{"id":112151,"date":"2022-09-16T11:00:00","date_gmt":"2022-09-16T11:00:00","guid":{"rendered":"https:\/\/dataunit.nadlotest.ch\/?p=112151"},"modified":"2026-07-30T11:36:41","modified_gmt":"2026-07-30T11:36:41","slug":"what-is-business-analytics-and-what-types-are-there","status":"publish","type":"post","link":"https:\/\/dataunit.nadlotest.ch\/en\/2022\/09\/16\/what-is-business-analytics-and-what-types-are-there\/","title":{"rendered":"What is Business Analytics and what types are there?"},"content":{"rendered":"\n

If the coronavirus pandemic has taught us anything, it’s that those who make quick decisions can survive in adverse situations. Business analytics deals with collecting, analyzing, interpreting, and presenting a company’s data in a way that enables better decisions to be made.<\/p>\n\n\n\n

What are business analytics?<\/h2>\n\n\n\n

Business analytics, also known as corporate analysis, refers to “the use of mathematics and statistics to interpret data in a way that enables better business decisions to be made.”<\/p>\n\n\n\n

Advantages of business analysis<\/h2>\n\n\n\n

The advantages are far-reaching, but the following are particularly noteworthy:<\/p>\n\n\n\n

1. Data-driven decision-making<\/h3>\n\n\n\n

Furthermore, data can be used in businesses to make informed decisions without relying on impressions or hunches. Below, we’ll show you how to use predictive analytics to visualize potential business scenarios, ensuring you have all the necessary data at your fingertips when making decisions.<\/p>\n\n\n\n

2. Faster operations<\/h3>\n\n\n\n

Bottlenecks cause processes to stall. Data analysis or business analytics can help reduce or even eliminate these bottlenecks and accelerate processes, such as inventory forecasting during peak sales periods and finding suppliers to strengthen the supply chain.<\/p>\n\n\n\n

3. Better customer experience<\/h3>\n\n\n\n

Companies have an enormous capacity for collecting data. Every transaction or contact with a customer leaves a trace that can be used to get to know the customer better, both on the company’s own channels (such as the website) and on social networks or in email correspondence.<\/p>\n\n\n\n

By analyzing this data, fairly accurate customer profiles can be created, which in turn can personalize the experience and strengthen customer loyalty.<\/p>\n\n\n\n

4. Improve security<\/h3>\n\n\n\n

The data security of all companies is exposed to threats. It is a fact that voluntary or involuntary data breaches cost Swiss companies a considerable sum of money every year.<\/p>\n\n\n\n

Business analytics can help you identify these vulnerabilities early on or analyze the causes and origins of data breaches that have already occurred, so that measures can be taken to prevent such incidents from happening again.<\/p>\n\n\n\n

5. Minimal risk, maximum profitability<\/h3>\n\n\n\n

It is well known that companies are risk-averse and therefore spend many resources every year trying to minimize risks.<\/p>\n\n\n\n

Business analytics can help you mitigate risks by informing you about problems before they occur. This is achieved using predictive models that simulate possible future scenarios.<\/p>\n\n\n\n

Types of Business Analytics in Companies<\/h2>\n\n\n\n

There are four main types of business analytics: descriptive, predictive, diagnostic, and prescriptive.
Descriptive analysis is the interpretation of historical data to identify trends and patterns.
Predictive analytics focuses on using this information to forecast future outcomes.<\/p>\n\n\n\n

Diagnostic analysis can, in turn, be used to identify the cause of a problem.<\/p>\n\n\n\n

Prescriptive analysis ultimately uses tests and other techniques to determine which outcome performs best in a given scenario.<\/p>\n\n\n\n

Difference between Business Analytics and Data Science<\/h3>\n\n\n\n

It is essential to clarify two terms that are frequently confused: Business Analytics and Data Science.<\/p>\n\n\n\n

Although Big Data<\/a> Although both processes are used to solve business problems, they are separate fields.<\/p>\n\n\n\n

The main goal of business analytics is to extract information from data in order to guide decisions, while data science focuses on drawing conclusions from raw data using algorithms and statistical models.<\/p>\n\n\n\n

In the first case, tasks such as budget planning, forecasting, and product development are carried out. In the field of data science, on the other hand, the focus is primarily on creating statistical models.<\/p>\n\n\n\n

Business Analytics vs. Business Intelligence<\/h3>\n\n\n\n

Even though these are different things, it should be mentioned that Business Intelligence<\/a> or business intelligence and business analytics, or business analytics, are based on the same idea: to optimally use information to make better decisions.<\/p>\n\n\n\n

Nevertheless, they differ in four important concepts related to the data analyzed, the way it is stored, the purpose of the information, and the variable studied by each of these disciplines.<\/p>\n\n\n\n

Business intelligence attempts to explain facts using historical data. In this case, the entirety of the data used, drawn from business history, is usually well-structured and stored. Within this discipline, it is relatively easy to discover patterns.<\/p>\n\n\n\n

Business analytics focuses on future trends, using predictive models to support decision-making. Instead of relying on internal company data, business analytics utilizes macroeconomic trends and indicators.<\/p>\n\n\n\n

Business analytics is one of the disciplines that has a strong business vector, precisely because it provides the ability to make predictions in a world where change is the only constant.<\/p>\n\n\n\n

Unlocking the full potential of this technology would be impossible for SMEs without tools like SAP Business One and its analytical capabilities. Contact us anytime if you’d like a free demonstration.<\/p>\n","protected":false},"excerpt":{"rendered":"

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