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Leveraging Big Data for Ecommerce business

Recent shift in consumers’ acceptance of the benefits of online shopping experience puts greater stress on retailers and their strategies. Online shopping gives a stress free and uncrowded environment that ecommerce business offers from last few years. All activity in ecommerce business is done in internet world and hence, it generate a huge amount of data i.e. big data.

Big data is a huge collection of data comes from different sources such as social media, web browsing, and many other sources. Companies leverage these data to find useful information from it.

The most powerful impact of big data on business is identify hidden pattern and decision support. Decision making based on data insight always have a better probability of success than the decisions based on guess or gut feel.

Nidhi Agarwal, Founder and CIO, KAARYAH adds, “Big data makes a lot of relevance for ecommerce companies who want to stay agile and relevant to their customers. The companies are monitoring customer consumption patterns and convert them into product level inputs to improve products and introduce new products. Also, the speed of consumption combined with our agile production system leads to large working capital efficiencies.”

There are many areas where ecommerce companies leveraging big data and enjoying its benefits. Some of the area where ecommerce companies gaining benefits by leveraging big data are:

Data driven decisions – Almost all marketing or product related decisions is based on real time or near real time data analysis result. For making any decision, there should be a strong base behind that. Always decisions based on real time data information is more effective and fruitful.

Personalized offer – Analysis of data helps ecommerce companies to target their right audience in more effective ways. It helps customer to find what they want and as the result sales always become faster. Companies provide custom offers on the basis of customer interest and preference based on their earlier shopping history combined with their multiple other data sources. According to Amitabh Mishra, CTO, snapdeal “We have total 14 properties like ‘Viewers also viewed,’ ‘similar products,’ ‘trending now’, etc. on site for every viewers or customers who visited our website and the big data platforms when put together influence 40% of the orders we receive today”. It shows the strength of big data in ecommerce.

Supply chain management – Supply chain optimization is one of the most critical success factor of ecommerce business. Companies often leverage big data for their supply chain also. Using big data analytics, ecommerce companies plan their delivery route, reduced cost, preferred time for delivery and many more.

Fraud detection – Big data also helps in detecting fraudulent by analysing patterns, payment methods and browsing history. A report published by Aberdeen – a fact based research company says that after analysing different types of frauds and companies behaviour it came in picture that 16% of respondent say that detecting fraud was a primary use for their analytic suite.

Organized data – Organizing the data coming from multiple sources is also a big challenge in ecommerce business. All data need to collect, store and organize for the further use. Big data helps to find the way to organize data and enable business people to find useful insight from those data and apply in day-today decision making.

If you are in ecommerce industry – yes, leverage big data analysis for business decision. It really does not matter the size of your business today. Big data is one of the most important success factor of ecommerce business and by applying big data analytics, ecommerce you can make better business models to drive up sales day-by-day.

How Big Data can revolutionize social welfare?

Today Big Data is changing the way of our thinking. It’s changing the way of living and working. We are leveraging Big Data in our growth so that everyone can contribute and take advantages. The big data analytics makes life easier and more goal centred. Analysing huge amount of data gives us more accurate decision making ability. With these benefits it is also affecting our social life. Our social life can revolutionize after applying the big data analytics. There are many area from which Big Data can revolutionize social welfare. I am listing out some of them with reasons that how it can revolutionize social welfare.

Online life will be safer– Now a days everything went online. Our life is almost dependent on online services. From Shopping to Education, Transaction and many more we used online services. But this method is no more so safe. Others may hack your information and misuse those data. Big data can help us in this problem. By analysing the hacker’s pattern it can improve the security of your website.

Education– Today’s education cost is rising twice than any other sector. So we need to find an alternative of these traditional education system. Big data can help us to provide these study materials online. So that all could have easily access to the education.

Health Care– The most impact of big data on our social life is in healthcare sector. It helps doctors to find the pattern of any disease and on the basis of that pattern medicines for that disease can be invented.

Transport- The advantage of big data is also in transportation. In transportation there are multiple of uses of big data from analysing the traffic to road safety and security purpose. Data scientists can find the behaviour of people on road. By analysing the transportation data the pattern of accidents can be identified and their solutions can be generated.

