Retail & Distribution Chain Monitoring

 

Abstract

 

Retail and Distribution mean the purchase of goods in moderately small amounts for use or consumption. Retail and Distribution channel provides the pathway to travel from the producers to customers. Distribution channels depend on the number of mediators required to deliver a product or service. Retail and distribution chain monitoring is a fundamental element of the Supply Chain Management. Retail and Distribution chain is one of the important sectors to make rapid growth in the trade. Monitoring Retail and distribution chain help to understand the market, customer needs, and competition. This process of monitoring is done when the product for sale to the usual world. Data is collected and systematized to understand the pattern, trends, and brands and many other impacting factors. Conclusion obtained from the analysis rapidly consumed by regional and upper management to use in their vital and tactical decision to develop and sustain themselves in the market.

The Different Channel Of Retail & Distribution.

 

  • B2B (BUSINESS TO BUSINESS): This channel is between the business to business. For instance; any company producing mobile need many sensors and components. The deal for this between two companies is a channel for business to business trade.
  • B2C (BUSINESS TO CUSTOMER): channel between the business and the customer is known as B2C. For e.g. any mobile phones used by the customer is sold by the company to the customer/ consumer. Hence it is the channel between Business and customer.
  • B2G (BUSINESS TO GOVERNMENT): Under this channel, the door is open for trading between the government and business. The coal industry is one such example of this channel. B2G channel will give a great development for any country to become stable and developed.


Relation of data scraping with Retail & Distribution Chain Monitoring

 

Data scraping is always helpful where analysis of data is a need. Web scraping provides direct discernibly of data needed to succeed in the retail aspect. The Retail & Distribution Chain Monitoring by web scraping helps you recognize what’s happening at competitor’s tent and empowers you to equip strategy. This helps for the planning of the next strategy and action plan to execute and play the card of an organisation which will make an emperor strong by its roots. Data scraping helps to get data from multiple website data. When it is collected from the various different website and it will make data comparison efficient and planning of the strategy become more efficient in lesser time. Even data scraping save the time for the collection of the data. Market research is made easy when and multiple portal data will help the data authentication. This will open a big door and even the smaller blocked windows by the instant exploring of the current trending data. Hence it becomes easy to decide the deals of the company with regards to B2B, B2G, or B2C.

Goals of Financial Research and Analysis

Financial research or financial analysis is known as the course of assessing businesses, projects, budgets and other finance-related bodies to decide their performance and fitness. One can use financial analysis to check if the business or project or budget is stable or solvent or liquid or profitable enough to permit a monetary investment. On the other hand, Market research is the course of measuring the feasibility of a new good or service through research conducted directly with the consumer. Since this practice is done straight with the consumers, it helps the company to discover the target market and record direct inputs from the customers.

 

Goals of Financial Research and Analysis

 

Profitability – With the help of the income statement of the company, profitability can be measured.

Solvency & Liquidity – Based on the company’s balance sheet, its ability to maintain positive cash flow and its ability to pay its obligation can be calculated.

Stability – Besides the income statement and the balance sheet, other financial and non-financial indicators help find the ability of the company to remain in business in the long run.

 

Method of Financial Analysis

 

Comparing financial ratios like solvency, profitability, growth etc., past performance of the company is recorded. Extrapolating those values, the future performance can be foreseen and can be manipulated accordingly. Data scraping also helps in this when comparing between similar firms.

 

Goals of Market Research

 

Market research is a way of getting an impression of consumers’ wishes, needs and opinions. It can also involve discovering how they act.

Market research can guarantee the success of marketing campaigns, and in-turn sales. It can help the company keep a tab on the competitors. Market research can also help minimize loss in business.

 

Types of Market Research Information

 

Market research typically involves two types of data:

Primary information- the company itself or a third-party company does the research.

Secondary information- the data is already compiled by reports and studies by govt. agencies, trade associations etc. Data scraping helps in collecting the data.

Primary research can be done in a few ways like- direct mail, telephone or personal interviews.

