Business Intelligence Request Advancement – The business analytics process represents an organization’s step-by-step approach to performing analytics within the business analytics lifecycle. The approach may have specific steps depending on the organization, but the overall picture is more or less the same for all.
Business Analytics is a very widespread term across various industries in the 21st century. It corresponds to a set of methodologies and tools that change the way organizations approach decision-making. Since the impact of Business Analytics is very strong, organizations have defined the business analytics life cycle to make sure that you don’t make mistakes or miss out on any critical information. This process is called the Business Analytics process. The steps of the process can vary from organization to organization depending on many factors, such as industry, product type, company size, etc., but generally you can divide the entire Business Analytics process into six steps.
Business Intelligence Request Advancement
In this blog, we will discuss the Business Analytics process and its six steps in the following sections:
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Business Analytics is a term that has taken industries by storm in the 21st century. All businesses around the world were trying to make more and more profit and the only way to do that was to find gaps and fill them. The process of Business Analytics initially came as a problem solving approach in many organizations where data was collected and made available. This data was then used for a variety of purposes, from improving customer service to predicting fraud. Due to its huge success, people quickly realized that Business Analytics can not only solve already existing visible problems, but also alert them to illusory problems that seem non-existent.
As the world began to notice the impact of Business Analytics, organizations soon realized that its potential is not only related to solving problems, but they can also use it to predict, plan, improvise and overcome various obstacles they may encounter.
Business Analytics is a discipline where you use pre-existing data to discover key insights that can help you solve a business problem. To find said insights, you have to use many statistical models and also manipulate the data to fit those models.
In today’s world, Business Analytics is so important that almost every organization has a Business Analytics team and well-defined business analytics process steps. Because there are challenges and gaps in all forms of business, Business Analytics is a viable approach in all industries. From the food industry to the IT sector, everyone uses Business Analytics to discover optimal ways of doing business.
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Moreover, almost every organization today follows well-defined steps of the Business Analytics process. These process steps vary from organization to organization. However, some key steps remain the same for almost everyone. Let’s discuss them in this blog.
The Business Analytics process involves asking questions, looking at data and manipulating it to find the answers you want. Now, every organization has different ways of doing this process because they all work in different sectors and value different metrics more than others based on their specific business model.
Since the approach to business is different for different organizations, so are their solutions and the ways to arrive at solutions. However, all the actions they do can be classified and generalized to understand their approach. The figure below shows the steps in a company’s Business Analytics process:
The above image only covers an overview of the Business Analytics process. Now we’re going to translate this into actual troubleshooting steps.
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The first step in the process is to identify the business problem. The problem may be a real crisis; it could be something related to recognizing business needs or optimizing current processes. This is a key stage in Business Analytics as it is important to clearly understand what the expected result should be. When the desired result is determined, it is further broken down into smaller goals. Then the business partners decide on the relevant data needed to solve the problem. At this stage, some important questions need to be answered, such as: What kind of data is available? Is there enough data? And so on.
Once the problem statement is defined, the next step is to collect data (if required) and more importantly, clean the data – most organizations would have enough data, but not all data points would be accurate or useful. Organizations collect vast amounts of data through a variety of methods, but occasionally there are junk data or empty data points in the dataset. These erroneous pieces of data can hinder analysis. Therefore, it is very important to clean the data that needs to be analyzed.
To do this, you need to perform calculations for missing data, remove outliers, and find new variables as a combination of other variables. You may also need to plot time series graphs as they generally show patterns and outliers. It is very important to remove outliers because they can have a big impact on the accuracy of the model you are creating. Additionally, data cleaning helps you get a better idea of the dataset.
Once the data is ready, the next thing you need to do is analyze it. To do the same, there are different kinds of statistical methods (such as hypothesis testing, correlation, etc.) that allow you to discover the insights you are looking for. You can use any method for which you have data.
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The main way of analysis is to revolve around the target variable, so you need to consider all the factors that affect the target variable. In addition, many assumptions are also considered to see what the results might be. Generally, in this step the data is sliced and comparisons are made. Through these methods, you are trying to get useful information.
Gone are the days of using analytics to react. Nowadays, Business Analytics is all about being proactive. In this step, you use predictive techniques such as neural networks or decision trees to model the data. These predictive techniques help you discover hidden insights and relationships between variables, which further help you uncover patterns in your most important metrics. In principle, many models are used simultaneously and the models with the highest accuracy are selected. In this phase, many conditions are also checked as parameters and many “what if…?” questions are answered.
Based on the insights you gain from your model built on target variables, this step will create a viable action plan to meet the organization’s goals and expectations. Said action plan is then put into practice and the waiting period begins. You will have to wait until you see the actual results of your predictions and find out how successful you were in your efforts. Once you get the results, you’ll need to measure and evaluate them.
After the solution is implemented, the results are measured as above. If you find some methods that can be used to optimize the action plan, then they can be implemented. If not, you can continue to register the results of the entire process. This step is crucial for any future analysis, as you will have an ever-improving database. Through this database, you can get closer and closer to maximum optimization. It is also important to evaluate the ROI (return on investment) in this step. Take a look at the business analytics lifecycle diagram below.
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If Business Analytics is something that excites you, then you must consider a career in the industry as there are always new challenges and the demand is endless. You can check out our blog to learn business analytics and excel in your career. Happy learning!
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