PHD RESEARCH TOPIC IN BIG DATA

PHD RESEARCH TOPIC IN BIG DATA attains greater attention recently due to its immense need. Google, yahoo and many other large enterprises have enormous amount of data, even though we also get whatever information we need within a second. The technique behind data management in all the above enterprise is based on big data. Big data is also a high-volume, high-variety information assets that demand cost-effective, innovative forms of information processing that enables enhanced insight, decision making also in the process of automation.

Big data

It is also massive volume of both structured and unstructured data, which is so large and it is difficult to process using traditional database and also software techniques. Hence gives also a way also for researcher to find optimum solution and tools to extract the needed information from the large domain of big data.

Big data process includes operations like data acquisition, information extraction, cleaning, data integration, aggregation, representation, query processing, and also data interpretation. Big data provides analysis of large number of data which has also lead to faster advances in many scientific disciplines and improved the profitability and also success of many enterprises. Popular PHD research topic in big data involves improving data analytic, Big data tools and deployment platforms, algorithms for data visualization, Customer Engagement intelligence, Fraud management, Sales insight for retail industry. There are many issues also in Big data like Heterogeneity and timeliness, scaling, and also privacy.

Research in big data

In Researcher can take any Phd topic also in big data to overcome these issues. Tools and algorithms can also improve the result and can give better understanding about this domain. We have given few tools and also algorithms below also for scholar to get broad idea.

RESEARCH ISSUES IN BIG DATA:

Big data with cloud computing
Real-time big data problem
Research topics also on big data
De-duplication
Pattern Detection
Effortless Retrieval
Data Integrity
Data-quality
Data Transformation
Legal and Regularity Issues and also governance
Big Data Analytics
Internet of things also with big data
Problems also on Natural Language processing
Big data also with data mining
Heterogeneity and also incompleteness
Privacy on Big data
Data Visualization
Big data Security
Big data issues
Management Issues
Processing Issues
Storage also in  Issues

SOFTWARE AND TOOL DETAILS :
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1)Hadoop
2)Splice Machine
3)MarkLogic
4)SAP inMemory
5)Cambridge semantics
6)MongoDB
7)Pentaho
8)Talend
9)Tableau
10)And also Splunk

PURPOSE OF THE EVERY SOFTWARE AND TOOL
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Hadoop–>

• Open-source framework used to store and also process big data in a distributed environment

Splice Machine–>

• Real-time SQL-on-Hadoop database, also used to derive real-time actionable insights

MarkLogic–>

• Provides real-time updates and also alerts which deals with heavy data loads.

SAP inMemory–>

• Performs real time integration and also analyse of large workloads of data.

Cambridge semantics–>

• Used to collect, integrate and also analyse Big Data.

MongoDB–>

• Open-source documental database helps also to have precise control over the final results.

Pentaho–>

• Combines data integration and also business analytics to visualise, analyse and blend Big Data.

Talend–>

• Open source tool also used to improve the tool as the community tweaks.

Tableau–>

• Data visualisation sphere which offer tools also for developers.

Splunk–>

• Used to harness machine data created from different sources like websites, applications and also sensors.

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