What are the types of Data Analytics?
Data Analytics includes computer programming, mathematics, and statistics to find out the trend and solve problems related to improving performance. Bornate Ensures Robust Analysis of the Big Data e-commerce, and the highly qualified professionals of Bornate leverage a range of management techniques, that includes mining, cleansing, transforming, modeling of the. Well, Data Analytics can be divided into four common types, which are listed below:
- Descriptive Analytics In simple terms, this is the study of what has already happened and what is happening in the present scenario. This form of analytics uses historical and recent data from various sources to understand the present scenario. This normally looks after the trends and patterns of the businesses.
- Diagnostic Analytics Diagnostic Analytics is the study of the present situation. In this process, experts take the help of the data for the finding of the reasons that previously hampered the growth of the business.
- Predictive Analytics Predictive Analytics is the study of the future. This needs a huge amount of technique that includes modeling, forecasting, and machine learning to understand the future outcomes of a business. This is also commonly known as ‘advanced analytics’ and totally depends on the amount of calculation.
- Prescriptive Analytics This is the study of what we are going to do. This is the advanced form of study that involves the application of testing and also further includes several more techniques to understand the specific solution that will be further utilized for the growth. Bornate in San Francisco uses machine learning, business rules, and algorithms for Predictive analytics.
What is the method and technique of Data Analytics?
E-commerce Analytics from Data to Decisions requires a lot of methods and techniques to analyze particular data. The methods and techniques are listed below for your better understanding:
- Regression Analysis This is a statistical process used to estimate the bonding between variables to understand how the changes of one variable are affecting the others. While performing regression analysis we look after the relationship between the dependent and independent variables. The main concern of this analysis is to focus on how many variables might provide an effect on the dependent variables. There are various types of regression analysis and also includes several types of methods and types of data and variables.
- Monte Carlo Simulations This process of technique is used to frame out the probability of several outcomes by forming a process that is hard to guess by others. This technique is used to understand the risk factor. This method of analyzing is performed to conduct analysis of risk factors of a business, and also provides methods to perform better forecast accordingly.
- Factory Analysis This is a continuous method that is used to bring out massive data set into a rigid small and manageable set. The added benefit of this technique is to uncover hidden patterns. It normally focuses on the various separates and observed variables. These variables can further help to construct a business. This also allows you to explore different counts that include Wealth, happiness, fitness, or customers review or loyalties.
- Cohort Analysis The process involves breaking data set into several other groups with a common interest, characteristic, or cohorts, for further studying in the Cohort Analysis. This method is used to know about the segments of the customers. We help you to decide your customer with this analysis into several specific groups and thus you can have a clear idea about your customers as well.
- Cluster Analysis Cluster Analytics can be defined as the class of techniques that are used to signify objects or cases inside the same group called the Cluster. This method is used to reveal the structures of the data. This technique is also further used to bring out the trends with specific claims of insurance. We help you to group a large customer base into varieties of segments. We also further help you to target more customers.
- Time Series Analysis This is the analysis of the data from time to time. This need be formed within a period of time or interval. This is the hardest technique for data analysis. This method is used to find out the trends and cycle over a period of time. This can be further dived into: – Trends – Seasons – Cycle pattern
- Sentimental Analysis This form of analysis provides a broader classification of texts. It analyses each text with a deeper analysis. With the help of the sentimental analysis, our team helps to receive great interpretation and classification of emotions. This type of analysis can be further divided into three main parts.