Different Steps in Data Analytics
Data analytics is to learn how data is analyzed from the collection. We have different steps that are involved in data analytics.
Imagine we are running an e-commerce business and our company has a lot of customer base. And our target is to find out certain problems related to our business, and then come up with data-driven solutions to grow our business.
Below are the different steps that we can take to solve our problems:
Step-I: First we understand the problems, define the target and plan the optimum solution in the analytics process. Usually E-commerce companies often encounter different issues such as predicting the return of items, giving the client related product recommendations, cancellation of orders, identifying frauds, optimizing the transportation, etc.
Step-II: Next step is to collect transactional business data and customer related information from the previous years to address our problems facing in the business. The previous data can provide us information about the total details that were sold for a product, the sales, the profit that were made, and also provide the information when the order was placed. Previous data always plays a vital role in structuring the future of a business.
Step-III: Next target is to clean the data. All the collected data often is distorted, messy and unwanted missing values. Such kind of data is not fit or relevant for functioning data analytics. So it is required to clean the data properly for the analysis perfectly.
Step-IV: This step is to research and analyze. After the collection of right data, the next step is to execute exploratory data analysis. Now, we can use data visualization and business intelligence tools, data mining techniques and predictive models to analyze, visualize, and predict future outcomes for the collected data. After applying these procedures can tell the impact and relationship of a certain prediction to other variables.
Step-V: After the interpreting the results and drawing meaningful observations from them, the next step is to create visualizations by selecting the most appropriate charts and graphs.
But visualizations aren’t all that are needed here. If we want our valuable findings to be implemented, we need to be able to present it to decision-makers in a manner that’s compelling and easy to comprehend.
If interested, check our more about data analytics.