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 because 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 Preparation

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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 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.

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 and functional format and correct/remove any bad data.

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Altair® Monarch®

Monarch is a market leading desktop-based self-service data preparation solution. Monarch connects to multiple data sources including structured and unstructured data, cloud-based data, and big data. Connecting to data, cleansing and manipulating data requires no coding.

Monarch can quickly convert disparate data formats into rows and columns for use in data analytics. Over 80 pre-built data preparation functions mean data preparation tasks can be completed quickly and error free. More time is spent on generating value from data as opposed to making data usable to begin with.

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