Business analytics is at the centre of the future of business. Data is the new currency and it’s what will set apart successful businesses from the ones that fail to see the future.
Business analytics is used by companies to understand what is happening in their company. Some of the things that business analytics can do are measure the revenue & sales of a company, determine the product mix & quality and can even predict future sales.
Analytics has become a very important part of the business world and it is important to understand what exactly business analytics is. However, today, the majority of career aspirants are intrigued to learn about what is business analytics and its types. This blog will look at the different types of business analytics and how they can help guide your business to success.
What is Business Analytics?
Analytics helps in improving the business operations by helping in making decisions such as finding out profits and losses, improving customer relations, customer retention, etc.
Business analytics is an area that has seen a lot of development over the past few years. To keep up with the changes it is important to understand what is exactly business analytics and its types.
Getting the most out of data is the goal of business analytics. It’s about using data to make effective decisions and to improve business processes. It is a key component of the business intelligence and data science fields. Business analytics is the practice of analysing business data and converting it into valuable insights that can be used to drive the business forward. These insights can be used to make better business decisions, identify new revenue streams and also help identify new areas of innovation.
Now, let us get an insight of what are the types of business analytics.
What are the Different Types of Business Analytics?
A business needs to have a proper analytics system in place to understand and quantify its business. It will also ensure that each and every employee in the business is able to contribute towards its success.
A large volume of data is processed throughout the business analytics process. These four types of business analytics provide businesses with all the information they need, from what’s happening in the company to what improvements should be made.
Let us now understand different types of business analytics.
Based on the needs and stage of the workflow, here are four types of business analytics:
1. Descriptive Analytics: It helps describe or summarize the past.
2. Diagnostic Analytics: Identifies why something has happened based on historical data.
3. Predictive Analytics: Using past data, it anticipates what is likely to happen. Statistical models and machine learning techniques are used to predict the possible outcome.
4. Prescriptive Analytics: It refers to the process of recommending one or more actions based on analysis of the data.
Below, we have elaborated on the types of business analytics with examples.
- Descriptive analytics in business analytics
Businesses of today have to deal with a massive amount of data. Whether you are a data scientist or a sales manager, data has a role in your business. The type of data used may differ, but they need to analyse data is a common thread. Descriptive analytics is one of the simplest and most important forms of analytics. It is a subset of analytical techniques used for viewing the results of data. It is the first step of any analytics exercise. It is used to observe the current state of a business or a process.
Descriptive analytics is the process that is used in data analytics to draw insights by using descriptive statistics and other tools to display data in a way that is easier to read and interpret. Descriptive analytics is useful in easily identifying past patterns and current trends within the data that can then be used to derive insights and make the right decisions based on those. Its main goal is to answer the question “how much”.
A descriptive-analytic report is usually a table that contains the elements of the target variable and other variables that can help in understanding the target variable. A target variable is one that is measured or changed to achieve a particular goal.
Understanding raw data is imperative for investors, shareholders, and management. Through descriptive analysis, one can identify and address areas of strength and weakness that require attention. Descriptive analytics deals with descriptive statistics that help in describing the various average, variance and other measurements. It gives you facts, figures, and metrics about what happened. This is the data that is plotted in basic charts and graphs that we use to analyse the organizational data. This helps the business owners to figure out the best way to proceed.
- Diagnostic analytics in business analytics
Diagnostic analytics is one of the most important components of business analytics. It helps determine the cause of a problem and the solution to fix it. Diagnostic analytics involves digging deeper into data to find the causes of an event. It’s useful for determining what factors influenced the outcome through data mining, data discovery, and correlations. It helps you look at the bigger data and is a complete change from traditional analytics.
Diagnostic analytics is another important application used to assess the performance of the internal operations of the company. It is one of the key steps in a data science project and helps prevent unwanted risk. It is used to gauge the effectiveness of predictive analytics and identify the root causes of problems. An example of diagnostic analytics is determining why something happened in the past by examining historical data.
