Table of Contents
· 4 Types of Data Analytics that Prove Useful in Decision-Making
· Wrap up
Data is a highly valuable tool that when used properly helps entrepreneurs and stakeholders to make better decisions. Once you store data in a secured cloud platform, the next step is to perform some analysis. Even when you archive your data in sharearchive, you can employ some advanced analytics tools to get some valuable insight. Today, I am going to unlock details about 4 types of data analysis that prove quite useful in your business decision. Before I uncover these types, you must know: cloud archiving solutions
What Is Data Analytics?
It is a practice where data is examined with the means of different tools and techniques to get some answers to common questions, obtain valuable insight, and identify industry trends. file server archiving solution
Different kinds of software, tools, and frameworks can be used for data analytics such as Infogram, Sharearchiver, Zoho Analytics, Microsoft Excel, Google Chart, Data Wrapper, etc rpo rto disaster recovery
These days organizations have to deal with a large volume of data every day, thereby advanced techniques such as Artificial Intelligence and machine learning help your organization to gather, sort and analyze data at speed. archive storage solutions
Who Needs Data Analytics?
Now the next question in your mind is about the usage of data analytics or a better question is who needs this analysis. Well, there are different users of a data analytic report. archiving solutions
· Marketers
· Product Manager
· HR Manager
· Finance Professionals
Marketers
These professionals run campaigns and gather some data about these campaigns. Once analysis is performed on the data, they get some information based on which they set up the next marketing campaign. file archiving software
For example, a marketer employed traditional marketing tactics like brochures and coupons to promote a market. The brochure didn’t bring any good results but customers get attracted to your business through coupons. Now you have proper data like how many customers respond to two marketing techniques. Since one doesn’t work out, you can spend more on effective techniques to get more results.
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Product Manager
A product manager relies on data analytics to bring improvement in products or to introduce better products to win more customer base.
HR Manager
HR managers rely on data analytics to decide which employee works better and who needs management attention and guidance. Data helps them gain insight into employee behaviour, productivity level, motivation, and other aspects.
Finance Professionals
They need data analytics to predict and understand the future financial performance of a company based on available data.
4 Types Of Data Analytics That Prove Useful In Decision-Making
It’s time to get an idea about 4 different types of data analytics that help you make better decisions
· Descriptive Analytics
· Diagnostic Analytics
· Predictive Analytics
· Prescriptive analytics
1-Descriptive Analytics
It’s a type of analysis where you understand what has happened in your business and what’s happening. You can pull trends from raw data available through this analysis. When you store all your data in Share Archiver’s cloud storage, you can easily perform this basic analysis on your current and archived data. This software also provides data visualization features.
As a result, you can easily spot trends in data such as dips and spikes through charts, graphics, and maps. Getting an understanding of your business data becomes simple and easy through this sharearchiver.
2-Diagnostic Analytics
Whenever you are looking for an answer to this question- “Why did it happen?” then certainly you need to perform diagnostic analysis on the data. This analysis is one step advanced to basic analysis. It will help you look into different trends, compare them, and discover correlations between different variables.
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For example, you notice that your makeup products are high in demand in specific seasons and high in demand during specific months. Once you perform diagnostic analytics, it will help you understand that people purchase more makeup products during holidays and wedding season while they skip them during summer. The reason for the high demand is that they present these products as a gift. Some other motivator behind the purchase pattern also comes to the surface after analysis.
Once you have this valuable information, you can double-digit your sales by offering a discount at a time when people don’t shop much. This discount will motivate them to buy more.
3-Predictive Analytics
When you don’t have data analytics on your side, you make a wild guess that sales will increase in the upcoming season. However, when you have data analytics tools, you can predict what will happen next or in future.
For example, you compare trends of a certain product from year to year. You check the sales trends of a product in the market as well. After comparing and correlating these trends, you can easily predict whether sales of a certain product will go up or down in a specific season.
4-Prescriptive Analytics
You have a certain volume of data in hand and now you are wondering what should be my next course of action or strategies. Well, in that case, you need to make the most of prescriptive analysis. This type of analysis helps you create data-driven decisions and strategies.
For example, you can run a split A/B marketing test. Where you try two different marketing strategies on a specific location. Now results from these strategies will help you understand whether to continue with marketing strategy A or B. So, you decide everything based on valuable insight based on testing data.
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Wrap Up
Finally, you understand everything about four different types of data analytics. When you want to know what’s happening in your business, you can simply rely on Sharearchiver’s data analytics tool as it will help you understand better through data visualization. But when you need to predict the future or define the next course of action, predictive and prescriptive data analytics tools, especially machine learning and AI algorithms, come in handy.