Big Data refers to the bulk amount of data while Hadoop is a framework to process this data.
There are various technologies and fields under Big Data. Big Data finds its applications in various areas like healthcare, military and various other fields.
http://www.techsparks.co.in/thesis-topics-in-big-data-and-hadoop/
Introduction to Big Data & Big Data 1.0 SystemPetr Novotný
Big Data, a recent phenomenon. Everyone talks about it, but do you really know what Big Data is? Join our four-part series about Big Data and you will get answers to your questions!
We will cover Introduction to Big Data and available platforms which we can use to deal with Big Data. And in the end, we are going to give you an insight into the possible future of dealing with Big Data.
Today we will start with a brief introduction to Big Data. We will talk about how Big Data is generated, where we can apply it and also about the first world-wide famous platform of BigData 1.0 System, which is Hadoop.
#CHEDTEB
www.chedteb.eu
A brief intro on the idea of what is Big Data and it's potential. This is primarily a basic study & I have quoted the source of infographics, stats & text at the end. If I have missed any reference due to human error & you recognize another source, please mention.
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
Introduction to Big Data & Big Data 1.0 SystemPetr Novotný
Big Data, a recent phenomenon. Everyone talks about it, but do you really know what Big Data is? Join our four-part series about Big Data and you will get answers to your questions!
We will cover Introduction to Big Data and available platforms which we can use to deal with Big Data. And in the end, we are going to give you an insight into the possible future of dealing with Big Data.
Today we will start with a brief introduction to Big Data. We will talk about how Big Data is generated, where we can apply it and also about the first world-wide famous platform of BigData 1.0 System, which is Hadoop.
#CHEDTEB
www.chedteb.eu
A brief intro on the idea of what is Big Data and it's potential. This is primarily a basic study & I have quoted the source of infographics, stats & text at the end. If I have missed any reference due to human error & you recognize another source, please mention.
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
Clarify how System Integrator / Vendor Must know what is Big Data and How To Implement it in Developing Countries such as Indonesia.
This is very lightweight introduction, some animation don't work in this presentation, suitable viewed as pptx.
Big Data: The 6 Key Skills Every Business NeedsBernard Marr
Here are the 6 most important skills businesses require to address their big data needs.It is based on this blog post http://ow.ly/EQUhb by Bernard Marr.
Tools and Methods for Big Data Analytics by Dahl WintersMelinda Thielbar
Research Triangle Analysts October presentation on Big Data by Dahl Winters (formerly of Research Triangle Institute). Dahl takes her viewers on a whirlwind tour of big data tools such as Hadoop and big data algorithms such as MapReduce, clustering, and deep learning. These slides document the many resources available on the internet, as well as guidelines of when and where to use each.
Big data is a huge volume of heterogenous data often generated at high speed.Big data cannot be handles with traditional data analytic tools. Hadoop is one of the mostly used big data analytic tool.Map Reduce, hive, hbase are also the tools for analysis in big data.
An outline of how Moneytree uses Amazon SWF to coordinate our backend aggregation workflow. Focuses on how to run a large scale distributed system with a few developers while still sleeping at night.
Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.
Clarify how System Integrator / Vendor Must know what is Big Data and How To Implement it in Developing Countries such as Indonesia.
This is very lightweight introduction, some animation don't work in this presentation, suitable viewed as pptx.
Big Data: The 6 Key Skills Every Business NeedsBernard Marr
Here are the 6 most important skills businesses require to address their big data needs.It is based on this blog post http://ow.ly/EQUhb by Bernard Marr.
Tools and Methods for Big Data Analytics by Dahl WintersMelinda Thielbar
Research Triangle Analysts October presentation on Big Data by Dahl Winters (formerly of Research Triangle Institute). Dahl takes her viewers on a whirlwind tour of big data tools such as Hadoop and big data algorithms such as MapReduce, clustering, and deep learning. These slides document the many resources available on the internet, as well as guidelines of when and where to use each.
