Choose the Best Data Mining Company With This Simple Rule

Data mining is the analysis part of the knowledge finding in databases. It involves finding patterns in large data sets including processes like artificial intelligence, machine learning, statistics, and database systems. The main reason why companies do data mining is to transform a large set of data into understandable block of information that can be used for market knowledge. It allows companies to make informed business decisions.

Data mining was looked upon as a luxury until some time back, but businesses are waking up to the importance of the process by seeing the difference it makes. Most of the multinational corporations already have mining integrated as one of their core processes. Many companies don't make strategic decisions unless they have the complete data converted into useful information using mining techniques. However, it is not a cheap process and would require being put to good use in order to be able to justify its cost. This results in a demand of a data mining company that could fulfill the client's needs by being resourceful and economical at the same time.

Searching for the perfect data mining company for your business could become a lot easier if you follow one simple rule. The rule is to make sure you make enough strategic decisions that result in good profit or at least break even with a single session of mining the data, which allows you to justify the cost you put into the whole process. Then, choose the company that offers you the best quotation which allows you to maximize your profits and improve your business processes even more.

Most companies are not very stringent with their plans and pricing and would be happy to go that extra mile in order to help the client. That extra mile could include offering a discount on the whole process, or offering added services or extended time period in the same package and price as quoted. The way you negotiate with the company will decide the profit that you will make from the entire data mining process.

Data mining will not only improve your business decisions, it will improve your business processes as a whole. If used correctly, it will allow you to extract more out of the limited resources. It allows you to have comprehensive real time market knowledge that always keeps you ahead of your competitors. Therefore, putting in a few extra bucks to integrate it into your core business process is a really good idea. As mentioned earlier, if used correctly then it will not only justify its own cost but also increase profits manifold.

Choose the right company by integrating the whole process in your business and make the most of the market knowledge that is present on the internet. The power to make the best and the most informed decisions lies in your own hands, and data mining is one approach that will certainly get you a lot closer to your business goals.

Source:http://ezinearticles.com/?Choose-the-Best-Data-Mining-Company-With-This-Simple-Rule&id=8784911

Data Extraction Services - A Helpful Hand For Large Organization

The data extraction is the way to extract and to structure data from not structured and semi-structured electronic documents, as found on the web and in various data warehouses. Data extraction is extremely useful for the huge organizations which deal with considerable amounts of data, daily, which must be transformed into significant information and be stored for the use this later on.

Your company with tons of data but it is difficult to control and convert the data into useful information. Without right information at the right time and based on half of accurate information, decision makers with a company waste time by making wrong strategic decisions. In high competing world of businesses, the essential statistics such as information customer, the operational figures of the competitor and the sales figures inter-members play a big role in the manufacture of the strategic decisions. It can help you to take strategic business decisions that can shape your business' goals..

Outsourcing companies provide custom made services to the client's requirements. A few of the areas where it can be used to generate better sales leads, extract and harvest product pricing data, capture financial data, acquire real estate data, conduct market research , survey and analysis, conduct product research and analysis and duplicate an online database..

The different types of Data Extraction Services:

•    Database Extraction:

•    Reorganized data from multiple databases such as statistics about competitor's products, pricing and latest offers and customer opinion and reviews can be extracted and stored as per the requirement of company.

•    Web Data Extraction:

•    Web Data Extraction is also known as data Extraction which is usually referred to the practice of extract or reading text data from a targeted website.

Businesses have now realized about the huge benefits they can get by outsourcing their services. Then outsourcing is profitable option for business. Since all projects are custom based to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure are among the many advantages that outsourcing brings.

Advantages of Outsourcing Data Extraction Services:

•    Improved technology scalability
•    Skilled and qualified technical staff who are proficient in English
•    Advanced infrastructure resources
•    Quick turnaround time
•    Cost-effective prices
•    Secure Network systems to ensure data safety
•    Increased market coverage

By outsourcing, you can definitely increase your competitive advantages. Outsourcing of services helps businesses to manage their data effectively, which in turn would enable them to experience an increase in profits.

Outsourcing Web Research offer complete Data Extraction Services and Solutions to quickly collective data and information from multiple Internet sources for your Business needs in a cost efficient manner.

