In the digital era, data is not only important resource, but also is considered “new gold” of the business. However, to extraction of maximum value from data, businesses can't just stop at the gathering that need to use the tools to analyze modern data to process and transform data into valuable information. These tools not only support business capture trends, optimize performance, but also opens up opportunities for strategic decisions based on the platform accurate data.
This article Lac Viet Computing will introduce the details about the tools data analysisfrom basic concepts, the benefit highlights, to the list of common tools, as well as choosing appropriate tools for each type of business. If you are looking for solutions to improve processes, data analysis, enhance competitiveness, this is the article you can't ignore.
1. Tool analysis what is data?
Tools data analysis is the technology solutions designed to support business processing, analysis and visualization of data. These tools help to transform the raw data, complexity of the valuable information, support business decisions correct strategy quickly.
Specific:
- Data processing: Integrate, cleanse, standardize data from many different sources.
- Data analysis: Create reports, charts and predict the trend for businesses to understand more about the performance.
- Visualization: Display data through the dashboard easy to understand help the user does not need in-depth expertise can still capture quickly the information.
Important role:
Tools, data analysis plays a role as a bridge between data and business decisions. Some of the prominent role include:
- Optimize business performance: To help businesses detect the growth opportunities, optimize resources.
- Advanced financial capacity: Support financial analysis, accurate, given the reasonable forecast for the budget, cash flow.
- Improved customer experience: Analyze customer behavior to improve the marketing strategy, strengthen the satisfaction of customers.
2. The type of analytical tools common data
In the context of technology development, the tools, data analysis increasingly varied according to the purpose of use. Here are three types of main tools:
2.1. Tools to analyze business data (Business Intelligence – BI)
The BI tools focus on collecting, analyzing, and displaying data to support strategic decisions.
Characteristics:
- Easy to use with intuitive interface.
- Support integration of multiple data sources (CRM, ERP, accounting software).
- Create automatic reports, updated in real time.
For example:
- Microsoft Power BI: Create the dashboard dynamic analysis is effective for large organizations.
- Tableau: Strong in data visualizations with the chart type complex.
2.2. Tools, data analysis, financial accounting
Designed specifically to support finance department of accounting in the management of data related to the budget, revenue, expenses, cash flow.
Characteristics:
- Support detailed analysis of financial indicators such as profits, debts, cash flow.
- Forecast financial trends based on historical data.
- Provide high security features to protect sensitive information.
For example: Financial AI Agent of Vietnam: Integrated tools AI to analyze accounting and financial support, queries financial data in real time, forecast financial trends.
2.3. Tools, big data analytics (Big Data Analytics)
These tools focus on the processing of the data analytics giant, which is often used by businesses large scale or in the field of research.
Characteristics:
- Handle large data volumes with high speed.
- Integrated AI/Machine Learning to advanced analysis.
- Good scalable, consistent with the long-term project.
For example:
- Apache Hadoop: Handle large data dispersion, in accordance with the business in the field of research or technology.
- Google BigQuery: Focus on handling large data on the cloud platform to support the business, ecommerce, advertising.
Tools to analyze data not only support business process optimization, data management, but also help them to transform data into practical value. Choosing the right tool will depend on the specific objectives and the scale of each business.
3. The salient features of the tool data analysis
3.1. Integrated multi-source data
Tools data analytics allows businesses to integrate data from many different sources, including ERP systems, CRM software, accounting software, database internally. This feature helps the whole set of business data into a single platform to minimize the fragmentation of information, process optimization analysis.
Benefits:
- Data synchronization: Easily access data from different departments to ensure consistency integrity.
- Reducing processing time: Integrated automatic data save time entering data manually.
- Increase effective collaboration: The departments have access to the same data set, from which enhance coordination ability.
3.2. Real-time analysis
Khả năng phân tích thời gian thực cho phép doanh nghiệp truy cập xử lý dữ liệu ngay lập tức khi có thay đổi. Điều này đặc biệt quan trọng trong các ngành công nghiệp yêu cầu phản ứng nhanh, chẳng hạn như tài chính, sản xuất, hoặc thương mại điện tử.
Benefits:
- Feedback quickly: Leadership can be based on data update to take out the instant decision.
- Track KPI constant: Businesses can monitor the performance without waiting synthesis report.
- Detect troubleshooting: Support identification, timely issues, as sales decline, or the cost spike.
3.3. Trực quan hóa dữ liệu
Các công cụ phân tích dữ liệu hiện nay tập trung vào trực quan hóa dữ liệu giúp người dùng dễ dàng hiểu, phân tích thông tin thông qua các biểu đồ, bảng số liệu và dashboard.
