Adil Khan 1 year ago
AdiKhanOfficial #FYP Ideas

Bigdata Framework

This will be a software  using big data for the analysis of data , data mining , data management and efficient memory management,and  for the proximity of link prediction. We will use the technologies Scala , Apache Spark. Apache Maven ,Apache HDFS, BigDL Memory Management U

Project Title

Bigdata Framework

Project Area of Specialization

Artificial Intelligence

Project Summary

This will be a software  using big data for the analysis of data , data mining , data management and efficient memory management,and  for the proximity of link prediction. We will use the technologies Scala , Apache Spark. Apache Maven ,Apache HDFS, BigDL Memory Management Understanding and proposed  Technique coding. 

Project Objectives

Our main objective will be

Performance Management: Performance management involves understanding the meaning of big data in company databases using pre-determined queries and multidimensional analysis. The data used for this analysis are transactional, for example, years of customer purchasing activity, and inventory levels and turnover.

Data Exploration:Data exploration makes heavy use of statistics to experiment and get answers to questions that managers might not have thought of previously. This approach leverages predictive modeling techniques to predict user behavior based on their previous business transactions and preferences.

Social Analytics:Social analytics measure the vast amount of non-transactional data that exists today. Much of this data exist on social media platforms, such as conversations and reviews on Facebook, Twitter, and Yelp. Social analytics measure three broad categories: awareness, engagement, and word-of-mouth or reach.

Project Implementation Method

The sofware will be produced using Scala , Apache Spark. Apache Maven ,Apache HDFS, BigDL Memory Management Understanding and proposed  Technique coding. 

The following methods wil be used to implement

  • Machine learning implementation ? This could be a classification algorithm, a regression model or a segmentation model.

  • Recommender system ? The objective is to develop a system that recommends choices based on user behavior. Netflix is the characteristic example of this data product, where based on the ratings of users, other movies are recommended.

  • Dashboard ? Business normally needs tools to visualize aggregated data. A dashboard is a graphical mechanism to make this data accessible.

  • Ad-Hoc analysis ? Normally business areas have questions, hypotheses or myths that can be answered doing ad-hoc analysis with data.

Benefits of the Project

The final deliverble software will be

  1. Cost Savings because Some tools of Big Data like Hadoop and Cloud-Based Analytics can bring cost advantages to business when large amounts of data are to be stored and these tools also help in identifying more efficient ways of doing business.
  2.  Time Reductions because the high speed of tools like Hadop and in-memory analytics can easily identify new sources of data which helps businesses analyzing data immediately and make quick decisions based on the learnings.
  3.  New Product Development because by knowing the trends of customer needs and satisfaction through analytics we can create products according to the wants of customers.
  4.  Understand the market conditions because by analyzing big data we can get a better understanding of current market conditions. For example, by analyzing customers’ purchasing behaviors, a company can find out the products that are sold the most and produce products according to this trend. By this, it can get ahead of its competitors.
  5.  Control online reputation  because big data tools can do sentimental analysis.Therefore, we can get feedback about who is saying what about our company. If we want to monitor and improve the online presence of our business, then, big data tools can help in all this.

Technical Details of Final Deliverable

Technologies being applied to big data include efficient tensor-based computation, such as multilinear subspace learning] massively parallel-processing (MPP) databases, searched based applications data  mining , distributed systems , distributed  databases and cloud infrastructure  and the Internet.Although, many approaches and technologies have been developed, it still remains difficult to carry out machine learning with big data.

Final Deliverable of the Project

Software System

Type of Industry

IT

Technologies

Cloud Infrastructure, Big Data

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Data Bricks Analytics Apache Spark Server Service Equipment16600066000
Total in (Rs) 66000
If you need this project, please contact me on contact@adikhanofficial.com
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