Source: http://ezinearticles.com/?Data-Extraction-Services---A-Helpful-Hand-For-Large-Organization&id=2477589

Ancient Basic Tools to Green Light Laser: The Evolution of Mining

Mining is the process of extracting minerals and geological materials from the earth. Miners help recover many elements. These materials are rare as they are not grown, agriculturally processed or artificially created. Precious metals, coal, diamonds, and gold are just some of these materials. Mining also helps man to unearth non-renewable energy source like natural gas, petroleum, and even water. The job of miners can be difficult and risky. Thanks to efficient mining equipment, the task is a lot easier now.

People of the ancient time made use of the earth for many purposes. One way to make a living at the time is by mining. Equipment were not fully developed but people managed to unearth many precious stones and different kinds of metals. They use these minerals and elements in making basic tools for hunting and warfare. High quality flints found in masses of sedimentary rocks were in-demand in many parts of Europe. People used these flints as weapons during the Stone Age.

Ancient Egyptians were among the first to successfully get minerals from earth. Their advanced level of civilization made it possible for them to produce quality mining tools. They mined malachite and gold. Malachites are green stones used for pottery and as ornaments. The Egyptians started to quarry for other minerals not found in their soils. They head to Nubia, a part of Africa. There they used iron tools as mining equipment. That was the time when fire-setting was used to extract gold from ores. This method involves setting the rock containing the mineral against another rock, heat it and douse it with water. This was the most effective mining method that time.

The Romans also played an important part in the history of mining. They were the first to use large scale quarrying methods. An example of this is the application of volumes of water to operate simple machinery and remove debris. This is the birth of hydraulic mining.

The demand for metal increased dramatically in the 1300s. This was the time when swords, armors, and other weapons were in-demand. For this reason, miners looked for more sources of iron and silver. There was also an increase in the demand for coins that caused shortage of silver. Iron, on the other hand, was utilized in building constructions. With the high value of these materials, machineries and other mining equipment became in demand in the market.

These machines and equipment were the mothers of the present mining tools that we have today. Miners today use bulldozers, explosives and trucks. More advanced form of mining tools includes the use of green light laser serving as saw guides and machine alignment. With all these modern equipment, miners now have a safer and faster process to break down rocks and even carve out mountains. All these materials are produced and applied with the principles of engineering.

As of today, there are five major mining categories. They are coal, metal ore, non-metallic mineral mining, oil and gas extraction. Oil and gas extraction is among the biggest industries in the world today.

Source: http://ezinearticles.com/?Ancient-Basic-Tools-to-Green-Light-Laser:-The-Evolution-of-Mining&id=6768619

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

I Don’t Need No Stinking API: Web Scraping For Fun and Profit

If you’ve ever needed to pull data from a third party website, chances are you started by checking to see if they had an official API. But did you know that there’s a source of structured data that virtually every website on the internet supports automatically, by default?
scraper toolThat’s right, we’re talking about pulling our data straight out of HTML — otherwise known as web scraping. Here’s why web scraping is awesome:

Any content that can be viewed on a webpage can be scraped. Period.

If a website provides a way for a visitor’s browser to download content and render that content in a structured way, then almost by definition, that content can be accessed programmatically. In this article, I’ll show you how.

Over the past few years, I’ve scraped dozens of websites — from music blogs and fashion retailers to the USPTO and undocumented JSON endpoints I found by inspecting network traffic in my browser.

There are some tricks that site owners will use to thwart this type of access — which we’ll dive into later — but they almost all have simple work-arounds.

Why You Should Scrape

But first we’ll start with some great reasons why you should consider web scraping first, before you start looking for APIs or RSS feeds or other, more traditional forms of structured data.

Websites are More Important Than APIs

The biggest one is that site owners generally care way more about maintaining their public-facing visitor website than they do about their structured data feeds.

We’ve seen it very publicly with Twitter clamping down on their developer ecosystem, and I’ve seen it multiple times in my projects where APIs change or feeds move without warning.

Sometimes it’s deliberate, but most of the time these sorts of problems happen because no one at the organization really cares or maintains the structured data. If it goes offline or gets horribly mangled, no one really notices.

