Artificial intelligence (AI) is no longer a nice-to-have; it is a must-have for businesses. While data holds the key to informed decision-making, AI can help you quickly unlock hidden insights from the data, irrespective of the size and shape of the data.
While AI has a lot to offer, enterprises often lack clarity on why, how, and where to use AI in their business. Here in this blog post, we will decode the potential of AI in data visualization and detail some of the game-changing benefits already available for enterprise disposal.
Before we dive deeper, here is the basic understanding of data visualization in business.
What is data visualization?
Data visualization is the art of giving a graphical representation of the narrative to your data details. It assists users in interacting with the data and understanding it effectively. The main goal of data visualization is to provide insights and identify patterns easily to record present reality and future predictions.
Common Challenges in Data Visualization
While existing data visualization tools often have their advantages, enterprises still struggle to keep pace with the ever-growing data demands. Below, we will discuss some challenges that AI can solve effectively.
Interpreting complex data
Who does not feel daunted by complex data? The data we have today is often complex and large scale making it difficult to interpret manually. But AI is here with us for rescue!
Data integrity and quality
Improper data accuracy and reliability might create ambiguity in creating meaningful visualizations making it challenging for generating insights.
IT dependency
Data-driven decision-making relies heavily on IT teams, as they are crucial for managing, analyzing, and securing data. However, not every business can afford an in-house or outsourced IT team.
Customized dashboards
In decision-making, there is no one-size-fits-all dashboard that can serve everyone. It is a challenge to constantly amend the required variable from source data and add different dimensions on the fly to arrive at key insights.
Timely reports
Making today’s decision based on yesterday’s data can often lead to unworthy outcomes. Traditional data visualization practices struggle to cater to time-critical data needs.
What you can do with AI-powered Data Visualization
With AI making inroads across every corner of business functions, data visualization is no exception. AI makes it simple to capture trends, analyze patterns, and predict anomalies within the data. Additionally, it also gives an additional arm for employees and business owners to present their data for decision-making. It makes quite an effortless walk for business users without worrying about technical pathways.
AI algorithms can analyze large data sets, identify anomalies and hidden patterns, and deliver real-time and predict analytics. AI acts as a helping hand in creating dashboards using natural language querying and can also turn raw data into visuals or a complete dashboard.
Since we are a Microsoft Solutions Partner, we have decoded this from the Power BI perspective.
AI-powered visuals
- Identify your key influencers impacting business. All that is required is to select the measure, and you will know the key influencer. For example, if you are unaware of one factor impacting your customer success, try adding one or more fields to your visuals to arrive at the list of factors influencing your metrics. Furthermore, businesses can perform what-if analyses and filter them to conclude the pattern and plan action.
- Features like decomposition trees can help you drill down on which product has performed well and contributed a significant percentage to your overall sales.
- Q&A visuals allow business users to query natural language with little technical expertise. Thus, a sales head can quickly calculate YoY sales growth with little technical know-how. A sales head can arrive at YoY sales growth in an instant. Its natural language expressions like filters, calculations, etc., make it even more convenient for the enterprise class. Above all the probable question suggestions based on the queried is the icing on the cake.
- Smart narrative visuals facilitate the blend of data insights and a compelling story to the audience. It adds details like text summaries to make it more detailed and disseminate meaningful data stories to decision-makers.
AutoML in Power BI
- Automated machine learning for dataflows helps analysts create, train, and invoke machine learning models for business needs. No Azure subscription is required for AutoML. Select your historical data and the known outcomes of the past to predict your future using binary prediction aspects. Decode the predictive signals to prepare your business for the future. Additionally, the semantic model classification into multiple groups helps the business with the probability of the possible outcome prediction.
- Regression models help businesses predict the likelihood of payment against an invoice or an LTV of an account or the probable sales deal revenue. The Explanation, and Explanation Index in the outcome helps a user understand the reasoning behind the result generated, bringing the best of humans and AI.
Source:Microsoft
Copilot in Power BI
Copilot brings a new dimension to data analysis, making it faster, easier, and more intuitive. Copilot is a next generation AI assistant that can turn complex tasks into compelling narratives necessary for decision making. Businesses can use Copilot in Power BI to analyze data, create reports, generate graphs and charts and access insights instantly.
You can ask Copilot to generate visuals or reports and insights automatically by analyzing the data and inputs. It integrates team members’ feedback into the reports ensuring that your visualization meets the stakeholder needs. You can interact with your data and dig deeper simply by asking questions in your natural language, be it English, Spanish, or any other, and Copilot will provide you the most accurate, relevant answers. Copilot also helps you tap into Power BI’s advanced analytics capabilities to generate predictive analytics.
Want to learn how to leverage AI for your unique business needs?
Cognitive Services in Power Query
- The language detection capabilities use text analytics to understand the user input and support up to 120 languages.
- Extracts key phrases and evaluates the sentiment scores in binary.
- It uses computer vision API to identify the object in the image used as an input for cognitive services.
Benefits of Using AI-powered Data Visualization
Data is the new oil for business enterprises. Every decision made generates data and information that is stored for understanding user behavior. But amidst this massive amount of information, how do we refine the actual data and make sense of it? Here is what data visualization tools come into the picture! Data visualization acts as a treasure map that helps to navigate the data landscape revealing hidden insights for smart decision making. Below, we have listed some of the benefits of using AI-powered data visualization.
Deep data analysis
Raw data is equal to an unpolished gem which means it has potential but lacks the lustre that needs shine. With the help of AI and its powerful algorithms, you can transform the raw data into valuable insights. It can uncover correlations, detect patterns, and predict trends that have eluded human analytics.
Interactive visuals
Forget static charts and graphs! Data visualization infused with AI can give life to your data creating interactive visualizations. They also make data exploration a fun adventure, sparkling with some creativity and encouraging problem-solving techniques.
Personalized recommendations
You might have experienced eerily accurate product recommendations from online stores several times. This is how artificial intelligence in data visualization works! It can personalize recommendations by understanding your behavior and preferences and make the user experience delightful and smoother. From giving suggestions for shopping to showcasing personalized content, AI empowers everything to the exact needs.
AI Use Cases in Data Visualization
Below are some of the use cases for AI in data visualization across several industries:
Finance: AI is used in data visualization for automating visuals to detect fraud, forecasting, and investment optimization.
E-commerce: AI is used in E-commerce for recommending products to the customer based on the predictive analysis of the user behavior.
Marketing: AI is used in marketing to generate visuals for social media analytics helpful for target advertising.
Sports: It is used in sports to showcase player and team performance using augmented visuals.
Healthcare: it is used in healthcare for clinical decision support systems using interactive data visuals.
Future of AI with Data Visualization
AI is into everything! This crystal ball in data visualization is set to bring some interesting data narratives to business users.
Imagine a world with AI that can automate complex data into visuals in real-time and a future where you communicate with the data through conversational interfaces. Sounds exciting right!? Well, we are closer than we think. With AI in data visualization, you can create dynamic dashboards personalized to the user, predict the future with better accuracy, and plan your future precisely.
By 2025, nearly 30% of big businesses and corporations were predicted to employ AI for predictive analytics to boost their sales key performance indicators and understanding. Businesses utilizing AI for data visualization will gain a competitive edge over those not fully adopting the technology.
Scalable cloud platforms will make AI accessible to all sizes of enterprises. With the right strategy and plan, businesses discover new insights crucial for growth. Enterprises need to start experimenting with the capabilities of AI for data visualization to reap its benefits.
If you are looking for a partner who can get you started with AI in Power BI, or data visualization services, we are a click away.