Benefits:
- Display information visually: Complex data are expressed as diagrams, graphs help the user to easily recognize trends.
- Custom report: Users can design dashboard tailored to the individual needs of each of the departments.
- Enhance decision-making abilities: Data visualizations help leaders understand the overall picture. make decisions quickly.
3.4. Forecast analysis advanced
Integrated artificial intelligence (AI) and machine learning (Machine Learning) tool data analysis help businesses not only look back at past data but also predict trends in the detection of abnormalities in the future.
Benefits:
- Trend analysis: Help businesses predict customer demand, revenue, or expense in the future.
- Anomaly detection: SOMEONE help identify the index of unusual, such as financial fraud or error in supply chain.
- Optimization strategy: The analysis predicts allows businesses to adjust strategies to achieve goals more efficiently.
3.5. High data security
Dữ liệu doanh nghiệp luôn chứa đựng những thông tin nhạy cảm, vì vậy các công cụ phân tích dữ liệu cần đảm bảo mức độ bảo mật cao bao gồm mã hóa dữ liệu, phân quyền truy cập, và theo dõi hoạt động của người dùng.
Benefits:
- Prevent data leakage: Protect sensitive information such as financial information, customer.
- Management access: Only those who have the right to be allowed access to specific data.
- Regulatory compliance: Ensure business compliance with security standards like GDPR or ISO 27001.
The striking features such as integrated multi-source, real-time analysis, data visualizations, advanced analysis and high security have helped the tools, data analysis becomes indispensable solution in business activity. The effective use of this tool not only helps business process optimization, commissioning, but also create competitive advantages sustainable in the market.
4. Choosing tools, data analysis, fit
Selection tool suitable not only help businesses optimize workflow but also enhance the ability to make decisions based on accurate data. The review needs specific features, cost and the level of ease of use are the important factors to ensure the tool fully meet current requirements as well as supporting the long-term development of the business.
4.1. Determine the specific needs of the business
To select the analysis tool suitable data, the first step is most important is to clearly define the specific needs of the business.
- The types of data to analyze: Businesses need to analyze business data (sales revenue, profit, cost), or data, financial accounting (cash flow, debt, budget)? For example: A company e-commerce will need tools to help analyze customer behavior, while a manufacturing enterprise focused to analyze inventory and supply chain performance.
- Scale data, the target use: With business SME, tools for free or low cost, such as Google Data Studio may be the right choice. Large enterprises need tools capable of handling large data such as Apache Hadoop or Tableau to meet the requirements of speed, efficiency.
4.2. Features the ability to expand
An analytical tool well need to have the flexibility and scalability to meet the development of the business.
- Assess the ability to integrate with the current system: Tools should integrate smoothly with the existing software, such as ERP, CRM, accounting software. For example: Financial AI Agent of Vietnam has the ability to deeply integrated with the accounting system AccNet help enterprises easily deploy, manage financial data.
- The ability to expand as business grows: Tools to meet the demand growth in the scale of data and volume analysis. For example, Google BigQuery support extended automatically on the cloud platform, in accordance with the business processing big data in real time.
4.3. Cost and technical support
When choosing tools, cost and level of technical support from supplier, are important factors to consider.
- Compare the cost of deployment: Businesses need to compare the elements as free copyright, free to deploy, the other hidden costs. For example: the Tableau is the tool have a high cost, but bring great value on feature visualization, while Google Data Studio for free but in accordance with the small business.
- Service and technical support: Suppliers can provide 24/7 support no? Tools have to be updated periodically to feature enhancements, security't? For example: Financial AI Agent of Lac Viet provide support detailed technical consulting services customized for Vietnamese businesses.
4.4. Easy to use in accordance with the hr team
A tool for data analysis need to be friendly interface easy to use to all parts of business can apply without training too complicated.
- Reviews, interface documentation: The tool should have a simple interface, intuitive accompanied by the documents supporting details. For example, Microsoft Power BI, provides drag & drop interface friendly, documentation in full conformity with both users with no technical skills.
- Level easy-to-apply: Tools need to have automation features reduce dependence on our team of expert data analysis. For example: Financial AI Agent allows the user to perform the query data using natural language, help leadership easy to use without training deep.
5. The analytical tools common data for business
Tools such as Microsoft Power BI, Tableau, Google Data Studio, Financial AI Agent, Apache Hadoop bring the optimal solution in the data analysis. Depending on the needs and scale, businesses can choose the right tools to optimize the decision-making process, improve business performance, increase competitiveness on the market.
5.1. Financial AI Agent of Vietnam
Financial AI Agent is tools of financial analysis, accounting intelligence is developed by Lac Viet, integrate AI to assist enterprises in the query, data analysis, real-time financial.
