As a data analyst, I’ve always been on the lookout for ways to streamline my work and gain valuable insights faster. But with the sheer volume of data out there, it’s easy to feel like you’re drowning in information.
That’s where AI analytics tools come in – these cutting-edge tools use the latest in artificial intelligence technology to help you make sense of complex data sets and find hidden patterns and trends.
In this blog post, I’ll be exploring some of the best AI analytics tools on the market today, and showing you how they can help you take your data analysis game to the next level.
From natural language processing to predictive modeling, these tools are designed to make your life easier and your insights more powerful. So without wasting any more time let’s get started!
Tableau is an AI-powered analytics tool that helps people and organizations make informed decisions based on data. It offers a range of features that use machine learning, natural language, and smart data prep to quickly uncover insights and predictions.
Its augmented analytics capabilities help users of all levels, including those new to data analytics, explore and visualize data in a simple and fast way.
Its Business Science technology allows people with the domain expertise to make smarter decisions with no-code ML predictions, what-if scenario planning, and guided model building.
It also offers integrations with R, Python, MATLAB, and other data science tools to make statistical models more accessible. With transparent and trusted AI, Tableau empowers users to confidently stand behind their decisions.
With Power BI Desktop, you can easily access pre-trained machine learning models using AI Insights. These insights are found in the Power Query Editor and can be accessed through the Home and Add Column tabs.
With Text Analytics and Vision functions from Azure Cognitive Services, you can enhance your data in Power Query, and make transformations on the Power BI service without needing an Azure Cognitive Services subscription.
To use Text Analytics or Vision features, Power BI Premium is required. Power BI Desktop offers a range of functions, such as Detect Language, Extract Key Phrases, Score Sentiment, and Tag Images, which can be used to enrich your data.
You can conveniently apply Text Analytics or Vision functions in Power Query to enhance your data.
MonkeyLearn is an AI analytics tool that offers no-code text analytics to clean, label, and visualize customer feedback. It provides instant data visualizations and detailed insights, along with pre-built and custom machine-learning models.
Users can choose from a range of pre-trained classifiers and extractors, or build and train their own. It also simplifies text analytics with business templates tailored for different business scenarios. It offers native integrations, SQL connection, or API to connect to apps and BI tools.
The tool helps in strengthening promoters, converting passives and detractors, turning reviews into business improvements, finding weak links in products and business processes, increasing support team efficiencies, mining customer voices in survey responses, and becoming customer-centric.
In conclusion, the world of data analysis is rapidly evolving, and AI analytics tools are at the forefront of that evolution. By harnessing the power of artificial intelligence, we can gain valuable insights faster, make smarter decisions, and stay ahead of the curve.
But the future of data analysis is constantly evolving, and there are always new tools and techniques on the horizon. So I’ll leave you with this question: what do you think the next big thing in AI analytics will be?
In the meantime, be sure to share this post with your colleagues and friends, and let us know in the comments which of these tools you’re most excited to try out. And if you’re already using some of these tools in your work, we’d love to hear about your experiences.
That’s it for today, I hope you liked this post and will meet you soon with some new ai tools till then stay tuned.