In direct mail questionnaire, response is usually low. 3-5% is the usual response where in telephonic interviews success rate is higher. Speed and cost effectiveness are also advantages for telephonic interviews. However, personal interviews are the most effective form of marketing research. They can also be of two types: A group survey (used mostly by big business) and the in-depth review (one-on-one interviews).

In conclusion, we can say that financial and market research are both very important for a company. The ratios in financial analysis indicates how well the company is utilizing its equity investment. It is also important for small business owners to understand and use financial analysis because investors and outside analysts measure this for a company’s success. Marketing research is needed on a continual basis to keep up with the latest market trends and gain a competitive edge in the business market. Understanding market research and using it to advantage is vital in reaching out to the target audience and increasing the sales.

Reasons for Social Media Monitoring

 

 

Social media monitoring in the general sense refers to the method of utilizing of various devices to pay attention to what is the topic being discussed over the internet and monitoring and controlling media not only from the conventional publishers but on a million of different social networking sites. The practice of social media monitoring is at times also called or related to the terms social listening, buzz analysis, online analytics, social media intelligence, social media measurement or even social media management and the list can go on.

Reasons for Social Media Monitoring

Social media monitoring or social media analytics were previously applied in quintessential sector of companies such as the finance or retail industries who used social media monitoring and scraping to make sure to create brand awareness, improvement of customer services, marketing planning along with the detection and recognition’s of fraudulent. Apart from the mentioned reasons there are a few more causes which gets benefited through the social media monitoring which includes:

  • Measurement of Customer Sentiment

Social media monitoring helps an organisation to know about the position they hold in the social space and also gives a reality check. Through study of the social media one can assess the outlook of the customers regarding a particular product or topic and the viewpoint about the company as a whole by the measurement of their emotions, tone and context. Keeping a track of the customer reviews help the company to grow and maintain customer satisfaction, loyalty of the customers regarding the particular brands as well as their purpose of relation which would further help in the marketing of the campaigns at present and also in the future.

  • Segmentation of the Selected Market

The selected market refers to the bunch of customers which includes organisations, individuals or even households for which a particular company or organisation make designs, execute and preserve the mix of marketing procedures which suits the requirements and fondness of that particular bunch. Organisation and assessing the data-set of social media platform makes a person aware of when and to whom the marketing should be done regarding their services or products. Recognition of more suitable market field helps in the increment of the return on investment.

Monitoring of the online branding doesn’t only refer to paying attention to what the customers have to say regarding the particular products and services of the company but also keeping a check on the various competitors in the field, the press and print media monitoring along with the say of the key opinion leader of the industry. It is not only concerned about just the products of a company but also their customer service management procedure, social engagement, etc.

  • Recognition of Market Trends

Recognition of the various trends in the existing market is important to modify the business planning, keeping the business in the similar rate with the forthcoming changes in directions in the particular industry.

Other than the instinctive internet scraping devices, in the present times a lot of social media channels provide reimburse application program interface to its customers, research individuals, academia and particular organisations such as Facebook and Twitter in the social networking domain.

Media Scraping and monitoring for Broadcast Media

 

 

 

Media scraping is an extremely popular tool used primarily for the extraction of data from various social media sites as wells as blogs and news sites. The most important social media sites that are used for this very purpose are Facebook, twitter, Instagram, snapchat and LinkedIn. These are social media platforms where the majority of the public choose to share most of their private delights and opinions. Through numerous posts of different individuals in the public media scraping which is also known as social media scraping is able to derive data that ultimately aids in revealing and further understanding of various human behaviors, attitudes and habits. This particular information help to determine data about various consumption habit of the publics which helps organizations, individuals, media to understand how their content is being consumed, who are its most enthusiastic consumers and also they can improve their content.

Broadcast media is a group of media focused on producing entertaining as well as political and relevant contents. The success of broadcast media chiefly depends on audience reaction. What the audience thinks and wants influences the work of this group. Broadcast media traditionally includes television and radio but now also includes certain digital media platforms. The broadcast of different kinds of new totally depends on how the audience. For example the evenings are mostly reserved for the relaying of the most topical news and discussions around the world because that is the time when majority of the working population returns home and switches on the television or the radio. It also depends on who is watching what kind of content. Indian television serials mostly portray traditional Indian domestic scenes as housewives and old people are most likely to sit around the television and while away their time watching these contents.

