Claims:We claim:
1) The system and method for operational analytics in retail by using big data technology is comprising of the contents such as;
a. Backend server – Operational analytics in retail application in installed;
b. Any open-source framework like Hadoop for data analysis which stored data on big data; and
c. The application for operational analytics in retail;
2) The system claimed in claim 1 wherein, big data technology can be used to combine structured data with unstructured data.
3) The system claimed in claim 1 wherein, retailers can discover runtime series.
4) The system claimed in claim 1 wherein, retailers can parse, remodel and visualize data provided by big data technology.
5) The system claimed in claim 1 wherein, retailers can discover root cause analyses.
, Description:FIELD OF INVENTION
The present invention discloses the system and method for operational analytics in retail by using big data technology. The invention is related to retail sector, in particular operational analytics. Big data is one of the best technologies which can be effectively used for retail sector.
BACKGROUND OF INVENTION
Retail analytics is the process of providing analytical data on inventory levels, supply chain movement, consumer demand, sales, etc. that are crucial for making marketing, and procurement decisions.
Operations Analytics helps today's retailers increase revenue without increasing staffing by spending less time monitoring while gaining more insights about customers and processes. Retailers gain visibility over both asset movement through the store and employee response and engagement with customers.
It is concerned with turning raw data into insight for making better decisions. Analytics relies on the application of statistics, computer programming, and operations research in order to quantify and gain insight to the meanings of data. It is especially useful in areas which record a lot of data or information.
Currently, operational analytics is done manually or with the system which is not that much capable for handling such a huge data.
The present invention gives the solution for huge data analysis.
The present invention discloses the system and method for operational analytics in retail by using big data technology. The key to utilizing data engineering platforms to increase operational efficiency is to use them to unlock insights buried in log, sensor and machine data. These insights include information about trends, patterns and outliers that can improve decisions, drive better operations performance and save millions of rupees. Servers, plant machinery, customer-owned appliances, cell towers, energy grid infrastructures and even product logs – these are all examples of assets that generate valuable data. Collecting, preparing and analysing this fragmented (and often unstructured) data is no small task. The data volumes can double every few months, and the data itself is complex often in hundreds of different semi-structured and unstructured formats. Data engineering allows retailers to quickly combine structured data such as CRM, ERP, mainframe, geo location and public data and combine them with unstructured data. Then, utilizing the right analytical tools, you can use this data to detect outliers, run time series and root cause analyses, and parse, transform and visualize data.
OBJECTS OF THE INVENTION
The main object of the invention is that, system and method for operational analytics in retail by using big data technology.
Another object of the invention is that, big data technology can be used to combine structured data with unstructured data.
Another object of the invention is that, retailers can discover outliers.
Another object of the invention is that, retailers can discover runtime series.
Another object of the invention is that, retailers can parse, remodel and visualize data provided by big data technology.
Other object of the invention is that, retailers can discover root cause analyses.
SUMMARY OF THE INVENTION
The present invention discloses the system and method for operational analytics in retail by using big data technology. The invention application is installed at backend server. User/retail team member open the invention application. Big data technology analyses information related to business performance and returns. With the help of big data technology, retailers make an attempt to increase operation efficiency. For increasing operation efficiency, big data provided information such as trends, patterns and outliers, improve decisions, operations performance and reduce costs.
BRIEF DESCRIPTION OF DRAWINGS
Fig 1 shows flowchart of the system and method for this invention.
DETAILED DESCRIPTION OF THE INVENTION
The present invention discloses the system and method for operational analytics in retail by using big data technology.
Big data is the vast volume of structured or unstructured data that is readily available at collective fingertips. These large data sets are analysed to reveal previously unknown patterns and provide insights into businesses, human behaviour, and more. Big data analysis is used for everything from financial services, to gauging someone’s productivity, to even monitoring the weather.
The key feature of big data is to analyse, understand and interpret it in order to give user a full a picture as possible about the supply chain analysis in retail.
The system and method for operational analytics in retail by using big data technology is comprising of the contents such as;
Backend server – The operational analytics in retail application is installed
Operational analytics in retail application
Any open-source framework like Hadoop for data analysis which stored data on big data
Big data consists of five stages such as-
Data sources- web and social media, machines, Sensing, IoT
Content format – structured, semi-structured, unstructured data
Data stores – document oriented, column oriented, graph database, key value
Data Staging – cleaning, transform and normalization
Data processing – Batch and real time
The system and method for operational analytics in retail by using big data technology is comprising of the following steps such as;
Step 1) The application for operational analytics in retail is installed at backend server
Step 2) User/retail team member start the invention application
Step 3) Big data technology analyses information related to business performance and returns
Step 4) User/retail team member can see the information provided by big data technology related to trends, patterns and outliers, improve decisions, operations performance and reduce costs
Step 5) User/retail team member analyses the data and can make decision with reference to increase operation efficiency
The role of big data technology in invention application is as follows –
Big data technology analyses information related to business performance and returns. With the help of big data technology, retailers make an attempt to increase operation efficiency. For increasing operation efficiency, big data provided information such as trends, patterns and outliers, improve decisions, operations performance and reduce costs.
Use of big data is looking promising in the retail field and it can become a standard in the future.
The invention application has some advantages for the invented system, such as;
Text mining algorithms to arrive items and order quantity automatically.
Deep learning techniques such as convoluted nets for recognition and analysis of images obtained from cameras and automation of order placement.
Use of text mining to conduct customer sentiment analysis.
Customer lifetime value scores to identify specific customers who need to be targeted or reactivated.
Use of look-alike modelling on third-party databases to identify profiles similar to high-value customers.
Creation of unique customer personas.
Past purchase behaviour and timing analysis to identify potential products that customers are most likely to purchase.
Suggest more relevant product recommendations based on customer personas and purchase behaviour.
Enhanced end-user experience by suggesting the right products at the right time of the day.