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The International Association for Business Analytics – IIBA defines business analytics as a set of knowledge, techniques, recommendations, and approaches in discovering a company’s needs, problems, and opportunities. With the help of this knowledge, an analyst must research and find a comprehensive solution for the realisation of all opportunities. Through the rapidly increasing development of the field of informatics, the need has arisen for a more precise definition of processes, needs, and requirements that an individual company has to pursue its strategic goals.
An Introduction to Business Analytics
Business analytics is a set of tasks, knowledge, and techniques that helps you perform different functions, processes, and activities to reduce total costs. Also, it aims to use resources more efficiently and provide better customer support. It must be focused on continuous improvement of existing processes or the creation of new ones, and thus on ensuring continuous optimisation to achieve higher efficiency. Today, processes no longer rely on individual development or individual projects but more on centralised process management and data science, connecting various organisation segments.
Business intelligence does not know a single truth. It observes problems and opportunities from multiple sources. BA rejects arguments of power, merely superficial elimination of the consequences of problems and the introduction of compromise solutions. On the contrary, it is committed to finding the root causes of problems and encourages the creation of comprehensive creative decision-making solutions.
Main Challenges in Business Analytics
Today, in companies, as a rule, reports are still prepared by individuals who use mostly the same basic data in their work. They connect it with the additional data sources, each from their own point of view. In addition, data is repeatedly overwritten and entered in various tables, resulting in errors. Relatively much data is edited directly in the reports, rather than being edited at the source itself within the data warehouse. As a result, there are differences between individual reports, which causes us unnecessary work in preparing analyses from pre-prepared reports.
The next problem is the absence of employees in charge of preparing individual reports, which causes unwanted delays. Significantly too much time is spent on the data collection, insights, and analysis. In the end, the analyses and reports prepared in this way are based on static rather than dynamic data.
In optimising their operations with the goal of greater efficiency and effectiveness, organisations have two major fields of reserves and potential. The first is related to the word “connection”, which refers to closer ties with customers, as well as more active cooperation of all functions and units. The second is related to the comprehensive and in-depth solution of problems. This includes eliminating the causes and not only the consequences of weakness in business decisions.
Research in Business Analytics
The first step in a research challenge is to define your own needs. What do you want to achieve? Setting the goals and methods of your survey focuses on the resolutions you need to make. If you have more than one goal, you may first need to conduct a qualitative study (for example, through focus groups) to define which issues are primary.
Social networks have become very popular for consumer behavior research, so it is a great channel to involve a wider circle of people in the topic you want to deal with. You can create a short survey, even just one question, to get feedback on what is most important to consumers. You may even try to use some alternative research methods and see different approaches simply by searching for a question “Will someone write my research paper?”. This will help you create a good questionnaire instead of a robust one that will result in complex data to analyse later in the report.
Most of your questions should be quantitative in nature. Quantified, measurable data will give you the ability to influence it in the future. You can also use a few qualitative questions, but keep in mind that the number of open questions should be limited. Ask only questions that are relevant to the objectives of the task.
Many new businesses also rely on technologically advanced tools and methods. Next to data science methods, the company’s management can decide to employ machine learning methods. Machine learning is based on the concept borrowed from computer science. Accordingly, there are generic algorithms that can suggest gripping facts about data records. This all goes without having to write a special code for the issue. Rather than assembling a code, you insert data into a generic algorithm that makes its logic based on the data.
Gaining insight into the perception of a brand, product, or service, whether in general or in relation to the competition, is a good way to determine the steps that need to be taken to improve and enhance a company’s position.
Is There a Difference Between Analytics and Analysis?
While the focus of operating systems is the execution of processes, the task of analytical systems is the data analysis of processes. Analytical systems must answer, for example, questions such as the sales trend of the last five years, whether the marketing campaign has had a positive impact on sales, and who are the best customers. Data scientists here won’t observe an individual transaction but overall transactions and aggregate their values. Interaction with analytical systems is done through queries that return data on processes. These queries generally involve many transactions, as opposed to transactional systems that typically focus on specific transactions.
The analysis involves the application of scientific research and explanation of reality by breaking down a whole into its constituent parts and considering each part for itself and in relation to other parts of a given whole. Its descriptive character implies the presentation of quantitative and qualitative characteristics of the subject of analysis. The research characteristic implies the research of relationships, causal relationships, laws, and tendencies of individual research areas. Relationships can be right or wrong, normal, or abnormal. The information obtained based on the analysis is the basis for rational management.
Conclusion
The essence of the changes in the company’s economy was focused on survival, growth, and development. Also, it is based on finding adequate management concepts to better and faster internal and external adjustment of the company. The common goal of management and an analyst is the lasting success of the company. To achieve this goal, businesses use data science, social science, and many other resources. The modern environment brings new ways to analyse big data and thus helps a company maintain its health while progressing towards new achievements.
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