The question of the accuracy of prognostic research carried out on the basis of an analysis of the sentiment of verifying the comments of Internet users archived in Big Data systems?
Currently, many research centers use sentiment analysis by examining the content of comments, posts and news of thousands or millions of users of social media portals and other websites. The sentiment analysis is carried out on large collections of information collected from the deliberately selected many websites and stored in Big Data database systems. This analysis is carried out periodically at specific time intervals to diagnose changes in the main trends of general social awareness, including opinions on specific topics in society. This analysis may also refer to the diagnosis of dominant political sympathies, specific political views and opinions on selected political topics. This analysis is also used to examine the public support at a given time for specific politicians, candidates in the presidential elections or parliamentary elections. If this type of sentiment analysis is carried out directly by presidential or parliamentary elections, then it can be treated as an additional research instrument of a prognostic nature. There were results obtained from this type of prognostic analyzes characterized by a high level of accuracy of prognostic research.
In view of the above, the current question is: The question of the accuracy of prognostic research carried out on the basis of an analysis of the sentiment of verifying the comments of Internet users archived in Big Data systems?
Please, answer, comments. I invite you to the discussion.
The above question inspired me to the following considerations:
Are you already familiar with the use of Big Data data analysis in the risk management process in corporations and financial institutions?
Large companies, corporations and financial institutions, including banks, are technologically and financially prepared to develop applications for analyzing large data sets collected in Big Data database systems in the process of managing individual categories of banking, financial, including credit, operational, market and IT systems. The main research issue is the study of potential clients, eg potential borrowers in the field of creditworthiness analysis by analyzing data collected in the Big Data database. In the Big Data database system, data on potential clients collected from the Internet from entries, comments, posts contained on social media portals can be collected. If the banks analyze the client's creditworthiness based on sensitive, personal and classified data downloaded from social media portals, then the ethics of this type of analytical process should be considered. This issue of ethics and personal data protection also arises when the insurance company verifies the health of a potential client who submitted an application for life insurance - based on what he writes about himself, he will report his status on social media portals. If the potential client was aware of the fact that he shares personal information with his friends on social media portals only with his friends and the bank, insurance company or other institution uses this secret without using the client's knowledge, then the problem of breaking the basic ethical principles in business arises.
In view of the above, I am asking you the following question: Are you already familiar with the use of Big Data data analysis in the risk management process in corporations and financial institutions?
Please, answer, comments. I invite you to the discussion.
What kind of research dominate in the analysis of data collected in Big Data database systems?
First of all, as part of the processing of information collected in the Big Data database systems, the sentiment analysis is used very frequently during analytical processes conducted for the needs of scientific research. Sentiment analysis allows you to get an answer to the question, what is, for example, recognizability, what is the awareness, opinion on a specific topic among users of specific Internet portals, websites containing comments from Internet users, and social media portals.
I invite you to the discussion
To what extent the Big Data data sentiment analysis from social media portals can be used in forecasting the company's development?
Large amounts of information downloaded from comments, entries, posts from social media portals are processed in Big Data database systems to determine, for example, consumers' awareness of the offer of products and services of specific companies. This type of information is of great importance for the planning of advertising campaigns informing about the mission, idea, product offer, and the usability features of the company's offer. This type of data may be important for forecasting the changing preferences of consumers regarding the offer of specific companies.
In view of the above, I am asking you: To what extent the Big Data data sentiment analysis from social media portals can be used in forecasting the company's development?
Please reply. I invite you to the discussion
How can you use the data processing technologies in the cloud in Big Data database systems for the purpose of creating innovations?
If in many research works, for the purposes of conducted scientific research, the analysis of information collected in Big Data database systems is already used, more and more attempts will be made by various research centers to use data processing in the cloud data collected in Big Data database systems. The data mining technology, artificial intelligence, busieness intelligence and other advanced information and analytical technologies will also be added to this.
I invite you to the discussion
How to use data processing technologies in Big Data database systems for modern education 4.0?
In the field of technological fields that are developing strongly and co-create the current technological revolution referred to as Industry 4.0, data processing in the cloud computing information collected in Big Data database systems is included. In this way, you can conduct an analysis of the sentiment of evaluation of products and services made by consumers on discussion forums and in entries, comments, posts, recordings, banners posted on social media portals. All these tecnologies are already available for education and can be used both in modern education 4.0 as well as in ongoing research.
At present, in the age of the technological revolution known as the 4.0 industry, new teaching concepts are being defined as education 4.0.
The technological revolution in recent years, known as Industry 4.0, is motivated by the development of the following factors:
Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence.
