AI Tools that Help with Data Visualization
Have you ever found yourself staring at endless spreadsheets, struggling to find any patterns or anomalies? Are you tired of manually extracting and standardizing monthly reports for similar datasets?
Well, gone are the days when this task was yours alone. The latest Artificial Intelligence (AI) tools can now automate mundane tasks related to data visualization and extracting insights. Here is how AI-based data visualization tools can help:
- Natural Language Processing (NLP): Allows users to interact with the platform as well as the datasets in natural language, making the platform more intuitive and enhancing user experience.
- Predictive analytics: Build AI models to communicate, forecast, and craft a story with graphs that could invariably help streamline operations, predict campaign outcomes, mitigate risks, and create refined marketing strategies.
- Data discovery: Uncover hidden patterns across all your datasets, creating a single view of all your data from various sources.
- Automated insights: Through AI and Machine Learning (ML), these tools can go deeper to analyze data trends and identify patterns, establishing all-encompassing reports.
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AI tools for data visualization
The market offers a variety of robust solutions when it comes to AI tools that can elevate your data visualization game. We take a look at how two tools - Tableau and Qlik Sense - can help automate your data visualization workflow.
List of AI-driven features in Tableau and Qlik Sense
Overview of Tableau and its AI capabilities
Tableau is a powerhouse for data visualization. It leverages machine learning and statistical models to simplify data analysis and generate interactive, customizable visualizations.
Tableau promotes “data culture” by equipping every team in the enterprise with data-driven insights. It ensures the organization realizes the full potential of its data, helping solve any business challenges.
How does Tableau work?
Tableau can connect with your database over multiple sources and provide a single view. It can connect and extract data from sources like Excel sheets, Oracle or Salesforce databases, SQL, AWS, Google Cloud, and other popular data sources.
With this single view, it is easy to transform and shape data for modeling, where you can create dashboards, charts, and graphs for better visualizations. These are created using Tableau Desktop which can be shared locally over the server, or publicly as required.
During the process of creating reports, you can ask questions to which Tableau can provide analysis and recommendations for data visualization.
If you are just getting started with Tableau and data visualization, then you can start with exploring Tableau Public. It is a free platform to create and publicly share data visualization dashboards, and more. It also has a 14-day free trial for Tableau Desktop before you choose to commit.
Example of Tableau Dashboard
As an example, consider a performance marketer who wants to build a comprehensive social media dashboard. With Tableau, it is possible to build one such dashboard where data insights can be viewed over a date range.
Tableau comes with multiple data visualization and prediction charts which also include scatter plot, line plot, pie chart, bar chart, heatmaps, Gantt chart, boxplot, etc.
Image-1 shows the sample dashboard, with the carousel showcasing more examples of dashboards that can be built on Tableau. For more such public dashboards, you can explore Tableau Public.
Overview of Qlik and its AI capabilities
For analytics, Qlik started with QlikView which is their classic analytics solution. However, at the time of this article, they have an upgraded version called Qlik Sense - a modern analytics platform that is smarter and AI-driven.
Qlik Sense leverages AI capabilities to understand and transform data effectively. It minimizes cognitive biases and amplifies discovery elevating the data literacy of the user.
How does Qlik Sense work?
Qlik Sense works on Qlik’s associative engine which enables users to link and associate data from varied sources like AWS, Google Cloud, IBM DB, SQL, MongoDB, and more.
Qlik’s associative engine works differently from query-based languages. While in query-based language, search and analysis happen on data relevant to the query, Qlik’s associative engine allows users to explore the complete dataset for their selection and query input. This allows the visual reports to be intuitive and have deeper insights.
Qlik Sense has a 30-day free trial in which you can access all its tutorials. Even though you might not have access to all the apps for integration, it would be enough to browse around the platform and gauge if it suits your needs.
In case you get stuck anywhere, you can always get assistance from NLP-enabled “Ask Insight Advisor”.
Example of Qlik Sense Dashboard
Qlik Sense library has prebuilt automated templates that can be customized as per your needs. There are dashboard examples available in their tutorials, as well as their website. You can also watch these free demo videos to help you get started.
For more of such dashboards, have a look at the publicly available ones by Qlik here. You can play around these dashboards by changing filters and parameters in real-time and see the impact.
Our recommendation
Best data visualization tool for medium to large enterprise with high data needs: Tableau
Best data visualization tool for those who want to level-up from Excel sheets or Google Data Studio: Qlik Sense
If you are a large enterprise that has data coming in from systems and applications by Oracle, Hadoop, or Salesforce, then Tableau should be your choice. While if you're a small to mid-sized enterprise with limited resources you can go for Qlik Sense.
Secondly, Qlik Sense prices start from $30 per month with full functionality, while for Tableau Cloud it is $15 per month. However, for the full functionality needed to build dashboards and work on reports, you need Tableau Desktop which starts at $70 per month for 1 user.
Hence, as far as pricing is concerned Qlik Sense is more affordable. However, always consider other factors like features, integration with existing systems, and the end objectives for using these tools.
Other options worth exploring - Looker Studio, RapidMiner
In addition to Tableau and Qlik Sense, there are other AI data visualization tools available in the market. To ensure that the chosen solution matches your business requirements, conduct a thorough needs analysis and tool evaluation before implementing.
Implementing a data visualization tool can be a valuable endeavor, but like any project, there are potential risks and costs that you should be aware of.
The initial investment can be substantial, encompassing not just the cost of the tools but potentially also hardware upgrades, additional software, and employee training. Successfully integrating AI tools with existing systems and their ability to scale with your business growth should be a critical deciding-factor.
Which tool do you use for your data visualization needs? Let us know here.
