Whether it’s a big business project or small, when it comes to making a decision, or you have to choose one option out of many. Then it’s not always easy. However, data analysis is a great process of analyzing piles of data and extracting the most relevant information from it. So that it would make a good choice.
Today we’ll discuss data analysis, its importance, types, and how it works. Here it follows;
What is Data Analysis?
Data Analysis is a business analysis strategy that gathers, analyzes, and interprets data to find the most relevant information out of it. Because businesses are shifting toward a data-driven process that can positively affect the decision making. In simple words, the purpose of data analysis is to find the useful and relevant information that would help the business to make a good decision.
In our daily life before making any decision, we recall our past experiences and the choices we made during that time. Our past experiences and choices provide us basis for the future decisions. In other words, we analyze our past experiences and choices for the future decision. Data analysis for the business works the same way.
Importance of Data Analysis for Business
Here are some of the reasons why data analysis is important for your business;
When you have analyzed the data of your target market, then it helps you to find out how you can better reach your customers for the new product. Data analysis also helps you to choose the best promotional advertisement that would attract and bring new customers. You can also improve your current marketing ads, and you can have a better product that would satisfy customers.
Since you have the experience, data analysis would make you estimate the lowest possible cost for the best product and promotional marketing campaign. When you have the proper information on time, then it not only helps you to save a lot of time and resources. But you can also use that time for SEO (search engine optimization), and techniques to improve the ranking of your website.
Know Your Audience
One of the best advantages of data analysis is that you can evaluate the performance of your business and what category of product/service is working or not. When you know the tastes of customers, and what they want from a product. Then you can redirect all the company’s focus on those areas that would serve the business better, and fulfill customers’ needs and requirements.
When you have sufficient information, then you can set the most appropriate price for the product/service, which the customers are capable of and willing to pay. When you know your customers, then you can adopt the best marketing and advertisement campaign to target your customers.
Data analysis would guide you to run your business smoothly and effectively, because when you know the dos and don’ts. Then can cut down the unnecessary costs of your business, which are just eating up your assets and making your balance sheet lengthier. When you do this, then you would know that what technology you should use to lower the cost.
Data analysis assists you to answer questions like; what type of production method or advertising campaign that you should choose that would deliver you the best results. Andromeda is one such company that helps you to conduct the data analysis of your business.
Problems are bound to happen and they stop the productivity of the whole organization, which results in the form of losses to the company. When a business makes a good decision based on the data analysis, then it would help the company to avoid such incidents. If a problem has arisen in the company, then data analysis would help you to identify the quantity and quality of the problem.
When you analyze the data of your company and customers’ market, and you would see patterns and trends. However, if you study the patterns and trends of the customers market, then data analysis can guide you to predict the future.
Types of Data Analysis Methods
Types and methods of data analysis are as follows;
Descriptive analysis is the simplest and most common form of data analysis; it provides you the insight about the foundation of the data. Descriptive analysis usually summarises the previous data and answer the questions like ‘‘what happened.’’
Descriptive analysis is very important to identify and keep track of key performance indicators (KPIs), and those KPIs help you to scale up the performance of your business based on the predefined scale. The business application of descriptive analysis comprises of monthly profit/income statement, sales report, and the dashboard of KPI.
Diagnostic analysis starts with answering questions like ‘‘what happened,’’ but diagnostic analysis helps you to find the most important questions like ‘‘why it happened.’’
The diagnostic analysis lays the foundation of its research on descriptive analysis, and goes much deeper and finds whatever is in it. Companies and businesses use diagnostic analysis to find more information to connect the dots, develop patterns, and create trends.
Diagnostic analysis is a critical step to gather well-detailed information. The purpose is that if some new problem comes up, then you must have relevant information related to the problem. If you have got access to the data, then you should repeat the research work and try to find the link.
The application of diagnostic analysis is that when a Cargo company investigates the slow delivery in a certain region.
Predictive analysis answers the questions like ‘‘what is going to happen’’ in the future. The purpose is to analyze past data and predict the future. It is an upgraded form of both descriptive and diagnostic analyzes because it utilizes and summaries both forms of data and foretell the likely outcomes of the future event.
Predictive analysis depends on the statistical figures and numbers; therefore, it needs technology and resources to complete the forecast. Since the forecast of predictive analysis is an estimate, the accuracy of the final prediction depends on the quality and relevancy of the data.
Businesses and companies use descriptive and diagnostic analysis in their routine, but they don’t often use the predictive analysis. It’s because of two major reasons; first, it’s difficult to conduct predictive analysis. Secondly, many companies and businesses don’t have either the skill or the resources to forecast. That have resources are reluctant to invest in such a project.
Some of the business applications of predictive analysis are; sales forecast, risk assessment, and finding out the leads that are likely to be converted.
Prescriptive analysis is the most desired and demanded stage, because it requires the analysis of all the previous types (descriptive, diagnostic, and predictive), and take the decisive action for the prevailing problem.
It uses art, science, technology, and data analysis approaches. Therefore, it requires a great amount of commitment that the business must be ready to move forward.
AI (artificial intelligence) is a very good example of prescriptive analysis because it analyzes a bulk of data and information and then makes a good decision. If AI is designed well, then it would be perfectly capable of making decisions and taking actions. Artificial Intelligence (AI) performs routine tasks without human assistance.
Data Analysis Process
Now, the question is how to perform the data analysis process. Follow these steps to perform it;
Define Your Problem
If your business or company is facing some issues, then you should start with defining the right question. The question should be clear and precise. Only then you would be able to find the right solution if you have a clearly defined question.
For instance, costs are prices are high, and a government contractor is facing issues to submit the proposal of his contract. The most obvious question would be that could the company perform the same if it downsizes the current staff?
When you have clearly defined the problem; now you have moved to the stage of collecting the data to solve the problem. However, keep these steps in mind before collecting any data.
If you have the current existing database, then check out there that you could find something there.
You should divide the tasks among your team members, and assign them different names and numbers. It would help you not to save the data repetitively.
If you’re collecting through interviews and observation, then prepare the questions and checkpoint template before time.
Once you have collected the data, organize it correctly.
Whatever data you have collected along with your team; it would probably contain some errors, duplicity, and irrelevant to your study. If you do find it, then you remove all the irrelevant data before moving to the next stage of data analysis.
After collecting, cleaning, and processing your data. It is safe to say that you are at the analysis stage. If you have found some irrelevant information, then go back and collect it again. If the information is exact and correct, then you can move forward with the analysis. You can also use data analysis software tools to analyze the data and make a good decision.
After successfully analyzing your data, it’s time to interpret, express, and communicate the result of your data. You can present your data either in the form of charts, tables, or words.
When To Do Data Analysis
The question is what should be the most appropriate time to conduct the data analysis of your company? You can perform it either before making any big decision that would impact the whole company. Or you can also perform data analysis regularly for yearly evaluation of your business.
Data analysis has different types, and the process of conducting data analysis would be different for every type. It’s better to know in the beginning that for what purpose you want to use the data analysis.
Photo by Kevin Ku