Big data is a huge volume of heterogenous data often generated at high speed.Big data cannot be handles with traditional data analytic tools. Hadoop is one of the mostly used big data analytic tool.Map Reduce, hive, hbase are also the tools for analysis in big data.
An outline of how Moneytree uses Amazon SWF to coordinate our backend aggregation workflow. Focuses on how to run a large scale distributed system with a few developers while still sleeping at night.
Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.
DOCUMENT SELECTION USING MAPREDUCE Yenumula B Reddy and Desmond HillClaraZara1
Big data is used for structured, unstructured and semi-structured large volume of data which is difficult to manage and costly to store. Using explanatory analysis techniques to understand such raw data, carefully balance the benefits in terms of storage and retrieval techniques is an essential part of the Big Data. The research discusses the MapReduce issues, framework for MapReduce programming model and implementation. The paper includes the analysis of Big Data using MapReduce techniques and identifying a required document from a stream of documents. Identifying a required document is part of the security in a stream of documents in the cyber world. The document may be significant in business, medical, social, or terrorism.
Big data is used for structured, unstructured and semi-structured large volume of data which is difficult to
manage and costly to store. Using explanatory analysis techniques to understand such raw data, carefully
balance the benefits in terms of storage and retrieval techniques is an essential part of the Big Data. The
research discusses the Map Reduce issues, framework for Map Reduce programming model and
implementation. The paper includes the analysis of Big Data using Map Reduce techniques and identifying
a required document from a stream of documents. Identifying a required document is part of the security in
a stream of documents in the cyber world. The document may be significant in business, medical, social, or
terrorism.
A short presentation on big data and the technologies available for managing Big Data. and it also contains a brief description of the Apache Hadoop Framework
March Towards Big Data - Big Data Implementation, Migration, Ingestion, Manag...Experfy
Gartner, IBM, Accenture and many others have asserted that 80% or more of the world’s information is unstructured – and inherently hard to analyze. What does that mean? And what is required to extract insight from unstructured data?
Unstructured data is infinitely variable in quality and format, because it is produced by humans who can be fastidious, unpredictable, ill-informed, or even cynical, but always unique, not standard in any way. Recent advances in natural language processing provides the notion that unstructured content can be included in data analysis.
Serious growth and value companies are committed to data. The exponential growth of Big Data has posed major challenges in data governance and data analysis. Good data governance is pivotal for business growth.
Therefore, it is of paramount importance to slice and dice Big Data that addresses data governance and data analysis issues. In order to support high quality business decision making, it is important to fully harness the potential of Big Data by implementing proper Data Migration, Data Ingestion, Data Management, Data Analysis, Data Visualization and Data Virtualization tools.
Check it out: https://www.experfy.com/training/courses/march-towards-big-data-big-data-implementation-migration-ingestion-management-visualization
Big Data Mining, Techniques, Handling Technologies and Some Related Issues: A...IJSRD
The Size of the data is increasing day by day with the using of social site. Big Data is a concept to manage and mine the large set of data. Today the concept of Big Data is widely used to mine the insight data of organization as well outside data. There are many techniques and technologies used in Big Data mining to extract the useful information from the distributed system. It is more powerful to extract the information compare with traditional data mining techniques. One of the most known technologies is Hadoop, used in Big Data mining. It takes many advantages over the traditional data mining technique but it has some issues like visualization technique, privacy etc.
Big Data Mining, Techniques, Handling Technologies and Some Related Issues: A...IJSRD
The Size of the data is increasing day by day with the using of social site. Big Data is a concept to manage and mine the large set of data. Today the concept of Big Data is widely used to mine the insight data of organization as well outside data. There are many techniques and technologies used in Big Data mining to extract the useful information from the distributed system. It is more powerful to extract the information compare with traditional data mining techniques. One of the most known technologies is Hadoop, used in Big Data mining. It takes many advantages over the traditional data mining technique but it has some issues like visualization technique, privacy etc.
Big Data Tools: A Deep Dive into Essential ToolsFredReynolds2
Today, practically every firm uses big data to gain a competitive advantage in the market. With this in mind, freely available big data tools for analysis and processing are a cost-effective and beneficial choice for enterprises. Hadoop is the sector’s leading open-source initiative and big data tidal roller. Moreover, this is not the final chapter! Numerous other businesses pursue Hadoop’s free and open-source path.
