How about predicting your company’s sales performance for the next few months? What if you could recognise particular patterns in your social media performance data to tune in strategically to your targeted audience? What if you could identify the appropriate target audience for your product and use the proper strategy to drive sales?

For a result-oriented strategy to result in profit, AI in data analysis plays a pivotal role in offering a better and unique approach. For the firms to develop informed decisions on core functions, converting the raw data into valuable insights is essential. Manual data analysis, which is slow and less effective, is now more feasible in a limited time using AI tools. The availability of multiple AI tools that can assist in visualisation, analysis, and data tracking immediately is the best part of data analytics. It helps to find meaningful insights and reach the 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 approachable methods of data processing. AI can analyse a huge amount of data to find trends and patterns that can be used to derive insights for enhancing business processes. AI can also be leveraged to streamline data analysis by funnelling all data into one solution, allowing users to have an entire overview of data.

Let’s explore a few AI-powered data analysis tools that are key for organisations aiming to succeed in this data-driven world.

Tableau

Tableau is one of the top-rated tools, an analytics and data visualisation platform that allows users to engage with their data. Users are able to create reports and share them across desktop and mobile platforms with the help of Tableau. This data analytics tool aids data visualisation and analytics in developing reports that can be shared within a browser or embedded in an app. This is possible while the platform is run on the cloud or on-premise. All of this can occur while Tableau is run on the cloud or on-premise. The advantages include:

• It supports complex computations, data blending, and dashboarding. 
• Immediately develop interactive visualisations. 
• Ease in implementation
• Manages humungous data. 

Microsoft Power BI

Microsoft Power BI is a better option for data analysis, and it can be mainly used as a business intelligence platform that aids users in sorting through their data and visualising them for insights. Moreover, the platform enables users to import data from all kinds of sources, and they can develop reports and dashboards immediately. It also helps users to make machine learning models and utilise other AI-powered features in data analysis. Some of the advantages include:

• Seamless integration with current applications.
• Develop personalised dashboards. 
• Assist in publishing secure reports.
• Absence of memory and speed constraints. 

MonkeyLearn

MonkeyLearn is another no-coding platform that leverages the power of AI in data analysis to assist users in visualising and rearranging their data. It consists of multiple AI-based text analysis tools that can immediately analyse and visualise data to meet users’ requirements. Moreover, the platform can be utilised to set up text classifiers and text extractors, which aids in automatically sorting data as per the topic and extracting product features or user data. Some of the advantages include:

• Classifies text in labels effortlessly.
• Easy to clean, organise, and visualise feedback. 
• No coding is required. 
• Saves time by automating business workflows and analysing text. 

Akkio

Akkio is a business analytics and forecasting tool for users to analyse their data and foresee potential outcomes. The tool is predominantly for beginners and ideal for users who want to start with their data. Moreover, 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. It is more advantageous for predictive analysis, marketing, and sales. Some advantages 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 the models.

Qlik

Qlik can be utilised mainly by users from technical and non-technical backgrounds. It offers multiple data exploration features. Features like team collaboration with easy drag and drop options and workflows available to operate data as per specific likes and needs. Some advantages include:

• Offers custom and embedded analytics.  
• Reporting and alerting abilities
• Quick calculations with data
• Patterns and trends detection
• Syncs and extracts information from other websites
• Connect with multiple sources of information for data analysis.

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