What is Business Analytics?
Jun 15, 2020 ● 10 min read
While it is great to have your business data handy, what you do with it can make or break your company’s success. That’s where business analytics comes to play.
Table of Contents
- What is Business Analytics?
- How Does Business Analytics Works?
- Components of Business Analytics
- Types of Business Analytics
- Uses and Applications of Business Analytics
- The Bottom Line
What is Business Analytics?
Simply put, business analytics refers to the acts of converting your business data into accurate business insight. From a comprehensive view, business analytics means the collation of business data from diverse sources, processing them, and utilizing various strategies to extract the desired insightful data from these datasets.
In the present world, business analytics is simplified with the help of high-tech tools and software that provides insightful data with a simple click of an icon.
In recent times, business analytics has strongly evolved into the world of businesses. Though small and medium scale businesses are yet to fully wake up to the benefits of business analytics, large scale businesses are already prioritizing the use of business analytics.
Besides, large enterprises have continued to hire the services of experts in business analytics to help them purchase or invest in business analytics tools. Ultimately, it is believed that these tools and software will help them make business decisions that will drive them towards their business success.
In this piece, we’ll be revealing every relevant information about business analytics. From its mode of work, importance, components, and tools to the practical examples of business analytics, we’ll be feeding you with the much-needed details about business analytics.
How Does Business Analytics Works?
Usually, the first step of business analytics involves the collection of data. However, it doesn’t simply say that all data are collected. First, the business analysts follow due process by setting the parameters for data collection. This will foster a smooth collection and collation of data. The importance of setting parameters is that these parameters help to ensure that specific data are covered, which will provide meaningful insights into a particular business needs.
After the data collation phase, the next is the data processing phase. The collected data is then processed with the aid of analytics tools or software. To make more sense of the processed data, the reports are prepared based on the most insightful data from the dataset.
Modern business analytics tools and software are unique and advanced. This is because they perform the roles of executing every step beginning from the data collection stage to the last stage, which is the preparation of reports on insightful data. These reports are unique and useful in the sense that they help forecast for the future. Take an example below of the Whatagraph live report.
Apart from that, these reports are used to create effective business strategies while considering the associated risk management and losses of capital. Interestingly, one of the most accurate sciences in the world today is statistics. Similarly, one of the most modern and technological forms of statistics is business analytics.
Components of Business Analytics
There are several components associated with business analytics processes, tools, or software. It may interest you to note that each of these components plays significant roles in becoming a vital gear in the machinery.
Hence, the smooth and effective running of business analytics requires that these components be in perfect working condition. Here are the essential components of business analytics:
Data aggregation involves the collation or collection of business data into a single or central location. After this, the process of sorting begins. In this stage, inaccurate data is eliminated, and only the potentially useful data is left behind. This stage is where the available data is checked for duplication or repetition. Any duplicate data found will be removed entirely. Of course, these data are usually gathered from a wide array of sources.
A typical example is the volunteered data. Usually, volunteered data are gathered from both physical and digital forms that have been rolled out to customers or consumers for filling. This form is either made available to the consumers directly or through a third party. The other type of data source is known as tractional data. This refers to data shared by organizations. It is usually gathered from shipping records, banking transactions, and sales records.
In the course proceeding further in your business analytics component, data mining is the next stage after data aggregation. Data mining is the stage where unknown trends and patterns are revealed. During this process, one is required to mine through a vast amount of data. This is done through the creation of mining models. In this process, a wide variety of statistical models is utilized. One of such models is the classification demographics. Another involves the use of those parameters in sorting data.
In the regression model, which is typically based on historical patterns, numerical values can be predicted. One other popular method of data mining is clustering. This involves the prediction of classification factors to determine the exact variable to use.
Association and Identification of Sequences
This involves the patterns of consumer’s behaviors. In the association part of these behaviors, consumers tend to purchase products that are similar to each other—for instance, shampoo and conditioner or toothpaste and toothbrushes. Similarly, in the identification of sequences, this involves the identification of the sequence of purchases. A typical example is a sequence of booking an airline ticket, airport cab ride, and booking hotel rooms.
The association and identification of sequences make it extremely easy and straightforward to identify the next item on the customer’s purchase-list. Ultimately, this clearly defines and helps to understand the customer’s purchase pattern and behavior.
What constitutes text mining? These involve the text or comment types in blogs or social media pages or of a business. Also, the interaction of customers with a customer service call center is considered an essential component of text mining. This is due to the importance of these comments or feedback on improving customer services of businesses.
One of the main reasons why people show some forms of loyalty towards a product or brand lies in the power of its customer service.
The data collected from text mining makes it easy to develop new products or modify existing ones.
Text mining is also an essential component of business analytics, which helps to monitor competitions. Apart from that, it also grants meaningful insight into the developments that are being made in that specific business.
There is a famous quote that goes thus, “history usually repeats itself.” Incredibly, this saying possesses some iota of truth when it comes to the forecasting components of business analytics. Customers or consumers tend to exhibit certain traits or behaviors tied to specific periods or seasons.
Forecasting is a business analytics component that’s capable of helping you observe and plan for these repetitive behaviors. A typical example is the purchase of clothes while preparing for warm weather just before the cold season or purchase of sporting merchandise in preparation for sports seasons. Another example is the increased search for specific keywords on the internet based on current events like COVID-19.
Based on the business data, one can create, manage, or deploy predictive analytics to predict specific events accurately. One of the primary roles of this business analytics component is that it helps companies and businesses understand future occurrences or events. Understanding these will foster a sense of preparation to address those future events.
