Data analysis is a critical component of any business, and with the emergence of artificial intelligence (AI), it has become easier than ever to access powerful data analysis tools. AI-as-a-service provides a range of options for businesses to analyze their data quickly and accurately. From Splunk and Looker to MonkeyLearn and Akkio, there are a variety of AI data analysis tools available to help businesses make sense of their data. Splunk is a widely used software platform for searching, analyzing, and visualizing data in real time.
It is a powerful tool that can process large databases, allowing users to create multiple dashboards and reports and condense all their data sources into one. Looker, part of Google Cloud, is another no-code data analysis and business intelligence tool with powerful capabilities and multiple integrations. It is capable of processing large databases, allowing users to create multiple dashboards and reports and condense all their data sources into one. AI data analysis tools, such as MonkeyLearn, can locate, clean, analyze, and visualize your data with virtually no need for human intervention. The results are fast, making even big data seem small and making the process scalable for any need.
Imagine performing an opinion analysis on thousands of tweets about your brand just as you launch a new product, to find customer feedback in real time and then follow it as it changes over time. With AI becoming more advanced, AI is becoming a more powerful, efficient, and accessible solution for processing data. Akkio uses 80 percent of the loaded data as training data and the remaining 20 percent is used as validation data. This allows the AI to learn from the training data and then test its accuracy on the validation data. This ensures that the AI is able to accurately analyze the data without any human intervention. Another great option for data analysts is Polymer, which is a robust AI tool that offers powerful AI to transform data into an agile, flexible, and powerful database.
It can also be used to configure text classifiers and text extractors, which help to automatically classify data according to topic or intention as well as extract product features or user data. As mentioned above, AI data analysis can go beyond simple diagnostic analyses of quantitative data and address qualitative data for diagnostic, predictive, and prescriptive analyses. By “feeding machine learning algorithms with labeled text samples” also known as training data, AI tools can learn from this data. This allows businesses to gain insights from their data that would otherwise be impossible to obtain without the help of AI. AI-as-a-service provides businesses with access to powerful tools that can help them make sense of their data quickly and accurately. From Splunk and Looker to MonkeyLearn and Akkio, there are a variety of AI data analysis tools available that can help businesses unlock the power of their data. In conclusion, AI-based tools are becoming increasingly popular among businesses due to their ability to quickly process large amounts of data with minimal human intervention.
By leveraging these tools, businesses can gain valuable insights from their data that would otherwise be impossible to obtain without the help of AI.
