Descriptive
It describes the past happenings based on the data available in form of reports and graphics.
Diagnostic
It links to descriptive type as diagnostic analytics seeks to understand why such happening happened in the past. It brings more details of descriptive analysis.
Predictive
It is a resourceful analysis type for companies as it analyzes data to understand what could happen from the events that happened in the past.
Prescriptive
It depends on Automation processing or a/b testing as it brings a solution to the accruing problem. Because it works with descriptive and predictive analytics. The system analyzes and predicts data and provides solutions as to how to proceed according to them by recommending solutions. For example, what are the best template suggestions for your website and thus recommending options? Big data analytics help businesses understand the UX better. Because it finds overlooked opportunities and services and thus helps to understand how one can make the best use of these. It also helps to navigate how one can mitigate fraud.
Big Data Analytics Tools
There are different tools to analyze the various fields of data such as healthcare, transportation and more. Different tools help in the process of analytics of data from different field. The tools that analyze data are as such
Step#1: Evaluation
In this step, the business problem is brought to the table and the teams describe the causes of setting particular goals related to this analytics.
Step#2: Data Collection
In this step, the big data collection starts where the process of collecting data from different resources takes place. All this relevant data may provide value to the particular category your company is targeting. It is then the data filtering process starts.
Step#3: Data Extraction
After filtering the data, the process of sorting out relevant data takes place. Because once you identified the relevant data, the filtering and extracting help narrow down the data of the targeted category. Thus, the extracted data is then going through the process of integration with different data sets of the same category.
Step#4: Data Analysis
Now, the fun part begins, when using tools to analyze all the extracted data and thus find the useful information.
Step#5: Creating Visuals of Analytics
Here, you can use different tools such as Tableau and Power BI to create visuals for your analytics.
Step#6: Data Analytics Results
Lastly, the data analytics results have complied to provide to stakeholders who then take further action.
Hence, the process of data analytics goes through different steps that help to identify, filter, extract and analyze data. In the digital world, the data serves as oil to any company therefore big data becomes resourceful. It provides crucial information that saves time, reduces cost and creates new ideas regarding products and services of your company.