10 Top Business Intelligence Platform for Data Processing

Business Intelligence Platform – AI (Artificial Intelligence) technology or artificial intelligence is developing rapidly and making big changes in various industrial fields.

This is because almost all large companies use AI to improve their business processes, from manufacturing to operations, to customer experience. Therefore AI software tools can help optimize your projects and business.

Artificial Intelligence (AI) has become a modern technology in all aspects. The application of artificial intelligence greatly facilitates various jobs, including in the business world. When you use Siri’s virtual assistant to find information using your voice, “Where is the nearest restaurant?

When you use Spotify to search for music or movies that match your interests, when you find advertisements for the item you are looking for or have previously seen on e-commerce, do you realize that at that time you are being exposed to artificial intelligence? Artificial intelligence no longer only appears in science fiction films. But it has manifested itself in your daily life.

10 Top Business Intelligence Platform for Data Processing


1. Jupiter Notebooks

Can really help those of you who are struggling in the fields of data science, analysis, and machine learning because the system can run code in an interactive environment and includes documentation and visualizations in the same notebook.


So you can use Jupyter Notebook to jot down the code and can directly use the code without rewriting the code needed.

Jupyter Notebook can be used for several programming languages such as Python, R, and Julia. Jupyter Notebook also includes features that make coding easier such as autocomplete, syntax highlighting, and debugging.

2. Content DNA Platform

Is a platform that uses artificial intelligence (AI) technology to analyze and extract information from digital content, especially videos. This platform can extract data from various types of content such as text, images, videos, and audio.

Then these platforms can analyze it to determine the main themes, emotions, entities and other categories associated with the content.

Content DNA Platform is often used by broadcasters and telecommunications companies to perform various video-related tasks, such as scene recognition, anomaly detection, and metadata enrichment.

Even if you are not a professional in this field, you can still create great digital content with the Content DNA Platform due to its ease of use.

3. Google Cloud AI Platform

With this platform, you can create ML applications for various fields such as computer vision, translation, natural language processing, video, and others using trained cloud APIs.


In addition, the platform is supported by most of the widely used open-source frameworks, such as PyTorch, TensorFlow, and scikit-learn. So with Google Cloud AI Platform, you can easily integrate and use it in large enterprise projects.

4. Chorus. ai

Chorus.ai is a software used to analyze telephone or video conversations conducted by sales or customer service teams.

The app provides automatic transcription features, in-depth conversation analysis and in-depth performance reports. With these three main features, chorus.ai can improve the performance of corporate teams.

By providing in-depth analysis of how the conversation is conducted and will provide suggestions for improving sales performance.

5. Viso Suite Platforms

This platform offers the software infrastructure to create, implement, scale, and protect AI vision applications. You can extract important data from videos and images, such as text, emotions, entities and other categories.


As such, the Viso Suite Platform is frequently used by some of the world’s largest businesses to implement and maintain their portfolio of computer vision applications.

6. Observe. AI

Observe.ai is an advanced solution that will help companies to improve interaction with their customers. This platform provides voice and text analysis features to identify trends and determine customer satisfaction levels.

In addition, Observe.ai provides training for company staff to improve the quality of their interactions with customers. With observe.ai, companies can improve customer satisfaction and improve the quality of interactions with customers effectively.

7. IBM Watson

IBM Watson is an AI platform that can be used for data analysis, natural language processing and data management.

Its advantages are its ability to handle large and complex data, and can be used in various languages. However, the cost is quite expensive and requires large resources.


But don’t worry, it’s worth the money because IBM Watson can help companies automate complex machine learning processes, predict future outcomes, and optimize their company’s employee time.

8. Infosys Nia

Infosys Nia is an AI software platform created to make it easier for companies to implement AI. This platform will help a job that uses machine learning, deep learning, data management, natural language processing (NLP), etc.


With infosys nia, companies can automatically process and analyze the big data they have, so companies can make better decisions and improve business efficiency.

9. Business Intelligence Platform C3 AI

C3 AI is a technology company that focuses on developing intelligent computing systems or artificial intelligence for use in various industries, such as oil and gas companies, banking and healthcare.

They provide a platform that enables companies to pursue business gains by using data analytics and AI in their business processes. Specifically, C3 AI provides AI solutions that can be used to improve operational efficiency, reduce costs, and improve product and service quality.

10. Business Intelligence Platform H2O.ai

H2O.ai is a technology company that offers an open-source platform for data analytics and machine learning. With AutoML, anyone be it a professional or a novice can create or train AI models.


The platform supports various types of data including tabular, text, images, audio and video. H2O.ai will manage digital advertising, claims administration, fraud detection, creating virtual assistants and other tasks with the help of machine learning for enterprises.

Counterproductive Performance of Artificial Intelligence

Even so, that doesn’t mean Hawking’s worries can be ignored. The application of AI on an industrial scale has had an unwanted impact on some humans. One of the reasons is because AI will eliminate many job opportunities.

People who are less skilled at work are the ones most worried about having their jobs taken over by AI. Robots have taken up many jobs on the assembly line. He can do complex tasks very well, and in fact, they take on a lot of low-skilled jobs.

Another thing that is counterproductive to AI is its “inhumanity”. A real example occurred when there was a shooting and hostage-taking drama in downtown Sydney, Australia in 2014. In a panic, people started calling Uber to get out of the affected area.

So, because there is a surge in demand that is concentrated in one area, Uber’s algorithm automatically increases rates around the scene. Many consumers were angry because they felt squeezed during the crisis.

Thus, AI does not have the ability to make judgments, and may never acquire that ability. This incident forced Uber to re-evaluate its algorithm when handling emergencies. But one thing is clear, Uber’s AI has left a very unpleasant experience for its customers in Australia.

On a larger scale, many humans fear AI domination in the hands of the wrong people. AI does not humanize war. Countries that have advanced technology can kill humans without involving actual humans.

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That is the review Terraveu.com have prepared about the 10 Top Business Intelligence Platforms for Data Processing. That’s it and thank you!!