In addition, in the knowledge-based economy, the important areas of knowledge and technologies that are developed are primarily the development of data processing analytics in Business Intelligence enterprises, the development of life science technologies, biotechnology, eco-innovation, energy, medical intelligence, etc.
On the basis of the development of the new technological solutions mentioned in recent years, the processes of innovatively organized analyzes of large information collections gathered in Big Data database systems dynamically develop.
Therefore, I am asking you with the following query: How to use data processing technologies in Big Data database systems for modern education 4.0?
Please, answer, comments. I invite you to the discussion.
Are you aware of specific risk management systems that use the processing of information collected in Big Data database systems?
The improvement of specific risk management systems is particularly important in many areas of functioning of commercial business entities, financial institutions, public institutions as well as conducting investment, research and other projects.
How important is this is, for example, the global financial crisis that appeared in mid-September 2008, when specific financial, investment and credit risk management systems were not properly improved and the procedures of investment activity, including credit, were not carried out reliably, as well as customer service, and violation of business ethics in investment banks operating at the time and many other types of financial institutions and business entities.
please reply
Will new data processing technologies in Big Data database systems allow for precise prediction of climate disasters?
In my country, more than a dozen years ago or more, there were real winters with snow and frost after the autumn. Whereas last winter, during the last few years it looked like autumn, without snow and positive temperatures. I think that the greenhouse effect, ie the warming of the Earth's climate, has already begun. This is also confirmed by numerous climatic cataclysms and weather anomalies, which in the current year 2018 appear in numerous places on the Earth. In some parts of the Earth there are fires of huge forest areas such as in Scandinavia, California in the USA, Australia, the Iberian Peninsula, Africa, etc. In addition, weather anomalies, e.g. snow and floods in October and November in the south of Europe.
In addition, tornadoes in many places on Earth and so on.
Perhaps these problems will get worse. It is necessary to improve security systems and anti-crisis services, improve the prediction of these anomalies and climatic cataclysms so that people can, have managed to shelter or cope with the imminent cataclysm. One of the technologies that can help in more precise forecasting of these cataclysms is the processing of large collections of historical and current information on this subject in the cloud computing technology in Big Data database systems.
Therefore, I am asking you: Will new data processing technologies in Big Data database systems allow for accurate prediction of climate disasters?
Please, answer, comments. I invite you to the discussion.
Is the synergy and interdependence between the development of analytics conducted in Business Intelligence applications and the processing of data in the cloud in the Big Data database systems increased?
Currently, the amount of information collected in Big Data database systems is growing very fast.
Many companies that have their own Big Data database systems containing huge amounts of information downloaded from the Internet carry out analyzes of these data, the results of which are used in business management.
Many companies use these resources to manage their business. When processing information in the cloud, ie information collected in Big Data systems, the sentiment analysis uses the results of the analytical work carried out in this way for the strategic management of the company.
In view of the above, I am asking you: Is the synergy and interdependence between the development of analytics conducted in Business Intelligence applications and data processing in the cloud in the Big Data database systems increasing?
Please reply. I invite you to the discussion
Will the development of data processing technology accumulated in the Big Data banking database systems improve the credit risk management process or will it contribute to the development of Shadow Banking and the use of unethical practices for the surveillance of potential borrowers?
Large commercial banks generate high financial surpluses allowing for the implementation of modern integrated teleinformatic internet banking systems, Business Intelligence data analysis systems, data processing platforms in Big Data database systems, etc.
There were already situations of unethical use of modern ICT solutions, analysis of comments on social media portals, during which the bank verified the customer's data entered into the loan application by also scanning information that the potential borrower types in social media portals.
This informal verification took place without the knowledge of a potential borrower and could then be the basis for suing the bank.
However, the bank's client is not always aware of the fact that it can be invigilated in such a way by the public trust institutions that the bank should be.
Of course, these types of cases, which we know from the media is supposedly a margin of entire banking, which can be one of the categories of a new type of unethical practices typical of the so-called Shadow Banking.
However, only part of this type of information gets to the media.
Maybe this is just so-called "the tip of the iceberg" of this problem.
The situation is similar in the situation of cybercriminals' attack on bank IT systems or electronic banking platforms.
If it is possible to keep this type of events secret, then customers do not find out about it.
This is because media only receive information about some of these types of events.
Does any of you conduct research in this area?
If so, I invite you to cooperation.
I am asking for comments
When will artificial intelligence be implemented into the analytical Business Intelligence and Big Data systems and what will be the consequences?