Media scraping is extremely essential for the broadcast Medias.

 

The different ways in which media scraping monitors for the broadcast media are as follows –

 

  • The media scraping helps in determining the kind of content the audience is craving. By this the broadcast media is inspired to create content centering those topics. What the audience wants is crucial for the success and effect of the broadcast media.
  • The media scraping helps in assessing how satisfied the audience is with the present content. This aspect is also very important as this helps the broadcast company to understand the quality of content they are producing and how effective and impact they are.
  • Another crucial data that media scraping extracts is what the present content is lacking. This lack helps immensely in the determining of what more needs to be included in the future content.
  • The data also helps in understanding what kind of platform the audience prefers while consuming content – digital or traditional media
  • Media scraping also helps immensely in figuring on which days, at what part of those days a certain kind of content is likely to be consumed. Another crucial data that media scraping reveals is the amount of time the audience devotes to those contents.

The collaboration of media scraping and broadcast media is extremely crucial and critical.

Techniques of web scraping you should know

 

 

 

It’s a process of extraction of data from various websites. It’s a variant of data scraping. The data extracted is then used for analysis. Web scraping involves fetching a web page and then extracting the data from it. Web scraping is used to understand the trend of the market, to understand your competitors and their pricing and then get ahead of them. Web scrapers typically take something from webpage and then use it for other purposes. The data may be parsed, reformatted or put in a spreadsheet etc.

Techniques of web scraping

Web scraping is the process of automatically collecting information from the World Wide Web. Following are some of the best web scraping techniques that can be used for collecting information: –

  • Human copy and paste – Sometimes a better technology than any ever created. Usually websites don’t want their data to be scraped. For these sites, human touch can do the trick.
  • Text pattern matching – It’s a very simple yet powerful approach. It’s based on UNIX grep command or regular expression matching facilities of programming languages.
  • HTTP programming – HTTP requests can be posted to the web server to retrieve static and dynamic web pages.
  • HTML parsing – websites generally have a large collection of pages generated dynamically. Same category data are usually encoded into similar pages by a common script or template. To parse HTML pages, languages like HTQL and XQuery can be used.
  • Dom parsing – by embedding a full-fledged browser, programs can retrieve the dynamic content generated by client-side scripts.
  • Semantic annotation recognizing – the pages being scraped may embrace semantic mark-ups and annotations. These can be used to locate specific data snippets.

Conclusion

Web data scraping in modern times has advanced the internet usage, marketing and management to a whole new dimension. The job which demanded days can be finished within few seconds. Extensively used in marketing and artificial intelligence analysis it’s importance cannot be ignored.

Finance And Marketing Research

 

 

 

Web scraping is an efficient method for organizations to reduce the workload upon people involved in the analysis and study of data. It involves analysis, storage, and the organization of data regarding specific topics which is found by scanning through digital media and them downloading this information into directories that are stored on computers or in databases.

It is very useful for understanding and collecting financial data as this information would otherwise involve large amounts of research to identify. Financial activities include a number of avenues which can include large amounts of data, and a wide range of activities. Often, the financial activities of a single organization may be handled by a large number of people or units simultaneously. Data scraping makes it easier for the coordination and management of these activities, as well as to maintain clear and ordered records of all data.

Financial activities are one of the central processes which are associated with all organizations and are hence it is vital to have proper management. In terms of research, it is easy for organizations to gather relevant information using scraping. It can be used to understand current trends, reactions of consumers, and analyse what actions and decisions should be taken.

