Data Blending

What is Data Blending?

Data blending is combining multiple data sources to create a single, new dataset, which can be presented visually in a dashboard or other visualization, and can then be processed or analyzed.

Enterprises get their data from a variety of sources, and users may want to temporarily bring together different datasets to compare data relationships or answer a specific question.

Data blending tools let them “mash up” data from spreadsheets, web analytics, business systems, and cloud applications, among others

Basic steps for blending data?

Setting up your data blending operation can be complex. Let’s break it down into manageable chunks.

First, collect your data. You may have to collect the information you need from diverse sources like Excel spreadsheets, cloud and non-cloud databases, Google analytics, or social media tracking apps. Plan ahead, because it may take time to get the relevant access and permissions for everything.

Then, it’s time to join the data. Here’s where a BI platform like Sisense really comes in handy. Combine your sources and load it into a destination, like a data warehouse, where it will be accessible by everyone who needs to look at it.

Finally, clean and refine your data. Remove what is incomplete or incorrect, and modify the rest so it is properly formatted, and optimized for the best and most accurate analysis.

Ways to combine data?

If you want to create charts, reports, and visualizations based on two or more sources, you’ll have to blend your data. You have a few different options of how to do this.

The most common data combining method is via relationships. Using relationships, you can join data across multiple tables, making it the most flexible and dynamic way to combine data sources. This is also the easiest and most intuitive method.

Joins are another available option for combining your data. Joining tables means physically defining the data and merging it into one single table. You can use a Venn diagram to display your data joins. This method is best suited for data combinations that can use a single table, like row-level security and extract filters.

If you want to analyze data from already published sources, the best method to use is the data blend. Blends individually query each data source separately and present the results in a visualization. The data sources are never physically joined. This makes sense if your tables have different level of detail, or if the data needs cleaning.

Better Data Blending?

More capable data blending tools can make it easy to combine data, while retaining the details of each data element. Logical connections between the elements can also be maintained.

Users can then explore data on the fly and make new calculations for more insights. They can ask new questions of their data as they want, without depending on their IT department to do more complex database integrations.