Career opportunities- There are many websites which help job seekers and employees to find their jobs or employees. Job-seekers find the opportunities according to their skills and employees used to get their best meet on the basis of candidates skills

Business future- To plan the future of our business we need to go for big data analysis. Those business decision will take your business far away from your competitors because those decision will be based on the real experience of your customers.

Weather forecasting- Big data can also help our social welfare in weather forecasting. It will give great benefits to all but specially to farmers because most of time they dependent on weather. So use of big data in this area will revolutionize the whole society welfare.

Big data creates a lot of opportunities for every sectors people just need to catch those opportunities for the development of their own and as well as society. One more great use of big data towards revolutionize social welfare is in anti-poverty programs. Big data helps to create difficult policies for the anti-poverty programs. For these type of applications a large database set is needed and linked to different social data sources to get huge amount of information regarding our social life. Then only we can apply these benefits to revolutionize social welfare.

How to Hire Right Big Data Resource

Hiring right talent according to the need is the key factor for a company to be successful. “A good fit for the job equals a good fit for the company” is one of the most appropriate quote during hiring a resource.

Big data value chain is mainly divided in three steps. They are data integration, Big data development, and Big data analytics. We need different skilled resources for these three different phases. A person should be hired when his skills meets the needs of the requirement. Let’s look at these steps one by one..

  • Data Integration– As we know that in Big Data, data comes from multiple sources. Connecting these data from different sources leveraging big data technology through big data lab, Amazon web services etc. for collecting data and ingesting to the operations is called Data integration. Data coming from different sources have to connect with the appropriate technology. We need ‘Big Data Admins’ for this purpose who will able to make connection between these two, they must know how to use different data integration tools i.e. Sqoop, Flume, etc.
  • Big Data Development– Data comes from different sources in structured, semi structured and unstructured form. Those data need to be stored in an organized manner so different development tools can read it for processing. We need big data developers for this purpose who knows the different data processing technologies like Hadoop, Informatica, Teradata, etc. Their work is to make the data to be readable by data processing technologies. They should also know about different database in which data will be stored.
  • Big Data Analytics– This stage contains data processing and converting the processed data for the decision support. Data analysts and Data scientists work in this phase for analyzing data to find out hidden pattern in the data and build statistical models. One of the favorite definitions for data analyst is “A data analyst is someone who is better at statistics than any software engineer and better at software engineering than any statistician.” – Josh Wills” This one line defines the characteristics and needs of a data analyst. A data analyst must be good at problem solving. Companies generally prefer engineering, statistics or computer science background people for this role.

To summarize, some of the key skills needed for Big data team are as follows:

  • Hadoop– It is one of the famous big data working framework. Big data people must know this framework.
  • NoSQL– On the operational side of Big data field distributed storage like HBASE are used. To work on these databases NoSQL should be known to the person.
  • Statistical analysis– This is one of the important skills to be in a big data person. They should be familiar with different statistical modelling tools like R/Revolutio, SAS, SPSS, Alteryx, Mahout Libraries, Matlab and there are many more
  • Data Visualization – Person should be familiar with different visualization tools like Tablueau, Spotfire, Qlikview, Rapid miner, MS Excel, etc.
  • Programming language– Person to know the general purpose programming language like c, java, python, etc.
  • Problem Solving– A big data person must be good in problem solving. So, they can find the solutions of different problems during the analysis.

Big data is comparatively a new field with a lot of opportunities. During hiring process, Companies need to pay attention to what they wanted and go for that. Though, it is not advisable to find people having expertise in all big data tools in three phases mentioned here and it is not necessary. But, it is important that people have a bend of mind for learning new tools.

Hadoop: Cost effective way to process Ecommerce data Processing

Companies are vying different ways of discovering the value of letting customers create their own unique products. Almost all e-commerce giants leverage Big Data to present a personalized set of products to their customers and Amazon is a successful example.

Now, let us look at how small and medium size retailers can explore the driving force – big data, and how Hadoop can help in this journey.