Big data is data that, by virtue of its velocity, volume, or variety (the three Vs), cannot be easily stored or analyzed with traditional methods. Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware.
Available Research Topics in Machine LearningTechsparks
Due to the continuous the development in IT sector, research students have good chance in preparing their research papers in the field of the computer science. Although there are many subject areas that students opt for preparing their research papers, the most leading one is machine learning. What is the Machine Learning and why it is a leading subject area? Machine learning is an approach to analyzing the data. It is the applicable to automate construction of an analytical system. Considered one of the best sub-fields of artificial intelligence, machine learning allows systems to gain knowledge from the given data, recognize the patterns, and act accordingly without any human interference. Basically, machines are trained on how to learn and recognize various patterns in a given dataset, hence its name-'machine learning'. Both-small and big companies are using set of rules to develop models for getting better at the decision-making process without any human interference.
A planned, complete, and modernized strategy can help you to complete your Ph.D. thesis in an effective way. Major Key points may help you to achieve your degree on valid time. Qualifying for Ph.D. is a tedious, examination, and broad process. The researcher has to endure constantly working hard work to meet the deadlines.
Some very knowledgeable topics in Computer Networking provided by the best guides of Techsparks, we have the finest writers who assist with writing the best dissertations.
Get best thesis topics in machine learning from Experienced Ph.D. Writers at Techsparks with 100% Plagiarism Free Work & Affordable price. Our goal is to make students free from their assignments burden, by providing the best thesis assistance. For more details call us at-9465330425 or Visit at: https://bit.ly/3zRB3vN
Techsparks has been successful in creating its mark among the major Institutes For Thesis which are indulged in guiding the M.tech thesis project students residing in different corners of the world including Patna, Bihar , Punjab , New Delhi , Canada , USA and many more. http://www.techsparks.co.in
Software engineering - Topics and Research AreasTechsparks
Software Engineering is a trending topic for project, thesis, and research. There are various subfields under software engineering which will be helpful for engineering students.
http://www.techsparks.co.in/
Cloud computing and Cloud Security - Basics and TerminologiesTechsparks
Cloud Computing is a new trending field these days and is an Internet-based service. It is based on the concept of virtualization.
http://www.techsparks.co.in
How to write a thesis - Guidelines to Thesis WritingTechsparks
A thesis is an important part of the academics of the master's students. Without the submission of the thesis, a degree is not conferred to a student. Follow the slides to know the procedure of thesis writing.
http://www.techsparks.co.in
Matlab is programming language developed by MathWorks that provides a computing environment for programming.
www.techsparks.co.in/introduction-and-basics-of-matlab/
Digital Communication simply means devices communicating with each other in through digital signals. The signals are digitized and then the information is transferred through these digitized signals from source to destination.
But why Digital Communication or Digitization is needed?
Topics in wireless communication for project and thesisTechsparks
There are various topics in wireless communication which you can choose for your thesis.
You can call on this number for any query on this topic : +91- 9465330425
http://www.techsparks.co.in/thesis-topics-in-wireless-communication/
Techsparks deals with Thesis guidance and research work for M.Tech , PhD Students.
If you are looking for professional thesis guidance then of course you are at the right place. www.techsparks.co.in/
Techsparks deals with Thesis guidance and research work for M.Tech , PhD Students.
If you are looking for professional thesis guidance then of course you are at the right place. https://goo.gl/vfn68K
How to get published in Scopus/ IEEE journalsTechsparks
Before you start thinking about where to submit your article, you need to consider what you are planning to publish. What are you trying to say and how can you say it effectively? What kind of thesis topic for m.tech would suit your findings the best? A research thesis is a fully developed presentation of your work and its findings. It should be a discrete piece of research, with an introduction, rationale, methodology, results, discussion and conclusion. https://goo.gl/2xwh3J
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
3. Introduction
Big Data refers to large volume of data which may be structured or
unstructured and which make use of certain new technologies and techniques
to handle it. Organised form of data is known as structured data while
unorganised form of data is known as unstructured data. The data sets in
big data are so large and complex that we cannot handle them using
traditional application softwares. There are certain frameworks like Hadoop
designed for processing big data. These techniques are also used to extract
useful insights from data using predictive analysis, user behavior and
analytics.
