Unless you are a manger or a business owner, you probably have very little idea about what goes on behind the scenes of big companies. The truth is, it is a lot more complex than you might think. One way many businesses keep organized is by looking at their statistics and deciphering what they mean. However, this is a complicated task, which is why most companies have data analytics solutions to do the job for them. If you are unsure what these systems are, keep reading to find out.


What is the definition?

The term encompasses a range of processes, including business intelligence, business analysis and advanced analysis. DA focuses on examining data in order to get a better understanding of the information. With the growth of technology, more software is being used to complete this process and many organizations opt to use a data analytic solution. These systems are often used in the commercial industry and give companies the needed knowledge to make well informed decisions.



What are big statistics?

This is the procedure of studying large, wide varying sets of numerical information. In doing so, unknown patterns, hidden correlations, market trends and customer preferences can be discovered; this added information helps the decision making process in regards to business matters. In other words, it is a more advanced way of analyzing information and often includes predictive models, statistical algorithms and hypothetical scenarios that are generated by high performance data analytics solutions- usually in the form of software. Essentially, this form of statistics is DA on a larger, more detailed scale and will offer more in depth results.


What are the types of Data analytics solutions?

Data analytics solutions are complicated and intricate and are therefore quite difficult to understand. However, there are some basic ways of distinguishing between the different methods used by many organizations. The first easy way is by deciding if the information is considered to be quantitative and qualitative. Quantitative statistics revolves around numbers and will give all information in numerical form. This differs from qualitative which focuses on all information that is not number based; this includes text, images, audio and visual. As a result of this the latter type can be interoperated in many different ways.  Furthermore, at a more advanced level DA can be separated into many different sub sections. Some examples of these are: EDA (exploratory) which tries to look for patterns and relationships in information and CDA (confirmatory) which uses statistical techniques to deciphers if a hypothesis about information is true or false. Furthermore, businesses sometimes use ‘mining’ to sort through information to identify trends, patterns and relationships alongside predictive analysis which hopes to predict and understand customer behavior.


Why is it DA important?

Although it may seem like a complex task with very few rewards, this is not the case. Data analytics solutions provide the needed information to help any commercial business run as smoothly and profitably as possible. As a result of this, the software helps to find new revenue opportunities and improved operational efficiency. Both of these things give any business a competitive advantage over other companies in the industry. The applications answer questions such as ‘what happened?’ ‘when did it happen?’ ‘why did it happen’ and ‘will it happen again?’. The answers to each of these questions will enable managers or business owners to make better decisions. Furthermore, the answers to the questions will also allow for more effective marketing strategies and improved customer service. Better customer service means customers will return, meaning a better profit margin. In short, these systems provide the information and the answers to enable businesses to be better, meaning they will make more money and be more highly regarded than their competitors.