Applying AI to analyze data and 7 popular AI data analytics tools

In the digital era, data is not just resources, but also become strategic assets to help businesses improve competitiveness. However, the processing, analysis, block a huge amount of data is a challenge, especially when using traditional methods. This is the time AI data analysis become groundbreaking solution brings automation capabilities, increase speed, improve accuracy in the extraction of value from data.

This article Lac Viet Computing will provide comprehensive perspective on AI data analysis: from exceptional benefits, common tools to the implementation steps in detail. If you are looking for a solution to optimize business operations and make strategic decisions based on data, this is exactly the content you need.

1. AI analysis what is data?

1.1. Definitions of AI, data analysis

AI data analysis (Artificial Intelligence in Data Analytics) is the application of artificial intelligence (AI) to automate the process of collecting, processing, analyzing and visualization of data. Instead of having to rely on the method or the traditional time-consuming, easy to flaws, AI brings the optimal speed, accuracy and ability to handle the volume of data is huge.

AI data analytics help businesses transform raw data into useful information and insightful support strategic decisions, enhance business performance. The AI technologies such as machine learning (Machine Learning), deep learning (Deep Learning), language processing nature (Natural Language Processing) are playing an important role in the analysis, data mining.

1.2 the difference between The analysis of traditional data and AI data analysis

2. The numbers say about trending apps AI to analyze data in business

The numbers say:

• 85% of businesses surveyed in the report of McKinsey agree that AI data analytics has helped them optimize costs, revenue growth.
• Follow PwCapplying AI in data analysis can contribute more to 15.7 trillion to global GDP by 2030.

According to the Gartner report (2023): AI helps to increase efficiency in decision-making up 30%

Report of Gartner (2023) have shown that businesses apply AI data analytics into the decision-making process strategy has achieved the level of increased efficiency up to 30%. This has been possible thanks to the ability of AI in:

• Fast processing big data (Big Data): AI automatically analyze huge data from various sources such as CRM, ERP, social networking, sensors, IoT in a short time.
• To detect patterns and trends hidden: AI help businesses identify trends, potential approach that traditional analysis often overlook.
• Correct predictions: Based on historical data, current, AI support given reliable predictions about customer behavior, market volatility, performance business.

According to research from McKinsey (2023): AI shorten the analysis time down to 20% compared with traditional way

A study from McKinsey emphasize that the application of AI in data analysis not only increases accuracy but also shorten the processing time significantly. This is especially important in industries that require speed, such as e-commerce, finance, production.

• Process automation: AI automation from the stage of data collection to processing, analysis, removal of the capital take much time.
• Real-time analysis: AI can handle and analyze real-time data, to help businesses make decisions quickly to capitalize on market opportunities.
• Increase team productivity: ANYONE help reduce the load for the staff to analyze data, allowing them to focus on the interpretation, implementation, strategy, business.

3. Benefits of AI data analytics for business

3.1. Automate the entire process of data analysis

AI, data analysis, automation of important from collecting, cleaning, analyzing and reporting data. Thanks to that, the previous work requires weekly, even monthly, now it just needs few hours to complete.

• Collect data: AI direct integration with CRM systems, ERP, the external data source, such as social networks, sensors, IoT.
• Data cleaning: AI automatically detects error handling in data such as duplicate, missing or wrong format.
• Data analysis: AI apply algorithm machine learning to detect patterns, trends that people hardly recognize.

AI remove the errors caused by human factors, ensuring accuracy and consistency in data analysis. This is especially important to industries such as finance, medical, manufacturing, where decisions based on data that needs high accuracy.

3.2. Strategic decisions based on data

Analysis of the factors that impact business performance

AI data analysis to support business clearly define the factors that directly affect revenue, expenses, profit. By comparing script different business AI help businesses choose the most effective strategy.

Predict business trends, identify opportunities

AI uses historical data to predict market trends, customer behavior and growth opportunities. This helps businesses to quickly seize the opportunity before the opponent.

3.3. Personalize customer experience

Behavior analysis customer preferences: AI analyze data collected from the touched point customers such as website, mobile application, social network, to understand your interests, shopping habits. This information allows businesses to create marketing campaigns that are personalized for each customer.

