W H A T A R E B I GD A T A A N A L Y T I C S .

An Academic presentation byDr. Nancy Agens, Head, Technical Operations, PhdassistanceGroup  www.phdassistance.comEmail: info@phdassistance.com

H O W I T ' S B E I N G U S E D , M E N T I O N T H ET O O L S A N D T E C H N O L O G I E S U S E D I NB I G D A T A A N A L Y T I C S .

In-Brief

Introduction

How Big Data Analytics Works in Research

Big Data Analytics Tools and Technology

Conclusion

Outline

TODAY'S DISCUSSION

In-Brief

PhD Data Analytics & Big Data Services have data analysts, statisticians datascientists, predictive modellers, and other analytics professionals to analyze yourgrowing volumes of structured transaction data. Our expert in PhD Thesis on Big

Data Analytics utilizes that commonly used for advanced analytic process. PhDGuidance in Big Data Help Researchers to harness their data and use it to identify

different patterns and new opportunity in research

Big Data Analytics PhD is the complicated process ofexamining big data to uncover pieces of information,such as hidden patterns, correlations, customerpreference and market trends that can helporganizations make precise business decisions.

It is a type of advanced analytics, which involvecomplex applications with various elements such aspredictive model, statistical algorithms.

Introduction

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New revenue opportunities

More effective marketing

Better understanding the needs

Improved operational efficiency

Competitive advantages over rivals

Big data analytics through unique systems and software can lead to positive research-related outcomes such as,

Data collection varies from a different organization.

Based on the organization, they collect the data thatcan be both structured or unstructured data fromthe variety of source.

Some data stored in data warehouses whereresearch intelligence tools and provide outcomewhere professionals can access it easily.

PhD Projects in Big Data analysis services helps tohandle the complex set of data that is raw orunstructured.

How BigData AnalyticsWorks inResearch

1. Data collection

Contd..

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Once the data collected and stored, it is adequatelyorganized based on the organizational needs to get a targetoutcome on analytical quires, especially when it is large orunstructured data forms.

And the available data is growing exponentially.

The processing option is the batch processing that looks forbig data blocks.

Batch processing applies to the longer turnaround timebetween collecting and analyzing the data sets.

2. Data Process

Contd..

Stream processing is the type that looks at small batches that areshortening the delay time between the collection and analysis phase foreasier decision making.

The stream process method is a tedious process that is often expensiveto conduct.

Contd..

The data may be big or small, that requires scrubbing toimprove their quality and also to get more substantialresults to make the right decision for research.

All the available data must be formatted correctly to getreliable information out of it.

PhD Guidance in Big Data checks the presence ofduplicative or irrelevant data that are in the data set.

Raw data can be obscure and mislead the research bycreating flawed insights.

3. Clean Data

Contd..

It takes time to get PhD Research Topics in Big DataAnalytics into a usable state.

Once it is ready, the advanced analytic process canturn big data into insight.

Data mining group through large datasets to identifypatterns and relationships by identifying incongruitydata and creating data clusters.

Big data analytics method include,

4. Data Analyze

Contd..

Predictive analytics utilizes an organization's historical data to makejustifications for the identification of future research risks and opportunities.

Deep learning assumes human learning patterns by applying artificialintelligence and machine learning to layer algorithms and find patterns for themost complex and abstract data sets.

Hadoop is an open-source tool that efficiently stores andprocesses big datasets in the group in commodityhardware.

It is the framework that is free and also handles largeamounts of structured and unstructured data, to make avaluable mainstay for any data operation.

NoSQL databases is a non-relational data managementsystems that do not require a fixed scheme, making theman excellent option for big, raw, unstructured data.

Big DataAnalyticsTools andTechnology

Contd..

YARN stands for "Yet Another Resource Negotiator." It is a component of last-generation Hadoop.

The group management technology helps with scheduling and resource managementwhich is in the cluster.

Spark is an open-source group computing framework that utilizes implicit dataparallelism and faults tolerance to provide an interface for entire programming clusters.

Spark is applicable for both batch and stream processing.

Contd..

Tableau is a close-ended data analytics platform that allows researchers to prepare,analyze, collaborate, and share your research data insights.

Tableau excels in self-service visual analysis, allowing researchers to ask newquestions of governed Big Data in Official Statistics and allows to share those insightseasily within the organization.

PhD Program Big Data Analytics uses technologiessuch as Hadoop, NoSQL brings cloud-based analyticsthat shows significant cost difference when it comes tostoring large sets of data, plus they can identify moreefficient ways of doing research right.

Conclusion

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