Are there any ongoing work to implement artificial intelligence for the analysis processes of large collections of information collected in Big Data database systems?
Business entity management processes are more and more often supported by computerized Business Intelligence platforms that facilitate multi-criteria analysis and reporting.
Probably in the future, the business analyst will be supported by artificial intelligence.
It would be a great advance in the field of automation and objectification of multi-criteria economic analyzes of business entities.
Complex, multi-criteria analyzes regarding the verification of large companies' operations require aggregation and analytical processing of large data sets in Big Data database systems.
However, in what direction will technological progress be realized in this field?
In the future, as part of the progressing computerization of analytical processes, it will be possible to implement artificial intelligence to the processes of analyzing large collections of information collected in Big Data database systems.
In view of the above, I am asking you: Are there any ongoing works to implement artificial intelligence to the processes of analyzing large collections of information collected in Big Data database systems?
Please, answer, comments. I invite you to the discussion.
Hi Dariusz,
That's a great topic indeed. I guess the assistance of AI in such applications requires a certain level of maturity (technology and policy) before it can really be exploited in real settings. That is for different reasons. First, the resistance to changes brought by a new technology has been well observed throughout different implementations of information systems across the years and in different contexts (ERP, e-Government, e-Learning etc...). I believe such resistance will be even more fierce when it comes to tap on routine processes governed by old and well-established policies, especially within certain cultures (e.g. high power distance). Second, AI (along other intelligent computing techniques) can be harnessed in business entity management (BEM) for different purposes. For instance, AI can act as an enabler for improvement as it observes as-is processes and identifies bottlenecks and inefficiencies. It can therefore recommend improvements and, probably, transformation options of as-is processes to to-be more-efficient processes. A second perspective of AI in BEM can be, as you mentioned, by assisting human analysts in better performing their jobs. There are many other potential applications of AI in BEM. However, having a clear view of where AI can help in the short-run in the context of BEM is very important and as long as this view is not complete, AI won't mature up enough to be used the way you are mentioning. Third, governance! There is no doubt now that technology has won the race against business needs. In fact, many processes are penalized from improvements due to rigid governance schemes and outdated policies that may resist new-entering technologies. On the other hand, no technology can serve to the maximum of its capacity if it is not adopted and/or institutionalized by the policies governing BEMs. Unfortunately, that takes ages. Probably researching ways on how to accelerate this process of tech adoption by governing bodies worth investigation, especially for AI, BI, ML, DL and other game-changing techs.
Regarding the Big Data part in your question, accessibility is a main problem hindering many projects from achieving what you are looking for. Again, this can be attributed to governance.
AI and Big Data are becoming closely interconnected and that the greater availability of data is empowering AI and cognitive initiatives.
Dear Dariusz
ANN uses for big data set also, but you need so requirement to do it fast like very good PC with high performance.
Dear Dariusz ,
AI is emerging with all latest technologies such as big data analytics, cloud, IoT etc. Specifically big data and AI is really coming up with attractive research challenges. When you say AI it's about making systems smart enough to take decisions by thinking of all the factors and big data is about taking smart decision from tremendously large data so it's naturally interconnected. Though the existing systems are evolving to be robust enough to apply AI with big data.
Surly its used in analysing social network messages and big data servers such as google and youtube..
In social network.. messages are analysed to detect terrorism traffic..
Servers for youtube chase the legalized videos and publication rights for movies and songs
Dear Friends and Colleagues of RG
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.
Best wishes
Artificial intelligence is used in the analysis of large data for its effective effect in the interpretation and analysis of data. Examples of applications of artificial intelligence are fuzzy logic. Its advantage is the use of natural language in data analysis
Yes, we use AI to find and match patterns and motifs in large network(relational) data sets. In this report we looked at 67K nodes and 1M relationships...
See Part II: Swimming Upstream
Technical Report The Healing Economy: An Economic Development Framework for Cleveland
Yes..Since 2012 ,AI with Big Data has been used at production level in various Big MNC's and also in research centers.
Best regards!
Gourav Gupta
Certainly because the main reason for the emergence of artificial intelligence is the organizations deal with large amounts of data, so artificial intelligence deals with this data efficiently and effectively
Of course it is, maybe not as often as people might think since big data is not the same than large size data, velocity of data ingestion and variability of data types must be present, In any case, there are a few examples of AI being applied into Big Data and I would say that the most well know case is Google Maps when giving travelling direction advise.
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