Diagnostic analytics focuses on the issue of why a specific issue occurred at the project level. For instance, if a specific project is not meeting the deadline, why is the project not meeting the deadline? The diagnosis may be that the team is not working effectively or the project management is not effective. Diagnostic analytics tries to find the root cause of the issue so that the issue can be resolved. Therefore, the diagnostic analytics approach is the methodology used by professional consultants who are specialized in diagnosing the root cause of a problem. Agile and diagnostic analytics are two of the most powerful initiatives in the business intelligence domain. Applying these initiatives together forms diagnostic analytics, which can be effectively used to drive the continuous improvement of the organization.
There are several diagnostic analytics methodologies such as principal component analysis, sensitivity analysis, and conjoint analysis. Training algorithms for classification and regression are part of this type of analytics.
- Predictive analytics in business analytics
Business analytics is more than just looking at historical data and then using it to predict future activities. Through predictive analytics, business analytics bridges the gap between insights and decision-makers.
Business analytics refers to a data-driven approach to business decision making. Businesses, both small and large, get their data from their systems and apply a range of analytics to it. But the cost of creating all the data and analytics required for your business is usually prohibitive for most businesses. Predictive Analytics, on the other hand, refers to the use of data and statistical analysis to forecast future trends and events.
As businesses are increasingly using data to drive their day-to-day activities, predictive analytics, or prescriptive analytics, are playing a bigger role in decision making. Predictive analytics helps businesses to understand the potential risks, opportunities, or problems before they arise. Basically, is all about using data that is available, to predict future events that may impact the business. The business decisions could be anything ranging from forecasting the future revenues, projecting the number of products to be produced based on the expected demand and a lot more. The data used in this analysis is obtained from a variety of sources like historical and transactional data, industry trends, analytic reports, past events and surveys. Being able to predict the future outcome of decisions is a great way to optimize decision making.
For instance, one can use it to predict anything ranging from the number of visitors we will have on a website to predicting the risk of investment. In fact, businesses like Netflix, Nordstrom, and Target are all using predictive analytics to predict future trends. Hence, with more data and advancements in big data, predictive analytics is being used in different spheres of business.
- Prescriptive analytics in business analytics
It is based on the premise that analytics should be used to address future opportunities rather than just understanding past performance. Prescriptive analytics is a small but growing field. It is particularly useful in situations where large volumes of data exist and it helps to radically simplify the way that individuals interact with the data.
In business analytics, the core of what we do are descriptive and diagnostic analytics. Descriptive analytics focuses on data exploration, report generation, and identifying trends. Diagnostic analytics focus on the problem we are trying to solve by providing insights into the root cause of the issue. Prescriptive analytics looks at the data to find the optimal solution. Depending on a specific path of action, it can provide positive outcomes, or multiple paths to reach a goal. Therefore, it uses a system of feedback that continually monitors and adjusts the relationship between action and result.
Switching from descriptive and diagnostic to prescriptive analytics can be a challenge because the way you will be solving the problem is different. In diagnostic analytics, you can use trial and error. In prescriptive analytics, trial and error will not work.
Prescriptive analytics is a very powerful set of tools that gives enterprises the ability to make choices to achieve their desired business outcomes. It gives us the ability to solve a wide range of business-related problems. It helps in predicting or recommending the course of action which will lead to the best possible results, under a given set of conditions. Prescriptive analytics is also referred to as “What-If Analytics” or “What-Next Analysis” or “Thought-Provoking Analytics”. Prescriptive analytics can be applied in a wide spectrum of real-life problems.
This concludes our discussion of different types of business analytics!
Business analytics may seem to require implementing these four techniques sequentially. Today, most companies have adopted descriptive analytics. Thus, they can directly opt to implement prescriptive analytics. Having identified the key area that requires optimization and enhancement, prescriptive analytics should be used to achieve the desired outcome.
It has been found that most companies are only at the beginning stages of utilizing prescriptive analytics. Over time, this will evolve as predictive analytics progresses. By leveraging these types of data analytics, we can improve predictions and make better decisions for the future.
As a result, a competitive advantage can be gained by utilizing the appropriate form of analytics at the right time. After reading this blog, we hope you are now better acquainted with business analytics meaning and its types.
Don’t forget to reach out to our admissions desk if you’re interested in pursuing a career in this career-driven field.
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