Increase the rate of customer retention, improving satisfaction: Thanks to personalize content, products, AI enhances the user experience, retain customers longer.

Practical example: Netflix uses AI to analyze historical movies of each user, from which hint at the film, the series match. This has helped Netflix rate increase customer retention by 25% in just 1 year.

3.4. Optimized operation process

Discovered settle the score congestion in the process: AI analysis of data from the production process, supply chain to detect the point of obstruction or waste. This helps businesses optimize the timing of operating costs.

Allocate resources more effectively: AI business support allocation of resources such as personnel, materials, finance, based on real data, from which optimal performance.

Practical example: Amazon use AI in warehouse management helps track forecast product demand in real time. Thanks to that, Amazon discount 15% cost of storage, a 20% increase effective delivery.

4. The practical application of AI to analyze data in business

4.1. Revenue forecast cost

AI data analysis help businesses predict turnover costs with higher accuracy by analyzing factors such as:

• Sales history: Revenue data from the previous year are used to identify patterns, trends.
• The impact of external factors: AI integrated economic data, market trends, changing customer needs to put in place a comprehensive forecast.

Main benefits:

• Reduce financial risk thanks to forecast international.
• Support budgeting efficiency, optimize resources.

4.2. Analysis to understand market context, and performance opponent

AI collects data analysis from various sources, including financial reports, industry news, social network data, to help businesses:

• Evaluate its position in the market.
• Compare performance with the main rivals.
• Spot opportunities and potential risks.

Practical example: A technology company using AI to track the marketing strategy of opponents on social networks. Thanks to the analysis, keywords, ad content, they adjust their strategies, increase effective advertising campaign up 30%.

Main benefits:

• Building competitive strategy more effective.
• React quickly to the changes in the market.

4.3. Detection of unusual transactions

AI, data analysis, financial transactions to identify unusual patterns from which to detect, prevent fraud.

• Learn from historical data: AI automatically learn from past transactions to detect invalid activity.
• Real-time analysis: Detect suspicious transactions when they occur..

Main benefits:

• Improve transparency and financial security.
• Protect corporate reputation ahead of the legal risks.

4.4. Optimal personalization marketing strategy

AI analyze customer data such as purchase history, browsing behavior, feedback from the marketing channels to create the advertising campaign was personalization.

• Increase conversion rates: Aim the right target customers with tailored content.
• Cost optimization advertising: Focus resources on the customer group with high potential.

Main benefits:

• Increased satisfaction of customers.
• Improve effective ROI from the marketing campaigns.

4.5. Supply chain management

Predict product demand: AI support businesses predict product demand based on historical data, market trends, optimized production plans, reduce operating costs.

Optimize inventory and reduce the delivery time

• AI analysis of data from inventory to determine inventory levels optimal.
• Optimized route shipping to reduce the cost of delivery, waiting time of customers.

Main benefits:

• Increase supply chain efficiency.
• Ensure goods are always ready to meet customer needs.

5. The AI engine to analyze data downloads

5.1. Google Cloud AI: Leading in technology, big data analytics

Google Cloud AI provides a variety of powerful tools to support your business harness the value from the data:

• AutoML: This tool helps business automate the process of building machine learning models that don't need technical team in-depth. From image analysis, text to predictions based on data, AutoML solutions provide comprehensive, user-friendly.
• BigQuery WHO: Combine the ability to handle big data (Big Data) with analysis artificial intelligence. BigQuery AI allows businesses to perform complex queries, predict trends, build the real time report.

5.2. AWS AI: tools comprehensive optimization for business

Amazon Web Services (AWS) to provide the services, advanced AI, which highlights are:

• Amazon SageMaker: Support building, training and deployment of machine learning models. SageMaker helps business process optimization, data analysis, with fast speed and reasonable cost.
• Personalize: A special tool for business, ecommerce, help to create the personalized product recommendations based on user behavior.

5.3. Microsoft Azure AI deep integration with Microsoft ecosystem

Microsoft Azure AI is designed to integrate smoothly with familiar tools such as Microsoft Office, Dynamics 365, Power BI, bringing seamless experience in analyzing data.

