Standardize Your Data

Handling data from multiple sources introduces a unique issue: different variable names. This can make relating tables together difficult and, regardless, time consuming. With Datazoom’s integrated Data Dictionaries, all of your data can be standardized so that time is spent analyzing and assessing, rather than post-processing.

01

Stop Manually Connecting The Same Data Point Across Sources

Get Consistency Across Datasets

In the streaming video technology stack, many vendors collect similar data points. These values can be a way to link the sources together to create relationships that provide real insight. But, in many cases, the same value may be named something different requiring manual post-processing once the data is received. Datazoom’s Data Dictionaries can standardize common values, like bitrate, stall start, stall end, and throughput, so that the same value across multiple datasets is represented with a common name.

02

Use The Same Variable Name Across All Sources

Standardize Example: Bitrate

What's Happening?

Data sources coming from the same endpoint, like a player, may have different names for the same value, such as bitrate. In this case, bitrate could be named Resolution, or video_quality, or bit_rate. Different variable names can make it difficult to relate datasets together when the data is viewed through a visualization tool, requiring manual post-processing. Datazoom’s CDN Data Dictionary and Player Data Dictionaries can provide an automatic standardization of data names and values across datasets speeding up analysis.

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