What is Databricks Data Intelligence Platform?
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
85 Likeliness to Recommend
Down
1
Since last award
100 Plan to Renew
80 Satisfaction of Cost Relative to Value
Down
1
Since last award
Emotional Footprint Overview
- Product Experience:
- 95%
- Negotiation and Contract:
- 93%
- Conflict Resolution:
- 93%
- Strategy & Innovation:
- 94%
- Service Experience:
- 95%
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+94 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love Databricks Data Intelligence Platform?
Pros
- Respectful
- Fair
- Transparent
- Reliable
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Data Modelling Tools
Data Integration
Data Access
Data Enrichment
Data Connectors and Data Mashup
Data Cleansing
Data Pre-Processing
Cataloging
Data Profiling
Data Security
Data Mining
Vendor Capability Ratings
Quality of Features
Ease of Data Integration
Ease of Implementation
Product Strategy and Rate of Improvement
Business Value Created
Breadth of Features
Availability and Quality of Training
Usability and Intuitiveness
Ease of Customization
Ease of IT Administration
Vendor Support
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Databricks Data Intelligence Platform Reviews
- Role: Information Technology
- Industry: Technology
- Involvement: End User of Application
Submitted Oct 2022
Facilitate the large data transformation procedure
Likeliness to Recommend
Pros
- Helps Innovate
- Continually Improving Product
- Performance Enhancing
- Enables Productivity
Priyanka J.
- Role: Information Technology
- Industry: Technology
- Involvement: End User of Application
Submitted Oct 2022
Fantastic product for Data Analystics
Likeliness to Recommend
What differentiates Databricks Data Intelligence Platform from other similar products?
It's broad end features
What is your favorite aspect of this product?
Easy to manage, support of multiple language and can be interacted with different Azure services
What do you dislike most about this product?
Nothing specific
What recommendations would you give to someone considering this product?
Go for it
Pros
- Helps Innovate
- Reliable
- Performance Enhancing
- Trustworthy
Lisa-jess B.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Leader or Manager
Submitted Jun 2022
Databricks is a great platform.
Likeliness to Recommend
What differentiates Databricks Data Intelligence Platform from other similar products?
Great expertise that mixes ml-Runtimes – MLFlow and Spark. The flexibility to use Python, and SQL seamlessly in one platform. Since databricks notebooks are saved as python scripts in the background it’s superb to have both notebook and script experience and synchronize to git. Regular jobs, pre-installed ML environments, an abundance of documentation, and example use cases. There are tons of best practices obtainable through the Spark AI conference also.
What is your favorite aspect of this product?
I actually like that we can have queries. We’ve solely began to review them properly for each account, however there are limitless opportunities once we begin digging. It provides multi-cloud support across AWS etc. New options are sharply released every quarter. The UI is comparatively easy compared to AWS EMR or different similar products. The approach that works with the delta format. Providing tons of potentialities without the requirement to own a dedicated database administrator. It’ conjointly nice to talk concerning their flexibility.
What do you dislike most about this product?
Debugging code and using interactive applications outside databricks approved features is tough. It’s difficult to get a grasp of the documentation for beginners to the platform. Their Spark install is not forever compatible with third party tools (ex: geospatial) causing a delay in some package availability till an extra release. Some gotachs with distributed model coaching (Horovod). I’d prefer to access additional access to making queries and investigating many things. Generally, I get glitches with the account, it freezes and I can’t see the data.
What recommendations would you give to someone considering this product?
It’s highly efficient in executing queries, analyzing data, and performing complicated table joins if workloads are properly set up across high-performing clusters. The simplest part is looking for information on a couple of customers’ accounts that we cannot see on the other system we use. Therefore I like to recommend this.
Pros
- Continually Improving Product
- Reliable
- Enables Productivity
- Trustworthy