Hadoop is an open source tool for processing big data. It is an open source framework where data can be stored and processed. It is one of the most used and highly ranked platform for big data processing. Hadoop brings many advantages while applying it in processing of big data. Hadoop allows users to handle increasing volumes of data quickly and efficiently. That makes it friendlier with retail sector –ecommerce as well. There are many practical advantages of using Hadoop.

Hadoop having two parts in its core, one is HDFS (Hadoop Distributed File System) for data storing purpose and other is MapReduce for processing data. Whenever any data comes to Hadoop it breaks those data into small “chunks” and then those small-small part of data store in different Hadoop clusters across the server.

Hadoop framework is extensively used for ecommerce data processing that comes from different sources and analysis. Processing data using Hadoop is a cost effective way to find insight.

Shopping experience has been changing from traditional offline way to online marketing. Concept of brand is getting replaced with customer personalization. Now power has been shifted to consumers from shoppers. So, all ecommerce companies try to attract consumers with many plans. There are many application of Hadoop in ecommerce because of its cost effective data processing characteristic. Some application of Hadoop in ecommerce sector are:

Personalized offer – As we discussed above that shopping experience has been changed in recent years and power shifted to consumers from shoppers. So now customers are important. All ecommerce companies want to treat each customer in personal manner. Customers shop with same retailers in different ways. So using Hadoop retailers collect data of same customer from different sources and provide personalized offer for them.

Improve customer service – Online retailers use big data for a good customer service. Using Hadoop they track the customer data whenever customer contact representatives then customer data should be in front of customer care representative, so they won’t need to ask anything from customer and customer will feel special.

Fraud detection – Using Hadoop retailers detect the patterns of fraudulent. Hadoop is the simplest and best method to detect the pattern of fraudulent. Any other method will be cause for high expenses without certainty of correct result.

Dynamic pricing – These days in ecommerce sector competition is too high. So always each organisation needs to be alert about other rival companies that what they are doing and how? For example pricing. As a customer you may find some difference in price of same product on different retailers. So, companies are using Hadoop to find the changing pattern in price of their competitors and be ready for those situations.


These are the few ways through which we can know that using Hadoop in ecommerce business is a cost effective way to get a solution rather than any other way. The use of big data in business make the business more attractive and successful, and Hadoop makes it even more appealing. So ecommerce companies are steadily moving to apply Hadoop to increase returns and reduce effort.

Hadoop for Ecommerce data processing

Retailers always want real time or near real time analysis of huge data sets that change rapidly or have a very short life, for example web shopping cart. We know that Ecommerce companies sit on huge amount of data due to a large number of transaction & inventory. And for that, retailers leverage Hadoop technology for quick and large volume data processing.

Data processing is a process of manipulating the stored data for further use. Stored dump data need to be converted into meaningful and can be used for decision support. So, after processing the data, it can be fit for different purpose as per requirement. After processing, data format may change, means data may be modified and it cannot be the same that it was earlier.

Hadoop is one of the highly used platform for big data processing. Hadoop has established itself as the highly demanded tools in big data sector. Hadoop is used for data storing as well as data processing. For both purpose it is having different part inside it- for data storing HDFS is there and for data processing MapReduce is there. With the help of Hadoop, retailers started shifting their focus on individual marketing by giving customized retail experience.

Hadoop is the widely used framework for big data processing and MapReduce is the most important massive data processing tool for ecommerce data processing. Once Gartner had predicted “Hadoop will be in most advanced analytics products by 2015” and now we can see that their prediction became close to 100 % correct. There are many reports published on Hadoop which convey about the importance of Hadoop in Big data. Some of them are:

A report of Technology Research Organization says that “The data market currently with the fastest growth are Hadoop and NoSQL software and services”.

According to the Big Data Executive survey “Almost 90% organisations which are leveraging big data have embarked on Hadoop related projects and thus Hadoop skills are in huge demand”.

These are some survey reports that convey the importance of Hadoop in ecommerce data processing.

Now we will see that how and why we use Hadoop for data processing. First see the answer of How?

Hadoop is an open source data management technology which having both data storing capacity as well as data processing. Hadoop distributed file system i.e. HDFS is used for data storage and MapReduce is used for data processing. Whenever data come in Hadoop it break all data in small chunks and store it on different clusters across the server. After storing data, MapReduce job runs according to the requirement.

