AI in data analytics: An essential ingredient in your enterprise trans

Imagine this situation: Your organization is generating a huge amount of essential data from various touch points of the customers, but that data is sitting unused while competitors are leveraging those data insights to predict trends, get real-time insights, personalized customer experience, and more. Isn’t it a concerning situation?   

Here comes the Data analytics and AI in the picture, solving the data analytics challenges, streamlining the operations, and delivering insights faster. Agility is the cornerstone of today’s enterprises: faster response to market changes, personalized customers’ needs, and delivery of personalized messages.  According to a research, businesses using AI-driven data analytics experienced 30% increase in decision-making speed. 

Why AI in Data Analytics is a game-changer for your business  

With the integration of AI in the data analytics process, your enterprise can make a huge shift from guesswork-based decisions to data-driven (proactive and reactive) decision-making.  

There are enterprises using traditional data analysis to extract insights, but the real struggle lies in processing large volume of data and extracting real-time meaningful insights. Data analytics integrated with AI tools fill this gap and help you extract actionable insights from the data faster.  

Key Trends Driving AI in Data Analytics 

1. Enterprises need AI to manage the explosive growth of data. According to a Statista report, global data creation is expected to grow by more than 394 zettabytes by 2028.  

1. Forecasting is getting more accurate with Data Analytics and AI:  AI-driven predictive analytics is helping industries improve the accuracy of their forecasting compared to traditional analytics methods—Deloitte. 

1. Automated Decision-Making: We have noticed that enterprises implementing Data analytics and AI services experience faster decision-making in their processes. We have helped one of the leading pharmaceutical enterprises improve its pharmacovigilance with real-time insights.  

How Data Analytics and AI are impacting enterprises’ growth 

Saving time and cost Enhanced Data Preparation and Cleaning 

Most data scientists spend 60% of their time and efforts on data preparation and cleaning. This drains their energy and creativity, leading to costly and unproductive efforts. With the help of AI, enterprises can automate most of these repetitive and mundane tasks, reduce errors, and save time and money. AI integrated with data analytics enables data experts to focus their efforts on more strategic tasks. 

Advanced Predictive Analytics 

AI-driven data analytics solutions help industries anticipate customers’ behaviors, predict trends, operational issues, and more. Retail industry players like Amazon leverage AI in their data analytics process to predict inventory stocks, improve customer satisfaction, and reduce wastage.  

Real-Time Insights 

Traditional Data analytics methods struggle to analyze large volumes of data and produce real-time insights. AI and data analytics collectively bridge this gap, empowering enterprises with real-time insights. 

Interactive Dashboards  

Power BI and Tableau are some of the most commonly used AI tools that enable enterprises to visualize their insights more effectively. With interactive and intuitive dashboards of business insights, enterprises can simplify complex data into easy-to-understand patterns to make faster decisions. 

Personalized Customer Experiences 

By integrating AI into the data analytics process, enterprises can deliver personalized experiences to their target customers. Industries are using AI-powered data analytics solutions to personalize their marketing efforts and offer tailored solutions, such as Netflix, which offers personalized recommendations to users based on their viewing habits. 

 

How Data Analytics and AI Helping Industries 

Healthcare 

AI-powered predictive analytics help healthcare industry professionals analyze real-time data coming from ICU equipment and send alerts to healthcare professionals about early signs of patient deterioration.  

Finance 

Data analytics and AI help finance industry professionals, from risk assessment to detecting fraudulent activities and boosting finance forecasting.  

Retail and E-Commerce 

Retailers are leveraging real-time insights with an AI-powered data analytics process to improve their customers’ interactions with their brands by anticipating their buying behavior and patterns. This also helps them determine pricing strategies, predict demand, and more.   

Manufacturing 

Various manufacturing enterprises are leveraging AI-powered predictive maintenance to minimize production downtime and equipment failure. This leads to more productivity and cost savings.