How artificial intelligence technologies contribute to analytical capabilities?
Thanks to advanced artificial intelligence technologies, data analytics has become:
1. More efficient thanks to automation.
2. They are more accessible thanks to the improved user interface.
3. Even more powerful, as texts and videos can be easily analyzed; something that was not available before.
How artificial intelligence is used for big data analytics?
Artificial intelligence simplifies the process of analyzing big data by automating and enhancing data preparation tasks. In addition to data visualization, predictive models and other other complex analytical tasks that consume a lot of time, human resources and funds. Artificial intelligence helps users to work with actionable insights, process and highlight them faster by processing complex huge data sets.
What does big data have to do with artificial intelligence?
Big data is the fuel that artificial intelligence works with. The huge amount of diverse data is what enables machine learning applications to acquire and master skills. The greater the amount of data available to artificial intelligence, the more it will be able to learn and improve its pattern recognition capabilities.
Advantages of artificial intelligence technologies for big data analytics
- Artificial intelligence technologies for data analytics have added a lot of advantages that have made data analysis in a privileged position. The most important of these advantages are:
- Data analytics has become automated. Artificial intelligence systems are able to independently analyze data. Based on the results of the analysis, they can take automated actions or highlight ideas to employees who can determine the best course of action.
The preparation of reports has become automated, which has facilitated access to data. Natural language generation (NLG) enabled automatic reporting.
Access to analytics has become easier. Users can use natural language to find answers easily and simply without the need for data scientists to extract insights from the data. This was supported by a natural language query (also called natural language interaction – NLI or natural language user interaction – NLUI). These developments allow democratizing analytics and citizen data scientists to quickly process large amounts of data. - The range of analytics is growing thanks to artificial intelligence. Unstructured data and personal information limited the scope of analytics before the advancement of artificial intelligence algorithms, but now, companies are able to use this data directly or indirectly in their analytical efforts.
- Unstructured data has become amenable to analysis. Artificial intelligence developments have made it possible to significantly expand the scope of analytics when compared to the days when Excel was the primary analytics tool.
Semi-structured data has become analyzable. Deep learning-based data mining solutions allow companies to extract entities from their semi-structured data and use it to understand their business in more detail.
New technologies have made it possible to analyze anonymized personal identification data and expand the scope of analytics. Anonymity via synthetic data is a rather outdated technique. But with the growing demand for analytics and increased protection of personal data, the demand for anonymized data has increased.
Now, thanks to artificial intelligence technologies for data analytics, companies selling synthetic data can create synthetic copies (generated automatically and anonymously but following the same distributions as the basic personally identifiable data) for their customers so that they can improve their offers.
Analytics has become more powerful. Companies are now relying on machine learning; the use of statistical techniques to enable computers to identify and learn patterns in given data, rather than being explicitly programmed for a specific job.
Artificial intelligence technologies for various data analytics have led some companies to achieve a breakthrough in their sales. Companies of various sizes and activities were also able to improve the quality of work and productivity. Arab countries are aiming to take advantage of artificial intelligence for data analytics to help them achieve digital transformation.
