Unifying Data – Connecting the Data Dots

Analytics tools provide the ability to explore users’ behavioral patterns, such as where they click and when, what they did before or after a specific event and how long they spent on a particular screen or step.

But analyzing behavioral data alone is not good enough anymore. Data is collected from a variety of sources and organizations manage data on several databases simultaneously. One system collects behavioral data, a second collects campaign data, a third may store financial interactions and so on.

Looking solely at event data just does not tell the full picture any more. Only a truly unified view can provide analysts with a comprehensive understanding of user behavioral patterns.

Why is Unified Analysis Important?

Let’s look at an ROI example based on ad network data example to determine how businesses can best utilize unified data. We can assume a marketing manager is looking to optimize campaign spending. Examining data from the ad network presents the following view:<

[table id=60 /]

We can clearly see that Campaign ID c33135 is performing better than the others. So as a marketing manager, we will naturally tend to spend more money on that campaign.

However, analytics usage data tells a very different story. Let’s assume that a product manager wants to analyze revenues per traffic source. This manager looks at the same three campaigns illustrated in the previous example. The resulting data appears in the table and chart below:

[table id=61 /]

Here we can see that Campaign ID c9249 performed better than the others.

Only a unified view that looks at both spending and revenue can provide a comprehensive picture:

In the yellow highlighted section above, we see ad network data. In the green section we see application revenue data. The blue section details unified ROI data. This is a whole new picture and our conclusions change dramatically. Here the most cost-effective campaign is c48205. We simply would not have been able to get conclusions like this without the power of unified data.<

How to Benefit from Unified Behavioral Analytics

At CoolaData, we understand that data can be stored in different ways. In order to drive comprehensive conclusions, analysts must have quick access to their data sources.

CoolaData is a unified behavioral analytics platform that stores data regarding behavioral patterns and the flows that users take in consumer-facing websites and apps. We also enable the unification of behavioral data with data from external data sources.

The following are some good tips for how to unify data with CoolaData:

CoolaData’s “from” Clause

When querying behavioral data stored on CoolaData, we enable analysts four choices for using the ‘from’ clause:

  1. from cooladata – This is the default. Here CoolaData’s back-end receives the query and looks for the optimum database, table, or view to run this query. It will generally provide the best results in the shortest timeframe.
  2. from events – This directs the query to run directly over the events view – CoolaData’s basic collection of user actions.
  3. from session – This directs the query to run over an aggregation of users’ behavioral sessions. It is an aggregation of all the events together with some great counters, such as the number of events per session and session duration.
  4. from external – This enables running the query over any external data source that provides CoolaData the ability to connect to MySQL, Redshift, Big Query, and many others.

 

Fusion – Client Side Data Unification

CoolaData’s Fusion widget is another tool that enables analysts to easily unify results data from two (or more) data sources. Once data from the two data sources is fuzed, analysts can pivot it and further manipulate it on the client side.

Server Side Join

CoolaData’s server side join allows us to unify data in a query. With server side join, analysts can upload satellite lookup tables to our behavioral data store and then join them with data already stored there, while entering freehand CQL.

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