 

Marketing Practices

 

Marketing is another key area where organizations can benefit from data scraping. A lot of marketing practices are very dependent on how consumers react to certain actions and behaviors. Moreover, marketing practices are many and varied and there may be different activities which are appropriate for different groups of people. Data scraping can be used to consolidate information about various trends and demands which are found in the market and to use it to analyse how an organization should proceed with its marketing activities. It is even more important in the initial stages of the development of an organization because marketing plays a key role during launch periods. At such times, there is a large amount of research and data analysis which goes into planning their activities. These activities would be highly strenuous and time consuming If done manually. It can also help in greatly reducing the amount of time that must be put into consolidating and coordinating information between various sources. This is a key issue for a number of large organizations having numerous functions, and for organizations that are dependent on current market activities.

Research is in itself a very strenuous process which involves a large amount of attention and precision which is better achieved by using digital methods. Moreover, there are many sources and a large number of further links that may have relations to the same type of information. In these cases, financial and marketing related research can get very complicated and hard to keep track of for individual people. Scraping can greatly improve the quality and quantity of the research as well as help in the simultaneous categorizing and storing of this information. Finally, it is safe to say there is too much information and data relating to marketing and finance which may be needed for an organization and this research can be greatly simplified by using data scraping and related technology.

Data scraping: Jeopardy or bliss for compliance and risk management

 

 

 

Compliance and risk management

 

Compliance and risk management are closely associated with each other. To differentiate them there is a very thin borderline but, both the term protects the organisation from risk and helps to grow by guesti-mated risk to achieve the goal.” DATA scraping is the process of collecting data/ set of instruction from a website to your pc with a help of a local file. It widely also known as the web scraping OR screen scraping.  To associate compliance and risk management with screen scraping might be the jeopardy or bliss to a company.  The two sides of the coin can only be judged once you know the traits and objective of the company. How well research that web scraping is? Or how the source is reliable for that specific industry?  The biggest question which can come to anyone’s mind is that will taking a risk on this web scraping worth or not. Web scraping itself is already a long time taking the process to understand and learn.

In an organisation, risk factors work in every possible manner. Many big companies have different executive for study and research purpose for their market. Here, web scraping might be helpful to do research and collect the data from the various website. Data scraping will be very helpful to people or officials who can recognize the risk and its fragment for the market and an organisation

DATA scraping is an emerging technology which will help every industry inclined or dependent on data. Compliance and risk management is one of those fields where they have to depend on the data to stay in competition or to become a brand. And institutions need to be careful to not lump. However, understanding their similarities and realising how to align and allowing producing the gains from compliance and risk management being in sync. Compliance and risk management assist as a repository for all rules, regulations, and contracts with tracking and monitoring to study it market culture with help of data scraping. Estimating the truth of prospective data and market of an organisation helps to grow industry with a larger perimeter.  Data scraping with the authentication of data will help each and every industry. The analysis will be more easily executed and taken into consideration. Even the data security plays an important role in risk management and compliance.

Compliance and risk management is an important factor of a business to sustain it demands technology to increase operational values and trustworthy. Web scraping provides an intelligence eye to analysis in the field of compliance and risk management. This eye will help grow the business industry and get a better idea of tomorrow.

Competitive Pricing Intelligence

 

Competitive Pricing Intelligence Solutions recover product and pricing information from market leader websites including their competitors and change necessary details. It helps an E-commerce business remain one step ahead of the market competition. Pricing tools assemble and screen competitive data shifting it in to intelligence. They draw data at scheduled interval of time with automation – tracking competitor’s online presence. Pricing intelligence contains tracking, monitoring and analyzing pricing data to understand the market to make educated pricing changes at speed and scale. Since product pricing fluctuates randomly, retailers need to continually monitor their relative price position and include changes. However, this doesn’t mean dropping the price just because a competitor does.

 

Importance

Price Intelligence is necessary for retailers, for several key reasons:

  • Increased consumer price sensitivity.
  • Increased aggressiveness from competitors.
  • Increased price transparency.

 

Application

There are a few steps to apply Competitive Price Intelligence.