Whereas if the website goes down or is having issues, that’s a more of an in-your-face, drop-everything-until-this-is-fixed kind of problem, and gets dealt with quickly.

No Rate-Limiting

Another thing to think about is that the concept of rate-limiting is virtually non-existent for public websites.

Aside from the occasional captchas on sign up pages, most businesses generally don’t build a lot of defenses against automated access. I’ve scraped a single site for over 4 hours at a time and not seen any issues.

Unless you’re making concurrent requests, you probably won’t be viewed as a DDOS attack, you’ll just show up as a super-avid visitor in the logs, in case anyone’s looking.

Anonymous Access

There are also fewer ways for the website’s administrators to track your behavior, which can be useful if you want gather data more privately.

With APIs, you often have to register to get a key and then send along that key with every request. But with simple HTTP requests, you’re basically anonymous besides your IP address and cookies, which can be easily spoofed.

The Data’s Already in Your Face

Web scraping is also universally available, as I mentioned earlier. You don’t have to wait for a site to open up an API or even contact anyone at the organization. Just spend some time browsing the site until you find the data you need and figure out some basic access patterns — which we’ll talk about next.

Let’s Get to Scraping

So you’ve decided you want to dive in and start grabbing data like a true hacker. Awesome.

Just like reading API docs, it takes a bit of work up front to figure out how the data is structured and how you can access it. Unlike APIs however, there’s really no documentation so you have to be a little clever about it.

I’ll share some of the tips I’ve learned along the way.

Fetching the Data

So the first thing you’re going to need to do is fetch the data. You’ll need to start by finding your “endpoints” — the URL or URLs that return the data you need.

If you know you need your information organized in a certain way — or only need a specific subset of it — you can browse through the site using their navigation. Pay attention to the URLs and how they change as you click between sections and drill down into sub-sections.

The other option for getting started is to go straight to the site’s search functionality. Try typing in a few different terms and again, pay attention to the URL and how it changes depending on what you search for. You’ll probably see a GET parameter like q= that always changes based on you search term.

Try removing other unnecessary GET parameters from the URL, until you’re left with only the ones you need to load your data. Make sure that there’s always a beginning ? to start the query string and a & between each key/value pair.

Dealing with Pagination

At this point, you should be starting to see the data you want access to, but there’s usually some sort of pagination issue keeping you from seeing all of it at once. Most regular APIs do this as well, to keep single requests from slamming the database.

Usually, clicking to page 2 adds some sort of offset= parameter to the URL, which is usually either the page number or else the number of items displayed on the page. Try changing this to some really high number and see what response you get when you “fall off the end” of the data.

With this information, you can now iterate over every page of results, incrementing the offset parameter as necessary, until you hit that “end of data” condition.

The other thing you can try doing is changing the “Display X Per Page” which most pagination UIs now have. Again, look for a new GET parameter to be appended to the URL which indicates how many items are on the page.

Try setting this to some arbitrarily large number to see if the server will return all the information you need in a single request. Sometimes there’ll be some limits enforced server-side that you can’t get around by tampering with this, but it’s still worth a shot since it can cut down on the number of pages you must paginate through to get all the data you need.

AJAX Isn’t That Bad!

Sometimes people see web pages with URL fragments # and AJAX content loading and think a site can’t be scraped. On the contrary! If a site is using AJAX to load the data, that probably makes it even easier to pull the information you need.

The AJAX response is probably coming back in some nicely-structured way (probably JSON!) in order to be rendered on the page with Javscript.

All you have to do is pull up the network tab in Web Inspector or Firebug and look through the XHR requests for the ones that seem to be pulling in your data.

Once you find it, you can leave the crufty HTML behind and focus instead on this endpoint, which is essentially an undocumented API.

(Un)structured Data?

Now that you’ve figured out how to get the data you need from the server, the somewhat tricky part is getting the data you need out of the page’s markup.

Use CSS Hooks

In my experience, this is usually straightforward since most web designers litter the markup with tons of classes and ids to provide hooks for their CSS.

You can piggyback on these to jump to the parts of the markup that contain the data you need.