Now we will answer the question of why i.e. Why ecommerce uses Hadoop for data processing?

Using Hadoop, ecommerce companies process data to utilize big data insight to ensure high profitability. Some of the area where they use analysis result that comes after data processing are:

  • Personalized marketing
  • Fraud detection
  • Improved customer service
  • Dynamic pricing

These are the few areas where Hadoop helps ecommerce sector to ensure high value service.

Hadoop having some advantages that make it better from other tools. It is based on distributing computing concept that makes it different from others. Due to its scalability and effectiveness, companies are heavily adopting Hadoop for data processing.

How Small and Medium level companies can leverage Big Data?

Big Data’ is the word which appears on everybody’s lips these days. In recent years, there has been a huge hype of ‘Big Data’ which is use to analyse by different companies and vendors to capture meaningful insights from a vast amount of data that can be used to improve business and decision making. When the data is too big, and too diverse to handle in standard database; then it is called big data.

As it is clear from the above that big data is huge collection of data. So, it is impossible to use all that data at a time. You can, however, make use of a small portion of the data that is beneficial for your business.

Unfortunately, many small and medium size companies are missing out on the benefits of utilizing big data because they believe that leveraging big data is too costly and too complex. But the truth is that big data is neither too costly nor too complex. Small and medium size companies can also leverage big data because Big Data solutions have become much more affordable in recent years.

There are many ways by which small and medium level companies can leverage big data. Here are just a few ways small and medium size companies can leverage big data towards their success.

Look for unused data– Small and medium size companies should look for those data which never used in the entire value chain. These data can be their feedback by customers, emails, vendor transaction, and many more. By leveraging these data, we can get some meaning insight that can be used to improve the business – the way it runs and operate.

Look for affordable and effective big data partner– Small and medium level companies can outsource their data to a suitable third party vendor for processing because developing internal capability may not be a wise decision for them at the initial stage. So find an affordable and effective big data partner for your success.

Go for small– If your company is small and medium level; then go for a small start towards big data. After getting some quick positive results from the vendor then only go for big implementation.

Look for the necessity – Small and medium size companies can go for leveraging only those part of data, where analysis is required. Analysing the whole data can be a waste of time and money for them.

Location– Cost is an important factor for any size companies including small and medium size companies while leveraging big data. So, find suitable big data vendors – today there are good small players in the marker out there where you get what you wanted at lesser cost at higher quality and quick turnaround. For eg: leveraging big data is costlier in USA rather than leveraging in India.

Adopt new tools and techniques- For collecting and leveraging big data; use new tools and techniques from the market – essentially freeware.

Every business needs to know the way to success and increased ROI. Leveraging big data is useful for all level of companies. The point is – how you are using and implementing it. According to a survey of Gartner, investment in big data technologies continues to expand every year. They found that 73 % of respondents have invested in big data or have plan to invest in big data in next two years. So, if you are a small or medium size company and thinking that big data is not beneficial for me then for sure you are leaving your boat.

Big data and Advanced Analytics: Made for each other

Before knowing the relation between big data and advance analytics let us look at both i.e. big data and advance analytics.

Recent research by analyst firm International Data Corp. (IDC) reported that the global amount of digital data will grow from 130 Exabyte’s to 40,000 Exabyte’s by 2020. The old data processing technologies like RDBMS are simply not capable to process data in such a large amount; so, a new trend came “Big Data”. In simple words big data is a collection of huge amount of data coming from different sources.


How to train existing employees on Big Data?

It’s very challenging to talk about Big Data without taking about the skills required for big data. At present companies are suffering from Big Data skill gap. According to a CompTIA survey of 500 U.S. business and IT executives, 50 percent of firms that are moving forward on the way to leverage big data, and 71 percent of firms that just started leveraging big data, feel that their staff are not so proficient in data management and analysis skills. Due to the lack of knowledge about big data processing, employees couldn’t give their full effort and it may cause for the project failure. So, the training of existing employees on Big Data should be an integrated part of big data processing.

Now, if you are a caretaker of a company you may have a question that “How”? How to train your employees on big data?