The old-style model of monitoring price changes manually is inefficient, time consuming and often inaccurate. The vast amount of existing data makes it more difficult to scale. So, data collection needs to be scalable. As a company grows, its number of SKUs, channels and competitors to monitor grows with it. This is where automation comes in convenient, as the retailer won’t have to repeat those time-consuming and inefficient processes over and over again.  By automating competitive pricing analysis, retailers can obtain exact pricing data in a timely manner. This frees up valuable time and resources, eradicates potential human error, and delivers relevant and accurate information. Data Scraping software help in automating also.

Retailers can make quicker response and decisions depending on the data and outperform their competitors based on market trends and behaviors. Say for an emerging clothing brand, competing with big, established brands, any bit of intel is a big deal. It wants to know which of its competitors sell basic shirts, when, and with what offers and shipping options. Seeing this, the emerging cloth brand can offer something similar, or be more creative to persuade the consumers to buy the brand or make a switch.

Pricing intelligence is nothing without immediate action. If a retailer collects a heap of data about the price of sweaters in December, but analysts review the data in May, it is way too late. On one hand the prices are irrelevant five months later, and on the other hand, no one is going to buy sweaters in the middle of summer. Retailers need to act on data as and when the market changes, not six months later. If a retailer notices a spike in sweater sales in December, it needs to react at that time. It does not matter if it’s creating its own sale or sending out promo deals and coupons. The benefits of acting on more accurate data faster can mean an increase in sales and getting new customers.

So, it’s necessary to implement a dynamic pricing strategy that can swing based on the latest and greatest competitor visions. Retailers should use pricing intelligence to manage its relative price position in the competitive market, anticipate margin pressures, and boost revenue at the same time. If it doesn’t, it’s certain that its competitor will.

Steps to open a CSV File in Excel without breaking it or formatting

 

1.  Open a blank workbook in Excel

2.  Chose “Data” -> “From Text”.

 

3.  Select the CSV file to open.

4.  In “Text Import Wizard – Step 1 of 3”, chose options “Delimited” and check the box “My data has headers.”

 

5.  In “Text Import Wizard – Step 2 of 3”, check “Comma” as Delimiter and select double quote symbol as Text qualifier.

 

6.  In “Text Import Wizard – Step 3 of 3”, with the first column in the “Data Preview” selected, scroll across to the last column and select it while holding the SHIFT key (all columns should now be selected). Then select “Text” as the Column Data Format and click “Finish”.

 

7.  In the final step under “Import Data”, select “Existing worksheet:” and click on “OK”.

 

You should now have a spreadsheet with the imported data but without Excel breaking the formatting required and all values as text. Remember to export the file from Excel to CSV again if you have made changes in the file.

Data Scraping – Make the Best of Data

 

 

Description

Data scraping or more preferably web scraping is extracting data from a website into a local file or spreadsheet on your computer. It is a method of importing information to a human-readable output. Data scraping also termed as Web Harvesting or Web Data Extraction is employed to extract a large chunk of data and save it to a database in spreadsheet format. It is most efficiently used to collect data from various websites. Even data scraping helps in channeling information from one website to another. Generally, data transfer from one program to another is totally computer-centric. No involvement of human interaction is required. Data scraping is generally considered, inelegant technique, often used only as a “last resort” when no other mechanism for data interchange is available. Data displayed by websites can only be seen using browsers. There are no functionality of the option for saving an offline version in your device. One has to manually copy and paste the data which is a very tedious and time-consuming job It can take days to extract data and import it to a local file in your device. To curb this problem and to make the process easier data scraping software is used. They perform the same task within a fraction of second. This web scraping software would automatically load and extract data from multiple sites depending upon your preference and requirements. Just one click away you can file and document the information directly from the websites. The basics for web scraping is relatively easy to master.

Popular uses of data scraping

Data scraping is used popularly to channel constructive data from website to another or from multiple websites to your local file on computer. Data scraping Popular uses of web data scraping includes

  • Research purposes- Generally when we intend to do research on a particular topic, this technology comes handy in analyzing and channeling data directly between various websites offering you the information as per requirement.
  • Comparing cost and price change monitoring – It is also used for travel booking of tickets in various price comparing sites.
  • Contact scraping- It is used to obtain access to customer’s email account for marketing purposes.
  • Sending product details from an e-commerce site to another online vendor.
  • Weather data comparison.
  • Gathering real estate listings.
  • Web data integration and web mashup.