Feature highlights:
- Financial analysis in-depth: Provide financial reports automatically as the balance sheet, cash flow, debts and profits.
- Support real-time query: Reply queries using natural language, such as “cash Flow available current is how much?” or “revenue of months ago?”.
- Trend forecasting: Use AI to predict the financial volatility based on historical data.
- Visualization report: Display data as a chart, easy to customize according to the needs of each department.
5.2. Microsoft Power BI
Microsoft Power BI is one of the tools, data analysis, today's most popular, featured with intuitive interface, the ability to deep integration with the Microsoft ecosystem, including Excel, Azure, Microsoft Teams.
Feature highlights:
- Dashboard activity: Create dashboard reports, intuitive, easy to customize according to needs.
- Support connecting multiple sources: Integrate data from SQL Server, Google Analytics, Salesforce and many other sources.
- Automation report: Update data automatically in real-time to help businesses always grasp the latest information.
5.3. Tableau
Tableau is an analytical tool data depth is known for its ability to visualise data to support diverse types of charts.
Feature highlights:
- Visualizing complex data: Create the graph, easy to understand even with big data complex.
- Advanced analysis: Integrated support AI, Machine Learning to predict trends and detect anomalies.
- Interoperability: Users can directly interact with the chart, customizable reports in real-time.
5.4. Google Data Studio
Google Data Studio is a free tool, easy to use, suitable for the small and medium enterprises. This tool is designed to support users to create reports, dashboard from many different data sources in the ecosystem, Google.
Feature highlights:
- Free: Does not require cost copyrighted or free to use.
- Easy integration: Fast connection with Google Analytics, Google Ads, Google Sheets, and many other platforms.
- Custom report: Support drag-and-drop the ingredients to create the report as you want.
5.5. Apache Hadoop
Apache Hadoop is the open source tool specialized in processing big data analytics. This is the optimal choice for the large-scale enterprise or the organization to handle huge amount of data from multiple sources.
Feature highlights:
- Handling big data: Support analysis of massive data sets that traditional tools can't handle.
- Integrated diversity: Connected to many systems, data storage and analysis tools other.
- Analysis of dispersion: Data is divided into small handle at the same time on multiple servers, increase the processor speed.
6. Trends app analysis tool data in the enterprise
6.1. Apps, AI and Machine Learning
The combination of artificial intelligence (AI) and machine learning (Machine Learning) in the tools data analysis is becoming an inevitable trend. These tools not only support data processing but also automate the process of analysis, thereby creating the forecast, hint, strategy, breakthrough.
Benefits highlights:
- In-depth analysis: AI can handle large volumes of data to detect patterns, trends that people hardly recognize.
- Automatic forecast: Machine learning allows businesses to predict the future outcomes based on historical data, which helps to plan more accurate.
- Personalization solutions: AI based on the individual characteristics of each enterprise or field of business.
For example: Insurance companies use AI to analyze customer profiles, detection of risk factors and proposed insurance products fit. Thus, they have to increase the rate of sales up 20%, reduce the rate of payment risk.
6.2. Combined with big data (Big Data)
Big data (Big Data) played a key role in promoting the efficiency of the analytics data. Businesses increasingly collect blocks a huge amount of data from many different sources such as website, social networks, IoT system, online trading. Tools data analysis now allow for processing and extraction of value from data blocks this.
Benefits highlights:
- A quick analysis of the effect: Handle large volume of data to generate reports, insight value.
- Integrated multi-source: Data from many different systems are combined to create a comprehensive picture of business operations.
- Decision support: Discover the factors that affect performance, detect new opportunities from data.
6.3. Integrated in the strategic transformation of
Convert numbers are is a top priority of many businesses to enhance competitiveness. In this strategy, the tools, data analysis plays an important role to help businesses transition from traditional management to manage based on data.
Benefits highlights:
- Accelerates the decision-making process: The data is analyzed, provided when in need of help leaders take timely decisions more accurate.
- Performance optimization: These tools help improve operational efficiency by automation of the analysis report.
- Ensure transparency: Providing clear information reliable help business activity monitoring, risk management, more effective..
In the context of data is increasingly becoming the determining factor of the success of the business, the use of tools data analysis no longer is the option that has become necessities. From the support correct decisions, optimize business operations to forecast future trends, analysis tools role as “the digital brain” to help businesses lead in the market competition fierce.
Let's start using the right tool as Microsoft Power BI, Tableauor Financial AI Agent of Vietnamstep by step building strategy, data analysis efficiency. Invest in tools data analysis the key is investing in the success and sustainability of business in the future. Take action today to turn data into competitive advantage superior!