The Business Intelligence systems currently being developed by IT technology companies and sold for companies support business management processes or a specific part of it. These systems, if they are connected to the Big Data database system and integrated with logistics, accounting, production, sales departments, inventories, relationships, contractors, financial institutions, etc., can significantly improve business management systems. If the whole system of obtaining and processing collected in Big Data information concerns all external and internal determinations of the company's operations and takes place in real time, the company has an excellent tool supporting decision-making processes. This type of tool allows you to make better decisions in the strategic and ongoing management of a company, corporation, financial institution or other type of business entity. However, in this area there is constant progress determined primarily by the creation of new ICT solutions, new data processing technologies, etc. Therefore, the following question arises: When will artificial intelligence be implemented into the analytical Business Intelligence systems and what are the consequences?
Will business management become even easier after implementing artificial intelligence in Business Intelligence business intelligence systems? And if so, for what kind of business entities? or only for large corporations and financial institutions, in which millions of different categories of information are being processed on a daily basis, or such new-generation systems supporting decision making, will also be available for smaller companies and enterprises from the SME sector?
I am asking for answers, comments. I invite you to the discussion.
Are commercial banks already introducing sentiment analysis conducted on Big Data data collected from social media portals to the standard of customer verification procedures?
Financial institutions are already introducing an analysis of sentiment carried out on Big Data data collected from social media portals to customer verification procedures.
Inclusion of the sentiment analysis conducted on Big Data collected from social media portals could be an important additional information on the economic and financial situation of the potential client. This type of information can be a significant additional factor of full verification, eg creditworthiness of a potential borrower. I know that some service companies, marketing companies, insurance companies and banks include the sentiment analysis carried out on data collected in Big Data database systems collected from social media portals for verification of potential customers. But is it already becoming a standard or is it only at the design stage for now?
Please, answer, comments. I invite you to the discussion.
Will Big Data database technologies be available in the future also for companies from the SME sector?
Advanced technologies of digitalization and automation of data processing first find their application in business. Then also in public institutions can be introduced including in the field of e-governance. This also applies to Big Data database technologies, which is applicable in various sectors of the economy, but due to the high investment costs of implementing this technology in the business processes of business entities, so far only large corporations and larger enterprises can afford such technologies. However, in the future, investment costs of implementing tech technologies into business processes should decrease and processing technologies and data collection in Big Data database systems should be available also for smaller companies, including business entities of the SME sector.
I invite you to the discussion.
Will the information collected and processed in the Big Data database systems in future be able to accurately check future climate disasters?
Information collected and processed in Big Data database systems from climate change
In my opinion, information obtained from various research centers, meteorological centers, satellites, etc., then collected and processed in Big Data database systems should help in more and more precise prediction of new, unfavorable weather phenomena, including climatic cataclysms and others. In this way, earlier and in a more planned way, crisis management systems can be organized in the situation when the predetermined flood disaster becomes real and will happen. Gradually increasing computing power of powerful computer servers managing platforms of Big Data database systems, implemented artificial intelligence, increasing number of verified historical data on the overall climate phenomena on Earth will allow in the future more precisely, more accurately determine the level of threats, risk value, predict time, place and scale adverse weather events, i.e. also cataclysms that threaten people's lives.
Therefore, the question is still valid:
Will the information collected and processed in the Big Data database systems in future be able to accurately check future climate disasters?
Please, answer, comments. I invite you to the discussion.
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
Article The Big Data technologies as an important factor of electron...
Article The Technological Solutions Big Data and the Importance of B...
I invite you to discussion and cooperation. Greetings
The above question inspired me to the following considerations:
The goal of predictive analysis is to develop predictions for the development of complex, multifaceted processes in various fields of science, industry, economy or other spheres of human activity. In addition, predictive analysis may refer to objectively performing processes such as natural phenomena, climate change, geological, cosmic etc.
Predictive analysis should be based on taking into account in the analytical methodology possible the most modern prognostic models and a large amount of data necessary to perform the most accurate predictive analysis. In this way, the result of the prediction analysis performed will be the least subject to the risk of analytical error, ie an incorrectly designed forecast.
Predictive analysis can be improved by using computerized modern information technologies, which include computing in the cloud of large data sets stored in Big Data database systems. In the predictive analysis, Business Intelligence analytics and other innovative information technologies typical of the current fourth technological revolution, known as Industry 4.0, can also be used.