 

Technique

Web scraping is process of automatically mining and extracting information from internet and document it. The field is actively developing. It ranges from fully automatic computerized programs to programs requiring human-computer interaction. Data scraping are structured on basis of- Human manual copy-and-paste, Text pattern matching, HTTP programming and parsing, computer vision webpage analysis and so on.

 

Dark side of Data Scraping

Despite having the positive views, data scraping technology gets abused by a small proportion. The most prevalent misuse being email harvesting leading to scamming and spamming of email addresses of the customers. There is an ongoing legal battle prevalent between the data scrappers and website developers.

Conclusion

Data scraping in modern times has advanced the internet usage, marketing and management to a whole new dimension. The job which demanded days can be finished within few seconds. Extensively used in marketing and artificial intelligence analysis it’s importance cannot be ignored.

Website Scraping – Extract Your Data

 

Website scraping, also known as Web Data Extraction, Web harvesting or Screen Scraping is the process of extracting large amounts of data from any given website, which is then stored locally in the local disk of the computer or in the form of a spreadsheet format. Data that is displayed by most websites can mainly be used for the purpose of viewing by consumers. These data are not open for copying on a large scale process locally. In such cases, one might be forced to copy the relevant data and simply paste in the computer file location. However, this is a tedious job as it takes up hours, days and even months, depending on the size of the date needed to be downloaded. This is where website scraping comes into the picture. Website scraping helps to automate this process of copying and pasting by loading and extracting the relevant data from many website pages at a single time, thereby saving man-hours and manpower.

The various techniques of Web Scraping

  1. Human copy paste – Some websites set up intricate barriers that do not allow Web Scraping to mine data from those websites. In such cases, human copy-pasting is the only method that comes in handy to get the desired data.
  2. Text Pattern Matching – The UNIX grep command or regular expression-matching facilities like Python offer simple methods of matching texts that have been set to be mined from the data, thereby facilitating easy web scraping.
  3. HTTP programming – In the case of static and dynamic websites, socket programming is used to post HTTP requests to the remote web servers to allow seamless data mining.

Benefits of Web Scraping

  1. Businesses require data on e-commerce websites to learn about the prices, discounts, and quality of products provided by them to get a better idea about their rivals and improve their own situation in the business market.
  2. Data mined regarding an individual or a company can be later used for statistical processes like analytics, comparisons and even investment decisions in the future.
  3. All websites depend on the choice of the consumers. The reputations of the websites depend on the liking of its users. So, by scraping data from the social media pages, the online website company can get a clear picture about its position in the market, what changes it must accomplish in order to satisfy customers and draw in new customers into the website.
  4. Online shopping mainly depends on past reviews. In order to catch fraudulent fake reviews that may affect the business in an adverse manner, web scraping comes into play to detect and locate such fake reviews.

Competitive And Pricing Intelligence

Pricing intelligence using data scraping

Price intelligence is also known as competitive price monitoring. It is the awareness about the market price and how it impacts the business. Modern techniques like data mining and data scraping are used to analyze the information. Price intelligence is useful as it gives information on increased consumer price sensitivity, increased competition among the competitors, and increased price transparency. Price scrapers or price bots provide pricing intelligence solutions. Price scraping is a technique used to lift off the pricing data from the e-commerce websites. Competitors use this data scraping technique to steal the dynamic data regarding the pricing. Many tools and technologies like cURL, HTTrack, Scrappy, Selenium, Wget, PhantonJS, and so on. The scrapers can also use third-party scrapers to target the data. They target multiple websites, pull the pricing, and catalog information and sell it to the competitors. Price intelligence has various advantages like optimization of pricing strategy, improvement of the in-store experience, boost pay-per-click, repricing etc. Scraping is done to analyze the website value of target and competitors and competitive edge.

