What Is Data Blending & Why Does It Matter?

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When data from multiple sources is combined into a single dataset, it’s referred to as “data blending”. It may sound like a simple concept but, in truth, it’s an extremely powerful one.

Thanks to the possibilities that data blending can open up for a business or tech company, the process is beginning to gain more and more attention from analytic companies and analysts alike. It’s quick, it’s straightforward, and it can offer incredible value to a person extracting insights from data.


Why Use Data Blending?

With data blending, a person is able to uncover the correlations that exist between various data sets. There is no longer a need to invest the time or money generally appointed to traditional data warehouse systems.

Some of the key reasons why a business may want to invest in data blending include the ability to:

  • unlock “deeper intelligence” from a business’ data by pulling it in from many different sources and tying it together.
  • get accurate data that forms actionable insights which can be put into a business analyst’s hands in no time.
  • empower those in charge of making decisions with the information they need to make smart choices.


Where Is Data Blending Being Used?

The reality is, any business could benefit from better insights. Therefore any business could also benefit from the data blending process. However, data blending is currently being utilized more prominently in the fields of sales and marketing. It’s also popular within finance operations and even operations relating to merchandising.

These industries, in particular, are faced with increasing demand for integrated tools. There is a greater need for a visual mashing of data. Data blending gives them the competitive advantage when responding to their big data flows. Big data obviously has a huge role to play as industries like these advance, and that’s why six million developers around the world are focusing on big data and advanced analytics.

With that said, data blending is beginning to be more widely used across every industry–and that’s good news. Since some estimates say that 1.7 megabytes of data will be created for every person in the world, every second of every day, by the year 2020, data blending and other tactics will prove essential for processing, managing, and understanding the growing amount of information out there.


How To Use Data Blending

Countless tools are now emerging that are enabling small businesses and tech startups alike to begin taking advantage of the data blending process. Most of these tools are designed to be easy to use and intuitive for even non-tech people, with automated extraction and report creation available.

At its core, the process of data blending requires a few key steps regardless of the tool a person chooses to use.

  1. Data Acquisition: The process always begins with data acquisition, which is the face where a business identifies the data they want to access and then works to obtain access to it through various sources.
  2. Joining Data: The next step is joining data where the edited data is combined for further analysis.
  3. Data Cleaning: The third step is data cleaning, which is when the data is redesigned into a functional format. Bad data is removed or corrected during this step.

As experts have said in the past, businesses don’t lack information, they simply lack the ability to efficiently process that information. Technology like data blending helps to unlock it.

Looking to get started with your own data blending? Data Studios has you covered: