Data blending is considered an important part of data cleaning and wrangling. Keep reading to learn more about data blending and how it can help your business.
Estimated reading time: 3 minutes
Data blending explained
Data blending includes taking data from one or more source and adding it to a single dataset. For example, if you want to consolidate data from PostgreSQL, Snowflake, and Amazon Redshift to find buying trends on each platform, data blending can help you do this.
Because data from different databases come in unique formats, you have to have a way to standardize all the information accumulated. After the data is standardized, you can load it into a set destination.
The importance of data blending
Today, blending data is more important for businesses because of the need to consolidate information from several sources. When you analyze marketing data (as an example), it may be necessary to gather information from customer surveys, your e-commerce platform, and different social media sites. If the data remains separate, you won’t have a full picture of the emerging trends. This means your perspective is limited and that you will be unable to make informed decisions.
By using data blending, you gain a more complete view of what your customers expect. Keep in mind, though, that it can be used for much more than just sales and marketing. It can also be used for consolidating and reformatting data. Put simply, if you have data coming from two or more sources, this process will benefit your company.
With data blending, it is possible to address a few issues that are encountered when working to combine information. For example, it can help combine unstructured and structured data, provide flexibility, resolve problems, and eliminate duplications.
If you do this properly, this process can be used to recognize any issues that may make it more difficult to process or analyze data. When duplications are removed, users will have a much clearer view of their information and data.
It is beneficial to resolve any collocation issues if users do not know the data’s value in a set. With data blending, the user can review the data as it moves around. This can help your business save a significant amount of money.
The flexibility of data blending makes it possible to process information in a manner that users require. This process may be beneficial for providing the information you can send to a data visualizer for creating graphics. If you don’t have this flexibility level, you may have to take even more steps to complete projects.
When you blend unstructured and structured data, it will be easier for your teams to share important information. This is going to provide for better collaboration, too.
Data blending does have some limitations. Quality platforms will know how to recognize duplicate and corrupted data. It can also help you keep your data organized, allowing you to use it effectively.
Some tools are more effective and efficient than others. It is a good idea to explore all the available options. If possible, request free trials and demos. Knowing exactly how the tool works can help you make informed decisions that will make it easier to complete projects without issues.
While data blending may seem like a complex and difficult issue, it doesn’t have to be. With the information here, you see how this is something that may help your business and processes. While implementing it can take time and effort, it will provide benefits in the long run.
Keep in mind that with data blending, you must learn the processes and understand how to use the process that is used. Being informed and following the evolving trends with these processes will pay off in the long run. Don’t underestimate the benefits of hiring a third-party service provider to help you with this, too.