Bringing AI in Business Data Analysis

Bringing AI in Business Data Analysis

Thursday 27 June, 2024

In today's world, making decisions based on data is more important than ever for all areas of a business. Companies are flooded with a lot of data from different places like their systems, ERP, CRM, marketing platforms, and social media. This data is not just useful; it's essential for businesses. Using this data effectively is a major goal for leaders. But how can businesses use their data to help reach their strategic goals? Many are finding that the solution is in combining Business Data Analytics and Artificial Intelligence (AI).

BI Tools: Revealing Information from Past Data

Data Analytics tools help gather, protect, sort, manage, and study data. They show data in easy-to-understand dashboards. These tools help users understand how their business is doing, supporting decisions based on data throughout the company.

Data Analytics tools use set queries, actions, calculations, and analytics to look at and present company-wide information. They use methods like data mining, cleaning data, Extract, Transform, and Load (ETL) processes, and showing data visually. These tools help users watch key performance indicators (KPIs), see company trends, and understand details. BI tools organize, study, and show data in user-friendly ways through data visualization reporting tools, giving fast access to important business information.

Use Cases for Analyzing Business Data: Understanding Past Events

Data Analytics tools are great for finding out "What happened?" and "Why did it happen?" For example, they help marketers keep an eye on campaign results in real-time and see how well different marketing campaigns are doing, which can help plan future campaigns. Sales managers can use data analytics to keep track of sales goals, see how well sales representatives are doing, and monitor key sales numbers. Operations teams can use data analytics to make supply chain processes better and ensure systems are running efficiently.

But, Data Analytics tools work best when used together with predictive and prescriptive analytics or AI.

AI Tools: Leading the Way in Advanced Analytics

AI, short for Artificial Intelligence, is changing the way we analyze data. It lets machines learn from past experiences, adjust to new situations, and do jobs like a human. AI includes different tech like machine learning, deep learning, natural language processing, and Large Language Models (LLMs). It looks at big amounts of data, finding patterns that normal tools might miss. Insights from AI make automation easier, improve customer experiences, make operations better, and find new chances for businesses to grow.

AI Applications: Forecasting and Enhancing

AI is good because it can learn from data and improve itself. It doesn't need much help from humans to adjust to changes. AI can guess what customers will do, suggest products, make processes faster, and make systems better, which can increase profits. It can figure out buying habits, group customers for specific marketing, and help keep customers longer.

Classification models help understand customer purchasing habits, while unsupervised learning models help group customers and make suggestions. For marketing teams, AI tools provide helpful information about campaign results, which helps improve strategies. In manufacturing, AI helps predict when maintenance is needed, preventing machine breakdowns and making operations more efficient.

Data Analytics and AI Tools: Making Them Easier to Use

Data Analytics and AI tools are different but work well together. Data Analysis is used to describe data, while AI is great for predicting and prescribing solutions. Data Analytics tools help sort, analyze, and picture structured and semi-structured data. On the other hand, AI is crucial for dealing with unstructured or large data from places like social media.

Bringing AI in Business Data Analysis

The use of AI in data analytics tools has changed how we do analytics. These tools now use AI, machine learning, and deep learning to do more. They can predict outcomes and suggest actions, answering questions like "What will happen?" and "What should we do about it?" This combination lets organizations use data in new and powerful ways.

AI helps businesses work better in many ways, like managing work and setting prices. For example, AI can set prices for things that don't last long, like plane seats or hotel rooms. It considers things like supply, demand, time of year, and weather. This helps businesses make more money, often making up for what they spent to get AI and data tools.

The Development of Analytics: Merging Data Analytics and AI

AI and Data Analytics tools are becoming more connected, which we can see in how analytics platforms are changing. Today, Business Intelligence (BI) tools are smoothly integrating Artificial Intelligence (AI). For instance, Qlik's AutoML feature improves its software with predictions and easy-to-understand AI. AutoML makes creating models easier, offering predictions and hypothetical situations without needing to code. Other BI companies are doing the same, adding AI features to their tools to keep up with the competition.

Unlocking Data's Power

Data Analytics and AI tools together help businesses use data in new ways. Data Analytics tools tell us about past data, while AI tools predict the future and suggest actions. This mix boosts profits and sets up businesses for success in a world that relies more and more on data.

As the AI and Data Analytics fields merge, software companies are working fast to create advanced, easy-to-use tools. These tools help businesses make decisions based on data, which can lead to growth. The combination of data visualization and Generative AI makes it easier to create visuals and reports for customers. This powerful combination is leading us into a new stage of data analytics.


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