Databricks Data Intelligence Platform vs. Informatica MDM & 360 Applications

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

Informatica MDM is a complete MDM solution, from ingestion to data exposition. This tool helps us in gathering customer data, and also it makes it possible for us to support our customers relationships and build customer-related strategies to improve their experience which helps to drive sales geometry and growth and customers satisfaction. On the other hand of price is relatively competitive.

Incentivized

• Process raw data in One Lake (S3) env to relational tables and views
• Share notebooks with our business analysts so that they can use the queries and generate value out of the data
• Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
• Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers

Incentivized

• This program raises us to a professional level where we have better versatility to control all the media of my work and have a correct response for each scenario.
• It is essential to be right about the destination and development of my data, Informatica MDM is here to simplify all these processes for its users.

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

• It is unfortunate how this program has a couple of limitations in terms of insertions; it does not have the ability to agglomerate and archive the data in real-time by groups.
• To have automation functions, the program is very limited in performing one task at a time, compared to other systems that perform functions simultaneously.

Incentivized

Supporting well in managing our huge customer base and managing the customer hierarchies well aligned with transactional processes

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

Strong Customer MDM capabilities for de-duplication, merging, golden record, exposing customer master data. Strong Integration capabilities

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.

I'm not sure since I never used support. My colleagues never had any issues with it, therefore my rating would be an 8 with a certain range of uncertainty.

The integrator did a fair job and even though Business Change Management was complex, it was well concluded on time

Incentivized

Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same time while Synapse and Snowflake feel more limited in terms of configuration and connectivity to external tools.

Informatica MDM has proven it's worth in the organization by driving the revenue growth. It saves our lot of time by filtering out duplicate values and helps in solving critical business problems. It is very helpful when we deal with a lot of data. Apart from this we can populate data on various third party integration which is most useful case

Incentivized

• The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
• DB has the ability to terminate/time out instances which helps manage cost.
• The ability to quickly access typical hard to build data scenarios easily is a strength.

Incentivized

• I cannot speak to this for 2 reasons. 1. I am not privy to the financials associated with this implementation or the previous one. 2. We have not hit our 'go-live' for this implementation yet to compare it's performance to our previous solution.

Incentivized