Data Blending

What is Data Blending?

Data Blending is the process of combining data from multiple sources into one useful dataset that can be processed, visualized in a dashboard, and then analyzed. It allows combining the data to mine for facts or correlations from disparate sources such as databases, spreadsheets, web analytics, social media, and cloud applications, among others.


Why is Data Blending important?

The data from disparate data sources are multiplying at a dizzying rate, and the time spent by data scientists and data analysts on preparing the data for analysis set to skyrocket. To escape this cycle of collect-> clean-> collect, data blending is used. It speeds up the consumption of the data without involving data scientists or other specialists. It blends the data from multiple sources and reveals important insights. Data blending tools give non-technical users rapid results in multiple areas and lead to faster, more data-driven decision-making.


What are the ways to blend the data?

The basic steps to blend the data are:

  • Acquire- Acquire the data from disparate sources such as databases, spreadsheets, social media, pdfs, etc.
  • Join-Combine the data and merge it into a single table via relationships across the multiple tables.
  • Clean-Clean the missed or incorrect data and redesign the remaining data into a usable format.
  • Analyze-Data blending query each data source separately, present the results in a visualization, and then analyze the results.

Opportunities for AI in Telecommunication

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