The competitor can completely analyze the data provided by the data scraping technique and override the pricing strategy by undercutting the prices. An entrepreneur can achieve success by using the data scraping tool. The company can also many customers by reducing the price of their products or services, compared to the competitors.

But price scraping has its disadvantage. There is a huge drain of information from the websites. The companies that use data scraping techniques illegally must also deal with scrapers and competitors in the court.

Competitive intelligence using data scraping

Competitive intelligence is the process of defining, forming, analyzing, and distributing data and information about the products, customers, demand, competitors, and competition. This data would help the executives and managers in taking a strategic decision for the company. It is a legal business practice so, you need to worry about court and privacy case.

With the increase in technology and advancements, many companies have been established. Many budding start-ups are also coming into the play. If a company wants to stay on the top of the leader board, then it must use the technology. Data scraping is the latest technique used to extract data on and about different companies.  Web scraping is done to gain information on the competitors. Having data about your competitors would serve as a huge advantage.

Data scraping would give you all the information about the market and competitors.

Assessing the Data like a Data Scientist

 

What is data mining?

Today everyone is behind data; whoever has big data rules the world. Companies pay a hefty amount to data mining firms and data scientists to gain hold of data.

Like the name suggest this means digging of data, the process of extracting usable data from a large set of any raw data, it means analyzing a large chunk of data with the help of one or more software. The application of data mining can be executed in multiple fields, such as research and science.

Businesses can learn more about their customers and develop effective strategies to leverage resources in a more optimized manner. Data mining uses sophisticated algorithms to evaluate the probability of future events.

What data can do?

Since last decade there have been advances in the speed that enables us to move beyond the traditional and time-consuming practices to automate data

analysis. Complicated data have the potential to unravel relevant insights. The major consumers of these data are banks, manufacturers, retailers, and telecommunications providers.

The techniques to mine the data have become more sophisticated, because of data we’ve been looking ahead by mapping out patterns into the future. Data mining does not work by itself; it discovers hidden information in gathered data.

Data mining won’t give out all the Information; it discovers predictive relationships which are not necessarily causes of behavior. For example; data mining will determine that males with income of 30000-60000 who have certain subscriptions will buy a given product. This information will help companies to develop a targeted marketing strategy; however, data only will give the leads that a consumer might be interested in the product but it doesn’t say that they will buy the product because they belong to this population.

Which tools can be used to mine data?

There are several tools to mine data, some of them are open sourced and some are paid. Here are a few tools which can help in mining the necessary data.

  • Rapid Miner is one of the best and open source tools to predictive analysis, this tool can be used for a various range of applications including for business applications, research, machine learning, and commercial application.
  • Weka also known as Waikato Environment, this software is based on the freemium model. This can be used for data analysis and predictive modeling, this software contains algorithms which supports machine learning.
  • Sisense is licensed software. This is extremely useful and suited when it comes to internal reporting within the organization. This software helps in generating highly visual reports; these are specially designed for non-technical users.

Data mining solves few problems and will lead companies to their customers by analyzing data which are already in the database, but this also takes the right skills and tools to execute and get desired results.

The scope for finding the necessary findings will be ever greater, companies as long as they can figure out how to mine and execute it effectively. Businesses will be able to learn about their consumers, the tools will help to make business decisions with the gathered data.

Web Scraping the Easy Way – Know the Basics

Web Scraping is also known as Screen Scraping, Web Data Extraction, Web Harvesting etc. is a technique that is used to extract large amounts of data from websites the data is extracted and saved to a local file in your computer or to a database in a spreadsheet format. Web Scraping is the technique of automating this process in which the Web Scraping software will perform the same task within a fraction of the time instead of manually copying the data from websites.  The act of data extraction which is done manually, automated and gives the higher quality output.


Web Scraper

 

Web scraping is done with a software that simulates human Web surfing in order to collect specified bits of information from different websites and helps to collect certain data to sell to other users, or to use for promotional purposes on a website. Website scraper is the software that extract the data from multiple number of pages as per our requirements. Web scraper automatically identifies and fetches the patterns of data and scraps or reformat the data whenever repeated. It automatically extracts the data from multiple data. The web scraper downloads the image for the automated processes.  A web scraper can even ban the computer from accessing the data. This scraper helps to collect the data and create our own data.

