Bigdata is one of the most trending word in today’s market. The effect of big data in every business- from fortune 500 enterprises to start-up’s is so huge that each and every company wants to leverage it. It doesn’t matter, in which field you are working and what is the size of your company? Data collection, analysis and implementation impact your business in several ways. This is the time where you can’t ignore big data analytics and if you are still saying that ‘Big data is not beneficial for my company’ then you are definitely moving out from the competition.
Today, data is a powerhouse for generating business and exploring growth. And, the beauty is – it doesn’t do anything unless someone know how to explore it. It is never been so easier to solve business problem and uncover new opportunity in ‘big data’ field. As we know, Big Data refers to the data comes from millions of sources i.e. from social media, emails, surfing, cell phone signals, sales transactions, etc. All these data that can be stored can call – big data. To use these data i.e. big data, for the business purpose, we need in-house big data team or we need a big data partner who can help to collect, store, process, analyse, and provide greater insight for decision support. (more…)
If we talk about the development of Hadoop technology then there are two companies which are doing a lot in this field. One is Hortonworks and another is Cloudera. These companies are developing a lot of new ideas and software in the field of Hadoop to make it easier to use and developing a lots of applications on them. These companies provide tools to use and learn Hadoop.
When we heard the word “Sandbox” then suddenly our mind clicked about it as a low, wide container filled with sand in which children use to play. But things are different here. We are going to talk about the sandbox used in developing in the field of software development. Basics are quite same but things are different. By providing sandboxes to a child we create an environment of a real playground with some resources and restrictions. Similarly in a software sandbox we create an environment in which development can be done with some tools as resources and some restrictions over what it can do.
So we can write a sandbox as a technical environment in which software development can be done and whose scope is well defined.
Software project having mainly four areas through which every software development steps processed. These are:
- Quality Assurance
- UAT ( User acceptance testing )
All these phase needs sandboxes to deliver their results fast with less risk of technical errors. We have categorized these sandboxes in five different types according to their uses in development process. Those are:
Development – These type of sandboxes provide an environment to developers and programmer to work or develop software with their separate set of tools that comes with the sandbox as a package without affecting the rest of their project team. Hortonworks Sandbox is an example of this in which all related and required tools come along with Hadoop working environment.
Project integration- These sandboxes are used to integrate the environment between a team. As we saw in development process that every team member having their own sandbox, so project integration sandbox establish an environment in which all the team members can exchange data and information to each other and validate the work before sending it to Quality Assurance sandbox.
Quality assurance – These sandboxes are useful in the testing process where it is shared by several teams and is often controlled by a specific separate team. The purpose of this sandbox is to provide an environment as real as the real time use so we can test our applications in different conditions. This sandbox is very useful when many applications access the database but it is same important when a single application access the database. We need to test within this sandbox before approaching to the User Acceptance Test.
UAT sandbox – These sandboxes are used for the acceptance testing purposes. This is the pre-step of production. So these sandboxes provides a real time scenario where the user acceptance testing can be performed.
Production – This is the final stage of software creation i.e. software has to release in this stage. So these sandboxes provide an actual environment in which the software has to establish.
The primary advantage of using sandboxes are that it always contains a package of software for the respective software development, so it makes the developers work easy and reduce the risk of technical errors.
OSP uses all these types of sandboxes while working on any project. With the help of these sandboxes we provide fast and better services to our clients. We provide an error free solutions by using these techniques. By using these sandboxes it’s very easy for us to provide a setup to our clients in less period of time. These type of special techniques make us different and unique for our clients.
A few years back, it was all manual data mining and it took long long days for almost all small and medium players in the market for web data mining. Today, technology is evolving a lot and we are in an era of Big data and manual data mining is no more a right method and it is mostly about automation tools, custom scripts, or Hadoop framework.
Now, let us discuss something about web data extraction. It is a process of collecting data from World Wide Web using some web scrapper, crawler, manual mining, etc. A web scrapper or crawler is a cutting tool for harvesting information available on internet. In other word web data extraction is a process of crawling websites and extract data from that page using a tool or programming. Web extraction is related to web indexing which refers to various methods of indexing the contents of web page using a bot or web crawler. A web crawler is an automated program, script or tool using that we can ‘crawl’ webpages to collect multiple information from websites.
In the world of big data, data comes from multiple sources and in huge amount. In which one source is web itself. Web data extraction is one of the medium of collecting data from this source i.e. web. Companies which are leveraging big data technology are using crawlers or programming to collect data. These data comes in bulk i.e. billions of records, or as a data dump. So, it needs to treat as big data and bring into Hadoop Eco system to get quick insight from it.
