What Is Data Blending?

Data blending is the process of combining data from multiple sources into a functioning dataset.

  • This process is gaining attention among analysts and analytic companies due to the fact that it is a quick and straightforward method used to extract value from multiple data sources.
  • It can help to discover correlations between the different data sets without the time and expense of traditional data warehouse processes.
 Data Blending definition

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Datawatch Monarch

structuring unstructured data

Datawatch Monarch is the industry’s leading solution for self-service data blending.
  • Built for business users not rocket scientists
  • Automatically extract from reports & web pages
  • Combine, clean and use with your favorite tools

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The goals of data blending:
  • Reveal a “deeper intelligence” within your data, by utilizing data from multiple sources
  • Provide accurate, actionable data in the hands of business analysts in a timely matter
  • Drive better decision-making skills by senior leaders in an organization

 The key steps to data blending:

  • Data Acquisition: Identify and obtain access to the data within your sources
  • Joining Data : Combine the edited data for further use and analysis
  • Data Cleansing: Redesign the data into a usable/functional format and correct/remove any bad data

The most prominent environments where data blending is utilized are within sales/marketing, finance operations, and site/merchandising operations. In today’s world it is critical for these business sectors to adopt and integrate tools that will allow their users to visually mash their data so that they will have a competitive edge when it comes to responding to big data flows.

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Want to learn more? Check out these whitepapers:

Gartner Market Guide for Self-Service Data Preparation

Bridge the Gap Between Business Agility and Governance

Extending Self-Service Data Preparation Through Automation
Data Preparation Series - Bridge The Gap Data Preparation Series - Automation