How about predicting your company’s business performance for the next few months? What if you could recognize particular patterns in your social media performance data to strategically tailor to your target audience? What if you could identify the appropriate target audience for your product and use the appropriate strategy to drive sales?
For a results-driven strategy to generate profits, AI in data analysis plays a pivotal role in providing a better and unique approach. For businesses to make informed decisions about their core functions, it is essential to convert raw data into valuable insights. Manual data analysis, slow and less efficient, is now more feasible in a limited time thanks to AI tools. The availability of multiple AI tools that can immediately help with data visualization, analysis, and tracking is the major strength of data analytics. This helps in finding meaningful information and achieving business goals.
AI in analytics
Artificial intelligence is considered the driving force behind any effective data analytics strategy. It is one of the most powerful, efficient and accessible data processing methods. AI can analyze a huge amount of data to find trends and patterns that can be used to gain insights to improve business processes. AI can also be leveraged to streamline data analysis by bringing all data into one solution, allowing users to have a comprehensive view of the data.
Let’s explore some AI-powered data analysis tools that are essential for organizations that want to succeed in this data-driven world.
Tableau is one of the top-rated tools, a data analysis and visualization platform that allows users to interact with their data. Users can create reports and share them across desktop and mobile platforms using Tableau. This data analysis tool makes it easy to visualize and analyze data in developing reports that can be shared in a browser or embedded in an application. This is possible when the platform is running on the cloud or on-premises. All of this can happen when Tableau is running in the cloud or on-premises. Benefits include:
- It supports complex calculations, data fusion, and dashboard creation.
- Immediately develop interactive visualizations.
- Ease of implementation
- Handles huge data.
Microsoft Power BI is a better option for data analysis and can be mainly used as a business intelligence platform that helps users sort their data and visualize it for insights. Additionally, the platform allows users to import data from all kinds of sources and immediately develop reports and dashboards. It also helps users create machine learning models and use other AI-based features in data analysis. Some of the benefits include:
- Seamless integration with current applications.
- Develop custom dashboards.
- Assist in publishing secure reports.
- No memory and speed constraints.
MonkeyLearn is another no-coding platform that leverages the power of AI in data analysis to help users visualize and reorganize their data. It consists of several AI-based text analytics tools that can immediately analyze and visualize data to meet user needs. Additionally, the platform can be used to configure text classifiers and text extractors, making it easier to automatically sort data by topic and extract product features or user data. Some of the benefits include:
- Classifies text into labels effortlessly.
- Easy to clean, organize and view comments.
- No coding is required.
- Save time by automating business workflows and analyzing text.
Akkio is a business analysis and forecasting tool that allows users to analyze their data and predict potential outcomes. The tool is primarily aimed at beginners and ideal for users who want to get started with their data. Additionally, the tool helps them upload their dataset and choose the variable they want to predict, which helps Akkio develop a neutral network around that variable. This is more beneficial for predictive analytics, marketing and sales. Some benefits include:
- No-code machine learning platform.
- It is best for beginners looking to get started with data.
- Build a neural network around selected variables.
- Accuracy rating for models.
Qlik can be used primarily by users with technical and non-technical backgrounds. It offers several data mining features. Features like team collaboration with simple drag-and-drop options and workflows available to leverage data according to specific tastes and needs. Some benefits include:
- Offers personalized and integrated analytics.
- Reporting and alerting capabilities
- Fast calculations with data
- Pattern and trend detection
- Synchronizes and extracts information from other websites
- Connect to multiple information sources for data analysis.