• Azure Machine Learning: Provide the machine learning models strongly support the prediction, classification and data optimization.
• Cognitive Services: Integrate the possibility of AI such as image recognition, text analysis, identifying emotions into the app business.

5.4. Tableau integrates AI data visualizations smart

Tableau, one of the platform data visualizations top has integrated artificial intelligence to improve the ability to analyze data.

• Ask Data: Lets users ask questions in natural language to get answers immediately as a chart or visual reports.
• Explain Data: Features AI this automatically search for the underlying factors in the data to explain the variation or anomalies.

5.5. Advanced analysis with IBM Watson

IBM Watson is an advanced AI system support analysis data at the level of in-depth:

• Watson Discovery: Search analysis information from the data source, not the structure, such as email, documents, news.
• Watson Studio: Provides development environment to build, deploy, the pattern AI, especially useful for large business with the needs complex analysis.

Practical application: A major pharmaceutical companies use IBM Watson to analyze millions of clinical reports, helping them detect correlations between drugs and diseases more quickly, shorten the time to research new drugs.

5.6. Vietnam Financial AI Agent: tools of financial analysis AI first in Vietnam

Financial AI Agent is the solution advanced technology of hanoi development, designed specifically to support business analysis financial data in an efficient way comprehensive. Integrate the power of Business Intelligence (BI), Generative AI, Natural Language Generation (NLG)this tool works as a financial expert business support 24/7.

The salient features of the Financial AI Agent:

Automatically create financial statements in detail and visually 

Financial AI Agent has the ability to automate the entire process of creating a report with the type of financial report as common as:

• Business report.
• Balance sheet accounting.
• Reported cash flow.
• Report receivables/payables.
• Inventory report.
• Reported revenue and profit.

All are expressed in the form of visual charts help business leaders understand easily evaluate the financial situation.

In-depth analysis “health” business finance:

• Integrated expert financial advisors AI support in-depth analysis on financial indicators such as profit, cash flow ratio, debt/capital, trend fluctuations.
• Errors are detected, automatically checks for problems in the financial data.
• Risk advisory, forecast financial trends based on historical data.

Data updates in real-time:

• Financial AI Agent direct link with the system software, financial accounting provides data always updated in real-time.
• System, ensure that the business always capture financial situation current to a timely decision.

Custom and flexible reporting:

• Businesses can customize the analysis criteria using a drag-and-drop simple.
• Reports can be rendered under various formats, meet all your needs presentation and analysis of data.

24/7 support on all devices: Financial AI Agent works smooth on all devices, allows the leader and the accounting easy access, work anytime, anywhere.

Solve the “anxieties” of the business:

For the accounting department:

• Reduce workload and handle end report states such as summarizing, tax settlement, budgeting.
• Automatically generate reports, cash flow, debt collection, financial statements, details in short time.

For leaders:

• Provide financial picture comprehensive, real-time, to help a decision quickly.
• Support troubleshooting instant on the financial indicators, providing forecast financial strategy without waiting from the related department.
• Warning of financial risks, suggesting solutions to optimize resources.

Financial AI Agent of Vietnam is not only a tool of financial analysis that is also a smart assistant, help businesses understand management “health” finance in a comprehensive manner. With the possibility of automation, in-depth analysis, update real-time, this is the ideal solution to the Vietnam business process optimization, financial management, strengthen competitive advantage in the market.

5.7 Alteryx: tools, data analysis, comprehensive with integrated AI

Alteryx is a cross-platform data analysis powerful tool designed to automate the process of data processing, advanced analysis information visualization. Highlights of Alteryx is integrated the possibility of artificial intelligence, help businesses handle large amounts of data, and generate reports detailed analysis that does not require programming skills high.

Automation, data analysis, comprehensive: 

• Alteryx lets connect, integrate data from various sources like ERP, CRM, database (Big Data) in real time. 
• Automatic system cleaning, processing, standardized data that help save time, quality of analysis.

Advanced analytics with AI and machine learning:

• Integrated machine learning algorithms to predict trends, data classification, detection of complex patterns.
• Alteryx Intelligence Suite allows users to build models AI without writing code.