Work

The work of web scraping is done with the webs scraper bot for which the operators invest in serveries for the data being extracted. A web scraper  bot is the software program that typically runs automated tasks with unattainable great speed.


Techniques

 

There are many techniques of web scraping.

  • Text pattern matching

Text pattern matching is basically the checking the sequences of data among the raw data, to extract the exact match.

  • HTTP programming

HTTP is the Hypertext transfer protocol that is the protocol that transfers the information between the computers and encrypt and decrypt their data according to the requests.

  • HTML parsing

HTML parsing is the software used for Hypertext Markup Language. HTML is the process for the analysing of data for storing.

  • DOM parsing

The Document Object Model (DOM) is the interface that allows to access and update the information used in the XML documents and with up-to-date style, text and pictures.

  • Computer vision web

Computer vision web is the ability to understand visual data, and interdisciplinary field. It seeks to acquire, process, analyse, and understand images.


Benefits

 

  1. Its enables to scrap product details. Boost analytics to extract all the data.
  2. Nothing can be hidden. The data can be scrapped which is further used in investment companies, analyzing companies, etc.,
  3. In helps in shilling. Shilling is an activity that aims to detect the fraudulent activities for the betterment of the company. Therefore, it enables the company to reduce the spamming so that no fake comments or data is present on the online portal of the company.
  4. It enables to update the portals of the company so businesses are able to update the data instantly with the help of data scraping.
  5. The extraction of data that is the data scraping helps to save the data into a single location.

Data Mining – Extract Useful Data

 

Data. It’s something that everybody has and everybody wants more of.

 

 

Over time, the amount of data in the universe has piled up in huge amounts, with more and more being added to the pile every day. Now, the term Big Data is being used to describe data that is extremely vast and cannot be easily measured.

Every company needs data to function- whether it’s based on customer reception to a product or service, or client-based information or data within your own system. Sometimes it is freely available and easy to get, but sometimes you have to dig a little deeper. Usually, a data scientist or analyst is hired to do the job of digging up data.

But the truth is anybody can do it. You don’t necessarily have to be a data scientist to do the job. This is where the concept of data mining steps in.

What is Data Mining?

In simple terms, data mining is a way to extract useful data from a large pile of raw data. It also involves checking or analyzing patterns in the data you’re collecting, using various kinds of tools and software.

You could use a tool like a web crawler software, for example, to extract the data you’re looking for.

Let’s take a look at the various other tools you could use to mine data.

Tools Used to my Data

Data mining software can either be an open source or a paid mining tool. Now, an open source tool is freely available, sure, but you might need to have the good coding knowledge to use it. The paid tools are a lot easier to use and give you immediate results. There several out there to choose from, but it’s important to choose one that meets your needs.

Understand what kind of data you need before you move ahead. If you’re going to go for data from your own system, then you can probably go ahead without expecting trouble. But if you need to go for data outside, then you might have to use a proxy server to cover up your footprints.

Now that you’ve chosen a tool and understood what kind of data you need, it’s time to take a look into the actual mining process.

Mining for Patterns

As mentioned before, the most important part of mining data is looking for a set of patterns.

There are various kinds of pattern. Some common ones are Association Learning Patterns, Anomaly, and Cluster Detection.

Association Learning consists of looking for patterns where you find items that are often bought together. Let’s say a man wants to buy a mobile phone, he might also want to buy a phone cover or a memory card. You find out which items customers usually buy together and then offer it next time a customer chooses the item.

Anomaly pattern is when there is a complete deviation from the usual selections. A Cluster pattern is when you categorize a customer under one cluster that has the same buying patterns. This helps predict what they usually buy and offer something along the same line.

Importance of Data Mining

Hence Data Mining is an important tool for businesses to understand their customers and for several other measures like database marketing and upselling their products.