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Did you know that disorganized data is a problem for 95% of businesses?
A large number of businesses, big and small, fail within the first year. This is a problem made worse by disorganized data.
This issue can be fixed by analyzing data effectively.
If you’re a product manager or business owner looking to dust up on your data analysis, this article is for you, so keep reading.
Contents
1. Visualize Your Data
The human brain can process images in 13 milliseconds. This means that data visualization can be a powerful tool in conveying your dataset. It will allow viewers to take in your data at a glance.
This means analysts can understand and organize data more efficiently. This gives your business more time to implement the results of your data, making operational changes smoother.
It also allows employees to better understand the internal workings of the business.
One way to visualize your data is to use a business intelligence reporting tool such as Qlik view or Qlik sense or Tableau. Tableau is a data visualization tool that can create interactive graphs, charts, and maps. It allows you to connect to different data sources and create visualizations in minutes. Learning Tableau takes time and practice, but there are plenty of resources and Tableau Training out there to help you learn how to use it. As a data scientist, Tableau has to be the number one tool to learn and use in your everyday tasks.
2. Clean Your Data
Before analyzing data it should first be cleaned up. You should remove any outliers, anomalous data fluctuations, and duplicates.
Using inconsistent datasets could lead to your analysis being incorrect and misleading. Taking action based on incorrect data analysis could cause problems for your business.
Although it can be time-consuming, cleaning up your data could save you money and time in the long run.
3. Define Your Goals
From product usage data to CTR, It’s important to understand why you’re analyzing your data. If you don’t have a clear purpose, you could analyze the wrong data and waste valuable time.
Defining an understandable goal will help your analysts to present the data in the right way. This will make your data more accessible to employees across departments. Thus creating cohesion across the board.
As a result, departments will be able to better work together to achieve the business’s goals.
4. Segment Your Data
Dividing your data into segments will allow you to keep your data organized. It will make it more digestible to analysts and employees, making the analysis process smoother.
For example, you may want to separate your digital marketing data from your financial dataset.
This would allow your analysts to focus on one segment at a time. Thus generating a more in-depth and personalized report.
5. Choose a Method for Analyzing Data
When analyzing data, it is important to choose the right analysis method for you. This can help you to achieve your defined goals. There are several methods to consider.
Descriptive Analysis
This method is used to help analysts describe a set of data, thus making them more understandable.
Exploratory Analysis
This method is used to explore data. It helps to uncover correlations that were otherwise unknown.
Predictive Analysis
This method is used to predict future data. It uses historical and present correlations to estimate future outcomes.
Now You’re Ready to Analyze Your Data
After reading these 5 tips for analyzing data, you should have a better understanding of data analysis.
Now you’re ready to analyze your data the right way.
If you found this article helpful, make sure to check out the rest of our content for more.
