Databricks Data Intelligence Platform vs. IBM watsonx.data intelligence

Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.

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The IBM Watson Knowledge Catalog is most well suited for large companies. With large companies storing data for a long amount of time, this can be helpful to allow all team members to find documents with ease. It would be less appropriate for storage that is deleted very often or does not needs to be saved for long amounts of time.

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• 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

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• Data discovery.
• Technical Data Lineage.
• Business Data Lineage.
• Data .
• Multiple Data Catalog Management.
• Creation of Governance Rules.
• Data Masking.

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• Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
• It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
• For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.

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• I think an industry-specific data catalog service will be good.
• Effective alignment of IBM consulting services and bringing in an Industry point of view will be great.
• Effective reach out like roadshows, etc. will be good.

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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

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It is very easy to use and very intuitive Es muy sencilla de utilizar y muy intuitiva

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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.

The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

The IBM Watson Knowledge Catalog is a great amount of storage for the price. It is easily accessed by all users in the company. It provides great search features and clear pathways to locate documents. This is great for the team and our client when needing access to a specific document.

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• 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.

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• The negative note: is that it needs to have a very secure cloud infrastructure and with its data well defined for integration with other databases.
• The positive point: allows for quick data discoveries aiding a quick implementation of privacy programs.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info