4. 3 Vs of Big Data
● Volume – It refers to the amount of data that is generated. The data can be low-density, high
volume, structured/unstructured or data with unknown value. This unknown data is converted
into useful one using technologies like Hadoop. The data can range from terabytes to
petabytes.
● Velocity – It refers to the rate at which the data is generated. The data is received at
an unprecedented speed and is acted upon in a timely manner. It also require real time
evaluation and action in case of Internet of Things(IoT) applications
● Variety – Variety refers to different formats of data. It may be structured, unstructured or
semistructured. The data can be audio, video, text or email. In this additional
processing is required to derive the meaning of data and also to support the metadata.
5. Hadoop
Hadoop is an open-source framework
provided to process and store big
data. Hadoop make use of simple
programming models to process big
data in a distributed environment
across clusters of computers. Hadoop
provides storage for large volume of
data along with advanced processing
power. It also gives the ability to
handle multiple tasks and jobs.
7. HDFS is the main component of Hadoop architecture. It stands for Hadoop
Distributed File Systems. It is used to store large amount of data and multiple
machines are used for this storage. MapReduce Overview is another component of
big data architecture. The data is processed here in a distributed manner across
multiple machines. YARN component is used for data processing resources like
CPU, RAM, and memory. Resource Manager and Node Manager are the elements of
YARN. These two elements work as master and slave. Resource Manager is the
master and assigns resources to the slave i.e. Node Manager. Node Manager sends
signal to the master when it is going to start the work. Big Data Hadoop for thesis
will be plus point for you.
9. Hadoop is important in Big Data due to:
● Processing of huge chunks of data – With Hadoop, we can process and store huge amount of data mainly the
data from social media and IoT(Internet of Things) applications.
● Computation power – The computation power of hadoop is high as it can process big data pretty fast. Hadoop
make use of distributed models for processing of data.
● Fault tolerance – Hadoop provide protection against any form of malware as well as from hardware failure. If a
node in the distributed model goes down, then other nodes continue to function.
● Flexibility – As much data as you require can be stored using Hadoop. There is no requirement of
preprocessing the data.
● Low Cost – Hadoop is an open-source framework and free to use. It provides additional hardware to store the
large quantities of data.
● Scalability – The system can be grown easily just by adding nodes in the system according to the requirements.
Minimal administration is required.
10. Applications of Big Data
Government
Big Data is used within governmental services with efficiency in cost, productivity and innovation. The
common example of this is the Indian Elections of 2014 in which BJP tried this to win the elections.
Finance
Big Data is used in finance for market prediction. It is used for compliance and regulatory reporting,
risk analysis, fraud detection, high speed trading and for analytics.
Healthcare
Big Data is used in healthcare services for clinical data analysis, disease pattern analysis, medical
devices and medicines supply, drug discovery and various other such analytics.
11. Media
Media uses Big Data for various mechanisms like ad targeting, forecasting,
clickstream analytics, campaign management and loyalty programs. It is mainly
focused on following three points:
Targeting consumers
Capturing of data
Data journalism
Information Technology
Big Data has helped employees working in Information Technology to work
efficiently and for widespread distribution of Information Technology.
12. Challenges of Big
Data
The main challenges of Big Data are:
Data Storage and quality of Data – The data is
growing at a fast pace as the number of companies and
organizations are growing. Proper storage of this data
has become a challenge.
Lack of big data analysts – There is huge demand for
data scientists and analysts who can understand and
analyze this data.
Quality Analysis - The data should also be accurate as
inaccurate data can lead to wrong decisions that will
affect the company's business.
Security and Privacy of Data – Security and privacy
are the biggest risks in big data.