TitanHQ Automates Data Analytics Pipeline to Get a 360-Degree Customer View Using Skyvia Data Integration

TitanHQ is a leading SaaS Cybersecurity Platform delivering a layered security solution to prevent user data vulnerability.



Data Integration


The toolset of TitanHQ consisted of Redshift data warehouse, SugarCRM, Tableau BI tool, Chargify payment processor and a ticketing platform. The customer data was siloed in the apps and there was a need to build a data analytics pipeline to get a 360 degrees customer view:

Management team wanted to get greater insights and align them with business goals by combining the data from these tools. For example, customer retention is a very important metric for the company here. The data needed to be combined from the CRM platform, Chargify, ticketing platform and from our products themselves to kind of help the customer success team measure their retention percentages, and maybe to create some kind of indicators of potential churn within customer accounts.

John McPhillips

Senior Data|BI Engineer

The first real challenge that the data engineering team faced was how to optimize time for writing Python scripts for data extraction in order to spend more time on creating reports in Tableau and doing other BI tasks as well.

TitanHQ’s engineering team also found that Redshift was not a perfect solution for them because of its cost and SQL capabilities.


First of all, TitanHQ moved from Amazon Redshift to Snowflake, because of its flexibility, powerful computing capabilities, and a fully fledged SQL support:

Snowflake has a lot of advantages over Redshift. You can scale compute and storage separately, and it fits our data model, because we're loading a data warehouse in a batch mode. We could leverage the Snowflake model to keep our costs down. I also like that Snowflake can coalesce out of the box, or convert array type structures to separate fields and things like that you just can't really do in Redshift.

John McPhillips

Senior Data|BI Engineer

After Snowflake was set up, the data pipeline looked this way: customers’ data was to be moved from SugarCRM to Snowflake, and then – to Tableau for reporting. The challenge was to automate data extraction from SugarCRM, Chargify, and the ticketing system to Snowflake, and the TitanHQ data engineering team started to look out for solutions. John compared multiple solutions, including Fietran, and at the end chose Skyvia as the best one for company needs.

I assessed Skyvia and Fivetran over maybe the course of four weeks, and I decided that the Skyvia team identified a good gap in the market. Because for me, a lot of the current tools are very restrictive, and Skyvia gives a lot more freedom to customize your data extraction process.

John McPhillips

Senior Data|BI Engineer


The key result of Skyvia implementation was that data integration from SugarCRM to Snowflake data warehouse was automated, which saved time and costs for writing custom data integration scripts manually and supporting them by the internal engineering team. TitanHQ’s customer success team received regularly updated reporting dashboards with an upwards trends for all important metrics:

I definitely think that Skyvia has very good flexibility. It can do simple data exports or do things that are more complicated, which I've seen only in enterprise level tools and not for the price point that you guys are offering. So I think it's very impressive. If I had to sum it up, I would say the capabilities of the tool for the price points that you're offering is desperately unique in that space.

John McPhillips

Senior Data|BI Engineer

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