The current technological revolution known as Industry 4.0 is motivated by the development of the following factors:
Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies. On the basis of the development of the new technological solutions in recent years, dynamically developing processes of innovatively organized analyzes of large information sets stored in Big Data database systems and computing cloud computing for the needs of applications in such areas as: machine learning, Internet of Things, artificial intelligence are dynamically developing. , Business Intelligence.
For the abovementioned application examples, one can add predictive analyzes of subsequent, other fields of application of advanced technologies for the analysis of large data sets such as Medical Intelligence, Life Science, Green Energy, etc. Processing and multi-criteria analysis of large data sets in Big Data database systems is carried out according to V4 concepts, ie Volume (meaning a large number of data), Value (large values of certain parameters of the analyzed information), Velocity (high speed of new information) and Variety (high variety of information).
The advanced information processing and analysis technologies mentioned above are used more and more often for the needs of conducting predictive analyzes concerning, for example, marketing activities of various business entities that advertise their offer on the Internet or analyze the needs in this area reported by other entities, including companies, corporations, institutions financial and public. More and more commercial business entities and financial institutions conduct marketing activities on the Internet, including on social media portals.
More and more public institutions and business entities, including companies, banks and other entities, need to conduct multi-criteria analyzes on large data sets downloaded from the Internet describing the markets on which they operate, as well as contractors and clients with whom they cooperate.
On the other hand, there are already specialized technology companies that offer this type of analytical services, including offering predictive analysis services, develop custom reports, which are the result of multicriteria analyzes of large data sets obtained from various websites and from entries and comments. contained on social media portals based on sentiment analyzes of the content of entries in the comments of Internet users.
Dear Colleagues and Friends from RG
The key aspects and determinants of the applications of modern computerized information technologies for data processing in Big Data and Business Intelligence database systems for the purpose of conducting predictive analyzes are described in the following publications:
Article APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTEL...
Article The Big Data technologies as an important factor of electron...
Article The Technological Solutions Big Data and the Importance of B...
Article THE QUESTION OF THE SECURITY OF FACILITATING, COLLECTING AND...
I invite you to discussion and cooperation.
Best wishes
In addition, I propose the following research question in this area:
What are the main topics of Big Data research and analysis?
What are the topics of research and analysis carried out on large information collections using Big Data database systems?
Exchange the topics of research and analysis carried out on you with large collections of information, which can be used to increase the efficiency of research processes using computerized database systems built on Big Data platforms. In addition, analytics conducted on IT Business Intelligence platforms are used in some of such analytical processes.
Such topics of research and analysis conducted on large collections of information using Big Data database technology include:
- observation and analysis of chemical composition, light, issued sounds from billions of galaxies, planetary systems, stars, exoplanets, etc.,
- analysis of the composition of full genomes, genetic makeup and chromosomal information for specific species of life, including animals, plants, fungi, microbes; besides, also the analysis of the full composition of the human genome,
- analysis and prediction of atmospheric phenomena in correlation with the change of seismic activity, water currents in the oceans, cyclically changing solar activity, increasing in a given area of ??the condition and nature of environmental pollution,
- statistical and prognostic analysis of economic development of specific business entities, enterprises, companies, institutions, markets and entire national economies,
- analysis of the repayment of investment, consumer, mortgage and other loans, including the analysis of creditworthiness and financial credibility of business entities representing specific industries, sectors of the national economy,
- analysis of credit risk accepted in commercial banks at central banks and financial institutions 'supervision institutions, analysis of commercial banks' credit policies from the point of view of monetary policy of central banking,
- prognosis analysis of the situation on financial markets, including capital markets, stock exchanges,
- prediction of changes in the supply of electricity in the following days, weeks, months and years,
- analysis of the progressing pollution of the natural environment, including soil pollution, surface water, air, seas and oceans, growing unsorted and non-biodegradable waste landfills, including especially toxic waste, which are often illegally removed from the production processes of specific enterprises,
- analysis of the progressing process of greenhouse gas emissions from various sources, ie civilization and natural sciences, prognostic analysis of the trends of the ongoing global warming process and forecast of the trends of these processes in the following years.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
What else do you know about research topics and analyzes conducted on large information collections using Big Data database systems?
Please reply
I invite you to the discussion
Dear Colleagues and Friends from RG
The key aspects and determinants of applications of data processing technology in Big Data database systems are described in the following publications:
Article APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTEL...
Article The Big Data technologies as an important factor of electron...
Article The Technological Solutions Big Data and the Importance of B...
I invite you to discussion and cooperation.
Best wishes
- Badges
- Science topic
- Similar topics
- Mathematics
- Statistics
- Statistical Analysis
- Data Analysis
- Dataset
- Big Data