickly started taking legal action against such screen scraping practices, fearing the loss of such additional, revenue-generating services to these third party websites and also through suffering reputational damage when consumers were not properly informed about issues such as flight changes and cancellations. In these circumstances there was one case between the low-cost airline, Ryanair, and the third party website owner, PR Aviation BV, in which the Dutch Supreme Court made a preliminary ruling request to the CJEU.

The CJEU, in its preliminary ruling on the scope of database protection and contractual freedom, ruled in Ryanair’s favour. It concluded that, in the absence of any database related copyright or sui generis protection on Ryanair’s website, Ryanair was expressly allowed to lay down contractual limitations on the use of its website by third parties. Ryanair would not have had such contractual freedom if its database enjoyed copyright or sui generis database protection (due to the restriction laid down in Article 15 of the Database Directive 96/9/EC). Ryanair’s terms and conditions, to which users had to visibly agree when searching for flights (but without needing to explicitly tick a box), indeed stated that the use of any automated system or software to extract data from its website for commercial purposes was prohibited. Ryanair even went as far as to explicitly state that other websites could not sell its flights and that price comparison websites had to enter into a written licence agreement with Ryanair,
to access Ryanair’s price, flight and timetable information for the sole purpose of price comparison.

As a consequence of the CJEU’s ruling, any website making available mere factual information not protected by any legal right, can still prevent others from using such information through its terms and conditions. Clearly, that website will have to demonstrate under applicable (national) law that the website visitor is contractually bound, in particular because it validly agreed to such terms and conditions. Depending on the applicable law, such agreement by the consumer could be considered as having taken place by ticking a box or merely after having been made aware of the website’s terms and conditions.

The CJEU’s ruling is likely to impact upon the business model of a number of content aggregating/price comparison websites. The ruling’s concrete relevance, however, will have to be assessed on a case-by-case basis.

Source:http://www.timelex.eu/en/blog/detail/websites-can-contractually-restrict-third-party-scraping-of-their-data

Data Mining Services in various types

How Companies Can the Most with Data Mining Services

The modern way to use data, effectively.

Data Mining is an act of transferring data into beneficial Information and actionable insight. Often known as Knowledge Discovery in Databases (KDD), Data Mining is a automated process to uncover a series of never-seen-before information in bulk quantities of data scenario. Post evaluating a series of random factors, which the human mind cannot easily look at or comprehend, it helps in reaching towards an actionable insight by means of progressive mathematical algorithms. These data mining reports are further distributed among esteemed influencers and stakeholders, and are used for enterprise-caliber data mining observations in an insightful manner.

The Process of Data Mining

Here’s a lowdown of a few used cases of how companies are using Data Mining Services in business: ASSOCIATION: Catching hold of frequently appearing observations. For instance, if you want to know which products are regularly purchased in pair, and could be offered together in a combo offer to boost sales.

CLASSIFICATION: Allowing the Data Mining experts at LoginWorks Software to attach observations towards repeated financial patterns of existing groups or categories. For instance, spotting fraudulent transactions or possibly bankrupt companies.

CLUSTERING:Identifying similarities and common ground between observations and groups. For instance, creating profiles for website users or clients by mapping website usage pattern and customer behavior.

DESCRIPTION:Detailing out patterns and showcasing them in a visual manner using explanatory analysis.

ESTIMATION: Revealing features that are difficult to observe with a straight-lined approach because of cost of observation or technical problems. PREDICTION: Predicting an estimated future using previous and present observations. for examples, predicting sales for the next financial period.

What are the Strategic Benefits of Incorporating Data Mining

A Comprehensive suite of Data Mining Services can help your company to:

•    Iron out strategic business problems with the use of number crunching, predictive and inferential analysis.

•    Recuperate your data mining atmosphere by making use of advanced algorithms, artificial neural networks, induction techniques, along with in-data and base-data mining technologies.

•    Automate business trends, understand human behavior and patterns predictions.

•    Do away with complexities of difficult-to-comprehend statistics and, need not necessarily require users to make use of complex applications/interface. Instead, we deliver compact results in the form of touch points, such as Excel, CSV, XML, text file and more.

•    Achieve high-end connectivity and communication capabilities.

The Power of LOGINWORKS Data Mining Services.

LOGINWORKS SOFTAWARES Data Mining Service is an advanced solution for predictive analytics designed to help companies in their strategic decision making. An ongoing process of discovery and interpretation, data mining unearths new and reliable patterns in your accumulated data and patterns, which you can make use of to adhere to testing business questions that calls for constant prediction and inference. With the ever evolving increase of business complexities, as well as the quantity and multiplicity of data, there’s a buzzing need for methods that are intelligently mechanical in nature and are backed by LOGINWORKS SOFTAWARES’ expert support; and data mining that fits the need of today’s businesses aptly. By and large, predictive data mining services makes use of pattern recognition technologies and statistical tools to help accelerate strategic business decisions and lead to more informed conversations with the target audience.

What is offered in our Data Mining Service.

•    First stage of discussion and estimating future direction: If your company would like to gain a competitive edge from our high-calibre Data Mining Services, do get in touch with our sales team at sales@loginworks.com so as to help you in understanding the most advanced benefits and opportunities.

•    Sharing feasibility statistics and studies: If you or your company has a clear view point of how you would want to make use of Data Mining in your flow of business, then do share with us your requirement to ask for a quote.

•    Segmentation and Profitability: Right from assessing the initial assessment to assessing the benefits and completing the data, we’ll share with you a comprehensive report on understanding of data needs.

•    The Final Stage: Data Mining Implementation Service: As soon as the Data Mining requirement is clearly undertstood, we build customized solutions to collect data in an automated fashion and export structured data into usable format.

BIG DATA SOLUTIONS AND SERVICES

Big data swiftly harnesses the ever-increasing volume on data on day-to-day basis and the incessant need of enterprisers to harness the true business value of such data in a quick turnaround time. Opening gates to a world of opportunities to find new and insightful calculations, Big Data can be generated at a variety of myriad speeds and types. This data further lends organizations, especially the burgeoning e-commerce industry of today, a competitive advantage, where estimated predictions becomes the bedrock of constant in-flow of costs and revenue.

LOGINWORKS SOFTWARES BIG DATA ADVANTAGE

Unearth the power of the accumulated data by making significant inroads into the digital revolution of 21st century. Leverage the advantage by using LOGINWORKS SOFTWARES end-to-end Big Data Solutions and Services. Our passion, backed with years of domain expertise and rich technical prowess empowers you to outline a Big Data strategy for your business to help uplift your overall IT roadmap, architect and re-imagine your business strategies. With us, you get the following services: Our all-encompassing  THINK, DEVELOP AND IMPLEMENT model for Big Data Services aids you to pick up the best strategies to adopt and use data. Our principle areas of focus for Big Data services are:

•    Big Data Management for the IT Organization
•    Big Data Analytics for the Business Organization

*change the Think, Build and Operate Model headline with THINK, DEVELOP AND IMPLEMENT model. big data process chart LOGINWORKS SOFTWARES Data Mining Services, also known as Loginworks DataStream is a perfect amalgamation of unlimited volumes, robust technology and matchless expertise. What sets up apart is our one-of-a-kind personalised approach, which makes use of optimal data warehouse technology. IF YOU ARE READY TO TAKE THE ADVANTAGE OF DATA MINING AND BOOST YOUR BUSINESS

– CONTACT LOGINWORKS SOFTWARES TODAY!

Source: http://www.loginworks.com/blogs/web-scraping-blogs/data-mining-services-various-types/