Databricks Data Intelligence Platform vs. Mode Analytics

If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.

Incentivized

After launching a new contact pathway in a help experience, Mode Analytics can help provide insight into the sentiments from users as well as the engagement with any written content. Numeric outputs are easier to manage, whereas more nuanced/emotional feedback is sometimes hard to quantify (though not impossible if you get creative).

Incentivized

• There is databricks community, which is a free version. It is available for beginners to have an easy start with a big data platform. It does not have every feature of the full version but is still adequate for extremely new coders.
• There are many resourceful training elements that are available to developers, data scientists, data engineers and other IT professionals to learn Apache Spark.

Incentivized

• Easy to use (click a button and get right to SQL).
• Security First (everything is locked down by default).
• The White Label feature is super easy to skin -- our embedded reports look just like our app!

Incentivized

• Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
• Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
• Visualization in MLFLOW experiment can be enhanced

Incentivized

• Date ranges aren't always the most intuitive to set, strangely
• Faster refresh rates would be ideal
• Would love more dynamic mobile device integration (alerts, etc)

Incentivized

Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX

Incentivized

For the advanced user already familiar with Python. It is just the same tool, already managed and connected to the data.

Incentivized

One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.

Mode has dedicated agents who are online in a chatroom, ready to take on any questions and provide helpful feedback.

Incentivized

Databricks is a true all-in-one platform, and at the time of implementation, it had more features available to us, making it a clear choice over Snowflake. Moving our workloads from local computing to the servers in Databricks gave our start-up staff a great quality of life boost.

Incentivized

• Tableau is a huge pain to edit or create dashboards, by comparison. It can make better looking visualizations, but in practice, letting users drill down and change dimensions slows the end user experience so much that it's often not worth it.
• Looker is amazing for data modeling, but you have to get your whole business all in on it to take advantage. Viz capabilities are similar.
• Databricks has a lot of functionality overlap, but the visualizations are terrible. Databricks' great strength is that you can use notebooks to do anything with code.

Incentivized

• ROI for us has been tremendous. Time to market by processing raw data in our big data infrastructure has been pretty fast.
• Non engineers can easily use Databricks, hence helping business customers.
• Thousands of different data combinations can easily be joined and used by our data teams.

Incentivized

• It has allowed us to monitor ongoing financial transactions written to our SQL data tables in real-time and that helps us to monitor user transaction activities in real-time
• Using Mode we have been able to also track users who undertake fraudulent financial transactions; preventing financial losses to our users
• Mode's collaborative abilities have been very helpful in sharing transaction monitoring workload across our compliance and cybersecurity team

Incentivized