Let us try to find answer for these questions and to make your current team more big data ready.

  • If you are a company having a base of developers in java, python or Ruby then you may further proceed towards their training on big data because these are some of the language useful for big data processing. So, overall you first need to train your employee on these languages i.e. java, python, ruby, etc.
  • You also need to train them on database development side with NoSQL Big Data systems like HBASE, MongoDB, Cassandra etc. You may choose database developer with good SQL knowledge to train on database part.
  • For the installation or setup big data lab you may need to train some people as Linux admin so that they make you big data lab ready for Hadoop or AWS. For this you may choose people with Linux knowledge.
  • After all these theoretical training you may need to go for some practical work on big data processing. For this use Hortonworks or Cloudera services to give practical training to your employees.
  • There are many free and paid online courses available for big data training. Can start with free course and can move to paid ones, if anything specific required. You may provide these materials to your employee where they will get online study material as well as practical works on big data processing.
  • For the analyst work, first you need to find employees with good analytical and reasoning skills. Train them to use different big data analysing tools.

With the help of these ways you may train your existing employees on big data and make them ready to start. The McKinsey Global Institute estimates that by 2018, there will be a shortage of 1.7 million workers with big data skills in the U.S. alone—140,000 to 190,000 workers with deep technical and analytical expertise and 1.5 million managers and analysts with the skills to work with big data outputs. It is a truth that big data processing and most of its components are new but you can easily cross train your employees on big data if you really want to get in this field. You just need to take existing developers, analyst and admins and cross train them.

Leverage big data to improve customer experience

It is a fact that customers who are happy with your products or services are much more likely to come back and buy from you again and again. To be in competition every organisation need a wide range of satisfied customers. And, for growth, a business needs to be able to retain, satisfy and engage their high value customers effectively. So in another word it is an era of connected customers. Companies invest a big amount on big data strategy to collect, store, organize and analyse the information about their customers to make personalised marketing strategy to make each one feel special. Big data helps companies to find their customer’s need and expectation from various customer touch points – data.

According to a survey of Driving Performance While Managing Risk, KPMG showed that 41% companies will use big data analytics to improve customer experience in next three years.

Companies cannot depend only on the traditional way for keeping their customer happy. They know that there is a need to leverage big data in their business. Let’s see some area where you can leverage big data to improve customer experience.

Customized marketing – In the era of customized marketing, companies try to reach every possible customer in personalized way. It helps both companies as well as customers. Customers feel special when they receive a personalized service from the service provider and companies get a new customer.

Personalised service – It is very difficult to analyse every customer purchase history transaction data to get information about their behavior, interest, and preferences. Big data makes it easy. With the help of these information companies can prepare their sales strategy to push customers to the point of purchase.

Identify customer problem and solve them– If a company doesn’t know about the pain point of their customers then they couldn’t pay attention to their customers. Companies who are using big data analytics, they know the difficulties facing by the customers and try to improve their customer’s experience. If your company get it to the world of bid data analytics, then for sure you will be out front in a competitive market. Delta Airlines used big data to find the lost baggage of their passengers and came out front in the airlines market.

Improve customer service- Companies are using big data for marketing product development but the companies who are using it to improve customer experience and move one step further. If a customer contacts you, for any enquiry, and if you have enough data in front of you about them then the representative can more quickly and competently solve their issues. They don’t need to ask many question of the customer because they already have this information in front of them. This makes customer feel good and satisfied.

Give more options- One dairy company uses big data to customize their product. Any customer can choose the product according to their interest like fat, etc. They analyse the customers review data and found that different customers having different needs. So they put some option related to the needs of customers for their product. This makes both happy, customer as well as company.

Provide them their own data– Make customers excited about their own data. Here data means analysed data not the huge amount of unstructured data. A food diary platform bodymedia gives not only the information about the calories they have consumed but also about their break down protein and fat. Some more companies use big data to help their customers to find their source of expenditures.

Customer service is a very important part of any business. If you don’t have a well organised and behaved customer service; then it is not possible for you to stand in the competition. Today’s companies not only focus on traditional customer service but also a highly managed and arranged customer service with the use of big data.

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