Just right click on a section of information you need and pull up the Web Inspector or Firebug to look at it. Zoom up and down through the DOM tree until you find the outermost <div> around the item you want.

This <div> should be the outer wrapper around a single item you want access to. It probably has some class attribute which you can use to easily pull out all of the other wrapper elements on the page. You can then iterate over these just as you would iterate over the items returned by an API response.

A note here though: the DOM tree that is presented by the inspector isn’t always the same as the DOM tree represented by the HTML sent back by the website. It’s possible that the DOM you see in the inspector has been modified by Javascript — or sometime even the browser, if it’s in quirks mode.

Once you find the right node in the DOM tree, you should always view the source of the page (“right click” > “View Source”) to make sure the elements you need are actually showing up in the raw HTML.

This issue has caused me a number of head-scratchers.

Get a Good HTML Parsing Library

It is probably a horrible idea to try parsing the HTML of the page as a long string (although there are times I’ve needed to fall back on that). Spend some time doing research for a good HTML parsing library in your language of choice.

Most of the code I write is in Python, and I love BeautifulSoup for its error handling and super-simple API. I also love its motto:

    You didn’t write that awful page. You’re just trying to get some data out of it. Beautiful Soup is here to help. :)

You’re going to have a bad time if you try to use an XML parser since most websites out there don’t actually validate as properly formed XML (sorry XHTML!) and will give you a ton of errors.

A good library will read in the HTML that you pull in using some HTTP library (hat tip to the Requests library if you’re writing Python) and turn it into an object that you can traverse and iterate over to your heart’s content, similar to a JSON object.

Some Traps To Know About

I should mention that some websites explicitly prohibit the use of automated scraping, so it’s a good idea to read your target site’s Terms of Use to see if you’re going to make anyone upset by scraping.

For two-thirds of the website I’ve scraped, the above steps are all you need. Just fire off a request to your “endpoint” and parse the returned data.

But sometimes, you’ll find that the response you get when scraping isn’t what you saw when you visited the site yourself.

When In Doubt, Spoof Headers

Some websites require that your User Agent string is set to something they allow, or you need to set certain cookies or other headers in order to get a proper response.

Depending on the HTTP library you’re using to make requests, this is usually pretty straightforward. I just browse the site in my web browser and then grab all of the headers that my browser is automatically sending. Then I put those in a dictionary and send them along with my request.

Note that this might mean grabbing some login or other session cookie, which might identify you and make your scraping less anonymous. It’s up to you how serious of a risk that is.

Content Behind A Login

Sometimes you might need to create an account and login to access the information you need. If you have a good HTTP library that handles logins and automatically sending session cookies (did I mention how awesome Requests is?), then you just need your scraper login before it gets to work.

Note that this obviously makes you totally non-anonymous to the third party website so all of your scraping behavior is probably pretty easy to trace back to you if anyone on their side cared to look.

Rate Limiting

I’ve never actually run into this issue myself, although I did have to plan for it one time. I was using a web service that had a strict rate limit that I knew I’d exceed fairly quickly.

Since the third party service conducted rate-limiting based on IP address (stated in their docs), my solution was to put the code that hit their service into some client-side Javascript, and then send the results back to my server from each of the clients.

This way, the requests would appear to come from thousands of different places, since each client would presumably have their own unique IP address, and none of them would individually be going over the rate limit.

Depending on your application, this could work for you.

Poorly Formed Markup

Sadly, this is the one condition that there really is no cure for. If the markup doesn’t come close to validating, then the site is not only keeping you out, but also serving a degraded browsing experience to all of their visitors.

It’s worth digging into your HTML parsing library to see if there’s any setting for error tolerance. Sometimes this can help.

If not, you can always try falling back on treating the entire HTML document as a long string and do all of your parsing as string splitting or — God forbid — a giant regex.

—

Well there’s 2000 words to get you started on web scraping. Hopefully I’ve convinced you that it’s actually a legitimate way of collecting data.

It’s a real hacker challenge to read through some HTML soup and look for patterns and structure in the markup in order to pull out the data you need. It usually doesn’t take much longer than reading some API docs and getting up to speed with a client. Plus it’s way more fun!

Source: https://blog.hartleybrody.com/web-scraping/