Business analytics is the combination of the fields of business, management and computer sciences. The business side involves both an advanced-level knowledge of the business itself and the practical restrictions that arise. The analytical part includes an understanding of statistics, data and the science of computer science. This part of the business analytics framework involves applying business analytics to the business and its activities. This knowledge can be used to provide managers with improved decision-making tools, better strategies and plans, and accurate internal control systems.
Analytics and Data Mining
Analytics can also be used for profit-extracting purposes. As business analytics and the business analytics model grow more sophisticated, the business may need the help of outside services. Data mining is one such service that analytics professionals commonly engage in. Data mining is the process of looking for profitable business relationships and then applying the business analytics framework to these relationships. The business analytics concept here is that a company should be able to identify the relationship between different aspects of the business (key areas of business focus include marketing, business development and operations). This article presents some of the business analytics basics to help managers and other employees understand the business analytics model better.
Data mining can be implemented using different strategies. In a business analytics exercise, the business analyst will exploit the business analytics framework by conducting a research exercise on a particular business domain and identifying the key business drivers or business areas. Then the business analyst will extract the key information from the empirical study and then relate this information to the business analyst’s business model. This gives rise to business analytics’ second aspect of data-driven decision-making.
The descriptive aspect of business analytics is descriptive. It refers to the process of obtaining and comparing quantitative data relevant to the business domain with business intelligence tools. The goal of this approach is to build predictive models or formulas on which the business intelligence is based. This is referred to as the predictive capability of business intelligence tools. This allows the business analysts to solve problems analytically rather than using the less direct and less quantitative techniques such as the rank-based and customer satisfaction techniques.
Another aspect of business analytics is predictive analytics. This is the analytics that attempts to provide a forecast of the future direction of the business based on statistical data. This is done by the use of sophisticated statistical methods that attempt to reveal business intelligence through the use of complex mathematics. Examples of such advanced statistics used in predictive analytics include forecasting techniques, lagging indicators, momentum indicators and artificial intelligence techniques. The main objective of predictive analytics is to provide business intelligence in the form of numerical predictions.
Strengths and Weaknesses
Both business analytics and descriptive analytics have their strengths and weaknesses. These two analytical methodologies need to be compared when it comes to the business context for the business owner to determine which one to employ. The strengths of business analytics are its ability to detect trends and the ability to forecast trends. However, business analytics weakness lies in the inability to provide quantitative information that can be mathematically calculated. This weakness is what makes business analytics fall short of its aims and purposes.
The strengths of business analytics lie more in the ways how it can gather the necessary information that will be used in business analytics. It can combine quantitative and qualitative statistical analysis to provide the business with the business intelligence needed. Unlike statistical analysis, business analytics is more prone to the use of creative strategies to arrive at the most appropriate conclusions. Business intelligence can also be referred to as the ability to translate the collected empirical data to the business context to gain insights on the business context. While the traditional statistical methodologies rely mainly on arithmetic data and logic, business analytics uses a blend of the two analytical methods to derive business intelligence.
There are several ways by which you can measure the business intelligence that you have acquired through business analytics. The major measurement units are the business units, the customer segments, the business process, the business outcomes, and the business intelligence. These are the different aspects of business analytics that need to be measured for the business owners to come up with the appropriate strategic decision solutions. By the application of the business intelligence, the business owners will be able to gain the necessary insights on how the business processes operate, how the customer perceptions are, the business analytics can also provide the business analytics solution.