Predictive analytics is a business analytics component that helps to reveal the exact time failure will occur. Apart from that, it helps to predict wear and tear in equipment if previously subjected to unfavorable conditions for a specific duration. Also, it helps to make a detailed classification of customers while also making predictions based on visible future trends.
Business analytics plays a significant role in optimization components. For businesses, analytics can be greatly used to optimize operations. The optimization component of business analytics helps to anticipate a surge in demand and provide valuable insight to step-up production and maintain or increase supplies. Ultimately, this helps to increase the flow of revenue.
Apart from that, they can offer their products at a competitive price if there is any form of peak or shortage of product supplies. Based on business analytics data, businesses can also make use of the opportunity to create sales, offers, promotions, and discounts.
One of the most effective ways to present data is through the use of business analytics components known as data visualization. The benefits of this visual form of data cannot be overlooked. While it helps companies and businesses to make reports and redefine their business goals, it also helps to leverage the business data to increase revenue, and improve customer relations. Above all, the visual format is highly easy to explore, model, and analyze.
Types of Business Analytics
Business analytics has four types. Each of these types seems increasingly complex and makes it easy to use in real-time as well as future situations. Usually, these types of business analytics are implemented systematically in stages. And of course, it begins from the simplest to the most complex. However, all of the four types have a similar importance as they are all interconnected or interrelated.
Incredibly, these four different types of business analytics provide valuable insight into the roles of each in business analysis. No doubt, you’ll be able to create meaningful solutions to many of your business challenges by leveraging these four types of business analytics.
Descriptive analytics is undoubtedly the first phase of business analytics. What does it do? It helps to give a clear picture of the past occurrences or presence scenarios. Ultimately, this provides you with an understanding of both scenarios while you critically look at the impact of those situations on the current state of your business. In this stage, the two main business analytics components are data aggregation and data mining techniques.
The descriptive analytics stage is the stage where you define and understand your business strength and weaknesses. Based on this report, you can then develop strategies that are capable of improving your business. After all, descriptive analytics presents a clear, unadulterated picture of all the statistics you can use.
However, there is a limitation in the statistics provided in this stage. If you want to know more, you need to move up to the next stage.
Now that you’ve had an insight into the past and current issues in your business through the descriptive analytics, the next thing to understand the reasons for those issues. That’s what diagnostic analytics does.
The diagnostic analysis grants a more critical look into the past and present issues in your business. It provides an insight to help you understand the reasons why those issues have occurred both in the past and the present.
With the providing of likelihoods and probabilities, diagnostic analytics helps to reveal the reasons why such has happened. Based on these data, you can then strategize to improve your business. Diagnostic analytics employs some business analytics components, including data mining, data discovery, drill-down, and correlations.
However, diagnostic analytics also has limitations in its ability to provide actionable insights. This is because it deals with correlation results as opposed to confirmed causations of the root causes of those events.
Now that you’ve scaled through the past issues, the next is to move to the third stage of business analytics, which is the predictive analysis. This is the stage where the future occurrences are revealed. Predictive analysis is a highly crucial stage in business analytics. This is because it requires the services of machine learning experts and data scientists to execute the predictive analysis correctly.
These machine learning experts and data scientists help to build statistical models and machine learning models, respectively, upon the previous stages of business analytics. This provides the opportunity to run a predictive analysis using statistical models coupled with learning algorithms.
The most popular application of predictive analysis is sentiment analysis. This involves the collection of existing data from social media to provide a clear and detailed picture of opinions held by a user. Usually, this data can be subjected to analysis to predict the sentiments of customers towards new subjects. Above all, the predictive analysis provides detailed reports that will foster complex predictions for your business.
Here comes the final stage of business analytics. Prescriptive analysis, however, goes further than predictive analysis. This is because it allows for making accurate predictions and makes real-time changes that will drive you towards the best possible results.
Apart from that, the prescriptive analysis helps you generate action-based models to arrive at your desired results for your business. The most popular product of a prescriptive analysis is the recommendation engines. These are engines that work in real-time and drives accurate and excellent results. This is due to the dependence of these analyses on sound data, complex neural networks, and deep learning. Prescriptive analytics provides you with the best recommendations on the much-needed results from your business.
Uses and Applications of Business Analytics
Business analytics are effective and functional in a wide range of applications. If you do not know, it is one of the biggest game-changers in the modern world. This is why businesses need to understand and realize the importance of these business analytics. Here are a few of the uses and applications of business analytics.
Start a Business
Using the accurate data and reports generated by business analytics tools, you can start a business in the most prepared manner. And of course, there is no barrier to having the best chance of success.
Grow Your Business
Business analytics is one of the safest and effective ways to grow your business. Apart from that, it helps you to eliminate all fears and risks. Decisions taken through the use of these business analytics can have the best chance of success.
With business analytics and business analytics tools, tons of data is generated. Of course, there are numerous ways to analyze these data efficiently. However, business analytics remains the best way to analyze and process the data to generate valuable insights into your business.
Create Business Strategies
The best business analytics will provide you with valuable insight to remodel your business strategies through prescriptive analysis. All you need to do is to implement these strategies and watch as your business shoots up the ranking.
Stay Updated With Business Trends
Undeniably, trends are subjected to changes. However, business analytics tools or software keeps you updated regarding the latest trends. Apart from that, you stand a chance of implementing these trends to develop and grow your business.
The Bottom Line
Business analytics is undeniably an excellent field to venture into. This is because of its potentials to change business models for the better. Several business analytics tools and software are currently being utilized by many of the largest businesses. Incredibly, they have become a crucial part of their daily lives.
Business analytics has a wide range of benefits to offer to your business. The challenge lies in the effective utilization of these tools to gain valuable insights into your business challenges and problems. After then, you can modify or remodel your business strategies to improve your business success.