The ability to visualise data powerful:

• The analysis results is shown through charts, dashboard interactive help users to easily understand to make a decision quickly.
• Connect with intuitive tools popular culture such as Tableau and Power BI to expand the ability to present data.

Support analysis of cooperation: This platform allows the team to work together in the same analysis process, increasing transparency and efficiency in project management data.

6. The step implementation, data analysis, AI in business

The steps to deploy AI data analysis should be done carefully, from identifying the target clearly, data preparation, to select tools, and continuously optimize the system. When done properly, AI not only help businesses improve efficiency, data analysis, but also opens the opportunity for sustainable growth in the future.

Step 1. Define your business goals clearly

Why need to define your business goals?
Before deploying AI, data analysis, business needs clear goals to achieve. This step is important to help guide strategy, ensure that the application of AI will properly solve the real problems that businesses are facing.

The specific objectives may include:

• Increase revenue: Use AI to predict the buying behavior of customers, optimize marketing campaigns.
• Cost optimization: Data analysis to detect, reduce the waste in the process of operation.
• Improved customer experience: Personalization of products or services based on behavioral data.
• Trend forecasting: Use AI to predict market fluctuations, prepare coping strategies.

Step 2. Collect and clean data

AI only works effectively when the input data accurately and fully. So, collect and clean data is an indispensable step to ensure the accuracy and efficiency of the analysis model.

Steps taken:

• Collect data: Connect data from multiple sources: CRM, ERP, social networking, sensors, IoT, financial reports. Ensure data covers entire aspects of business that business want to analyze.
• Data cleaning: Remove duplicate data, omissions, or inaccuracies. Standardized data formats for easy integration with AI engine.

Tool support:

• Trifacta, OpenRefine: cleaning tools, standardized data automatically.
• Alteryx: Integrated steps collected, cleaned data in a single platform.

Step 3. Select tools and the right technology

Needs assessment, the ability of business: Every business has scale peculiarities, so need to choose the tool AI analyze data in accordance with specific needs.

Criteria for tool selection:

• Features: Tool has the ability to automate, support advanced analysis, integrated with the existing system.
• Scalability: Tools need to be able to handle the volume of big data, expand as business grows.
• Easy to use: User-friendly interface, suitable for both employees do not specialize in technology.

A number of popular tools:

• Google Cloud AI: Support big data analysis and model building to predict strong.
• Financial AI Agent of Vietnam: Integrated ability to analyze financial depth, to meet the needs of businesses in Vietnam.
• Alteryx: Tools, process automation, data analysis, comprehensive.

Step 4. Coaching team and in cooperation with experts

Why the need for training and cooperation?
Our team of personnel are important factors determining the success of the deployment of AI. Businesses need to ensure that employees understand, competently use tools AI to optimize benefits.

Steps taken:

• Internal training: Organization basic course about AI and data analysis for employees. Intensive training for team analysis, data management.
• Cooperation with experts: Invite experts or partners solution providers AI support deployment of system optimization.

Practical example: An investment bank has organized training course on AI for finance, helping them master the use of the model to predict cash flow. The result is the ability to manage the financial risk of the bank is significantly improved.

Step 5. Reviews and continuous optimization

The importance of the assessment: The deployment of AI is not a fixed course, which should be monitoring, continuous optimization to ensure the long-lasting effect.

The steps for assessment and optimization:

• Tracking the performance: Use the KPI as the accuracy of predictions, the processing time, WHIP to assess the effectiveness of AI.
• Collect feedback: Listen to comments from departments and users to improve the system.
• Model updates: Retrain machine learning models based on new data. Integrate the technology and algorithms, the most advanced AI.

AI data analysis not merely a tool, but also is the key to help enterprises transition from the rely on feelings to make decisions based on actual data. With the possibility of automation, in-depth analysis, providing a reliable prediction, AI has become a core foundation to help businesses enhance performance, optimize costs and maintain competitive advantage.

Though the process of development AI may require thorough preparation, but the benefits that it brings completely worth the effort and investment. Please begin your journey to harness the potential of AI today to take your business further in the digital era!