There are multiples areas where companies can explore web data extraction. Some areas are:
- In ecommerce, companies use web data extraction to monitor their competitor price and improve their product attributes. They also fetch data from different web sources to collect customer review and using Hadoop framework they do analysis – including sentiment analysis.
- Media companies use web scraping to collect recent and popular topics of interest from different social media and popular websites.
- Business directories use web scraping to collect information about the business profile, address, phone, location, zip code, etc.
- In healthcare sector, health physician scrap data from multiple websites to collect information on diseases, medicine, components, etc.
When companies decide to go for web data extraction today, then they move ahead thinking about big data because they know that data will come in bulk i.e. in millions of records will be there and it will be mostly in semi or unstructured format. So, we will need to treat it as big data and use Hadoop framework and tools for converting it for any decision making.
In this whole process, first step is web data extraction, that can be done using different scraping tools available in market (there are free and paid tools are available) or create custom script using programming language with the help of expert in scripting language like Python, ruby, etc.
Second step is to find insight from the data. For this, first we need to process the data using the right tool based on the size of the data and availability of the expert resources. Hadoop framework is the most popular and highly used tool for big data processing. Also, for sentimental analysis of those data, if needed, we need MapReduce which is one of the components of big data (Hadoop).
To summarize, for web data extraction, we can choose different tools for automation or develop scripts using programming language. Developing a script is often minimize effort as it is reusable with minimal modification. Moreover, as the volume of web data is huge-what we extract, it is always advisable to go for Hadoop framework for quick processing.
Data management plays a major role in the success of an organisation. According to Wikipedia “Data management comprises all the disciplines related to managing data as a valuable resource”. As the name defines that it is the management of data. In these days data is playing a crucial role in business. Especially in ecommerce or retail sector companies uses data insight for each and every department for the better improvement in their services as well as improvement in company. They use data management to generate revenue, cost optimization and risk analysis.
We are now living in big data world. Data generated in vast amount with variety and complexity. Data are complex but it’s important too. In ecommerce industry data came from several sources. Managing these data is really a tough job. But to use those data for improvement of the organization we need to manage them in proper manner. So, a proper and effective data management is necessary.
Hadoop is a boat to travel in big data sea. Hadoop is the core and basic technology for most of the big data related solutions, planning and application. It is most highly ranked and used platform for big data analytics solutions and strategies. Hadoop has a great impact on each and every sector where big data is leveraging. Especially in Ecommerce, big data has its own importance. So, Hadoop has been frequently used in retail sector.
In recent years the shopping experience has changed dramatically. Now everything is available on internet as online shopping. The power has been shifted to consumer from retailer. Consumers having more options now than any other time. To compete in this environment retailers or ecommerce business changed their traditional plans and employ new strategies to attract and retain customers. Big data and Hadoop help them to connect with customers and in decision making.
Before going in deep of Hadoop we need to understand the concept of Hadoop. In simple words “Hadoop is a framework on which big data can be processed”. Traditional framework or relational database technology are unable to process big data because of its volume, variety, velocity and complexity. So, we use Hadoop framework for this purpose. In core of Hadoop there are two things, HDFS for storage and MapReduce for processing.
In retail sector MapReduce is used to integrate and analyse the large amount of data and the analysis result helps them in decision making. Some area where Hadoop can be used in ecommerce:
Personalised offer – Using MapReduce retailers try to know about their customers and their capabilities and according to their history they provide personalized offer to each customer.
Fraud detection – Using Hadoop retailers try to find fraudulent behaviour. They analyse the pattern of fraudulent and take decisions to prevent these things.
Social media analysis – Using Hadoop retailers analyse the sentiment of people about their products on different social media platform. It helps them a lot in improving their business.
Improving customer service – Hadoop also helps in improving customer service in ecommerce. Analysing the data of customers feedback companies improve their customer service to provide better shopping experience to their customers.
Predictive analysis – In ecommerce there is a very tough completion between all retailers. They always make plans for a short period of time with long period impact. To keep themselves in competition Companies use Hadoop to predict the future sales and after getting analysis result they make them ready for that.
Hadoop helps ecommerce business in many ways. Companies are using Hadoop for their data management and leveraging data to find better insight which they are applying in decision making. Now a days Hadoop became an integrated part of a successful ecommerce business. In other words ‘Hadoop is playing an important role in ecommerce data management’.
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.
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.
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.
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.