Today’s business landscape is driven more than ever by data-based decision-making, spanning all industries and (specialized) departments. Companies from all sectors are increasingly aiming to generate intelligent insights from their data to help them make decisions. As a result, analyzed data is taking an active role in shaping decision processes and plays an enormous role in continuously changing and optimizing processes. This is exactly where business data analytics comes in: a systematic approach to data-driven process optimization. But what does this actually mean and what benefits does it offer? Here are the key facts about business data analytics at a glance!
What does Business Data Analytics Mean?
Business data analytics combines two methods: business analysis and data analytics. Business analysis focuses on thoroughly examining existing business processes, whereas data analytics transforms company data collected into meaningful, value-generating information. Large volumes of raw data can be collected, analyzed and interpreted. It forms a solid foundation for informed business decisions. By combining both methods, business data analytics takes into account not only data, but also processes, platforms and IT infrastructure. This transforms a traditional algorithm-based business model step-by-step into a data-driven organization. Business data analytics enables you to analyze data and use it strategically for comprehensive and sustainable optimization of your business processes.
Advantages of Business Data Analytics
Any business areas that rely on extensive data and information for decision-making can benefit from this approach. Typical areas of application include choosing suppliers, planning production workflows and classic back-office processes. Discover how business data analytics can create value for you and your organization:
- Time Savings & Traceability
Data-based decisions dramatically reduce the effort required to identify problems. Data analysis and profit forecasts lead to faster turnaround times. All results remain traceable, reproducible and reusable for future decisions.
- Improved Decision-Making
Advanced predictive analytics algorithms and machine learning techniques use both old and current data with techniques such as advanced statistics and machine learning to model future events accurately and cost-efficiently. This enables better and more realistic foresight about future events and measures can be taken within good time.
- Real-Time & Historical Insights into Business Processes
Decision-makers can view real-time data and forecasts simultaneously to make decisions which promote sustainable growth and lead to success. Clear recommendations for action simplify the decision-making process and some actions can even be automated.
- Opportunities for Change
Prescriptive analyses models give recommendations for optimal business decisions. Artificial intelligence enhances business intelligence by simulating scenarios. This helps avoid failures and maximize successes.
Business data analytics enables data to be used for informed decision-making. Data visualization and insight delivery accelerate decision processes and give companies a competitive edge. They form the foundation for data-driven decisions and help organizations identify growth opportunities, reduce risks and continuously improve processes, products and services. Business data analytics is the method that unlocks intelligent insights and enables data-driven decisions to be made within your company.
The second part of our blog series will show you how to make your own processes data-driven and what to look out for. Check it out!
Not had enough yet? Do you want to check out business data analytics in action using real data?
Have you already got a few first ideas about how you want to use business data analytics? Why not have a non-binding chat to our data experts and find out how we can help you with your business data analytics project.
