The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
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Twilio Segment
Score 8.4 out of 10
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Segment is a customer data platform that helps engineering teams at companies like Tradesy, TIME, Inc., Gap, Lending Tree, PayPal, and Fender, etc., achieve time and cost savings on their data infrastructure, which was acquired by Twilio November 2020. The vendor says they also enable Product, BI, and Marketing teams to access 200+ tools (Mixpanel, Salesforce, Marketo, Redshift, etc.) to better understand and optimize customer preferences for growth— all integrations are pre-built and…
I am over our HR data, and we use Workday for our HR management system. I have a script in place that runs reports on Workday and saves the results as CSVs. I can then use stages in Snowflake to insert these CSVs into Snowflake, then I can insert or truncate and replace these staged tables into a final schema. Then once these are in a schema I can reference them and build out my data models. In addition to ingesting CSVs, Snowflake has the ability to write a CSV file to our Amazon S3 bucket. Ingesting these CSVs, transforming the data, then delivering it to a destination would've involved so much more coding than my current process if we were on any other platform.
Best suited: - Merging emails coming from: Facebook leads forms, Unbounce or landing pages forms, Google forms, any other kind of lead generation tool and bundling all that information together for a single user "profile". - Passing events generated in multiple applications by the same user (product selected in web, product discarded in cart, etc) and delivering those events into other applications (like a CRM) Less appropriate: - Reading/updating data directly from segment from a frontend application
Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
Snowflake manages concurrency better in our trials than other premium competitors
Snowflake has little to no setup and ramp up time
Snowflake offers online training for various employee types
Multi-platform. Segment has easy integrations in many different web, backend, and app platforms/frameworks. We use the Segment SDK in Android and iOS as well as our node.js backend.
Segment is fairly affordable for early-stage companies that are trying out different analytics software. The "developer" plan is free and is suitable for most companies with products that have a small user base.
The UI is great! It is extremely intuitive and easy-to-learn, and this made it take very little time to integrate this software into our analytics and marketing workflows.
This tool is very much technical and proper knowledge is required, so mostly you have to hire an IT team.
I wish if various videos could be available for basic quires like its initiation, then I think it would act as a guideline and would help the beginners a lot.
More and richer sources. For example, MailChimp is a source but the data you get from MailChimp is quite limited. I ended up writing my own scripts to take better advantage of MailChimp's API because Segment's integration was lacking.
Better examples on how to set up event tracking. Pageview tracking is easy enough, but it would be nice if they had a sample app and corresponding code for it and showed you, via Git commits, how to add various kinds of events.
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
The interface is similar to other SQL query systems I've used and is fairly easy to use. My only complaint is the syntax issues. Another thing is that the error messages are not always the easiest thing to understand, especially when you incorporate temp tables. Some of that is to be expected with any new database.
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
Over the period it took us to set up, we kept going back to their enablement team to help us with the setup, and they were always ready and were very helpful in the entire process. Even with their documentation, they took the time out to help us work through the process. We've never had a message/email unanswered for more than an hour on working days.
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
I'm not sure these are "official competitors" (or alternatives) to Segment, but we use them in parallel for different goals. We use Datadog for logging and monitoring and we use Mixpanel to perform data analysis based on the data we gather using Segment (and other sources). I don't think we ever evaluated any other service vs. Segment. I think we got a recommendation on Segment, liked it and decided to use it (and we're happy with it since).
Positive impact: we use Snowflake to track our subscription and payment charges, which we use for internal and investor reporting
Positive impact: 3 times faster query speed compared to Treasure Data means that answers to stakeholders can be delivered quicker by analysts
Positive impact: recommender systems now source their data from Snowflake rather than Spark clusters, improving development speed, and no longer require maintainence of Spark clusters.
Segment has enabled us to get a full view of our front end activity, join it to our back-end activity, and get full visibility into our funnels and user activity.
Segment lets us send events to ad tools with a full audit trail so all the numbers line up.
Segment also brings data from other sources into our data warehouse, saving our data engineering time from building commodity connectors.
