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Very friendly with Jupyter users.
What do you like best about the product?
Data Engineer & Machine Learning is very easy to use.
What do you dislike about the product?
It takes time to start a job cluster so I must create a cluster for live update dashboard.
What problems is the product solving and how is that benefiting you?
Schedule ETL jobs.
Many teams can use with different programming languages.
Many teams can use with different programming languages.
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Great product
What do you like best about the product?
Integarted UI for SQL , Spark , Python . This makes the job really seamless
What do you dislike about the product?
Nothing as of now . Enjoying the product
What problems is the product solving and how is that benefiting you?
We can leverage the concept of delta lake for our use cases
It's really useful for big datasets
What do you like best about the product?
Lesser Running time, handling big datsets, user-friendly platform
What do you dislike about the product?
Cluster active time is less, active time should be increased when not in use
What problems is the product solving and how is that benefiting you?
Helps in Data Warehousing on big datasets, building data engineering pipeline and ML models end to end
Make process easy for big data transformation
What do you like best about the product?
It's stores data in delta lake that basically helps to generate a backup of data doesn't matter if process failed every time it took cache of data and most importantly we can easily migrate it with any cloud platform to handle big data.
What do you dislike about the product?
For dislike I would say some time cluster takes time to run and it gives memory error and it's bit costly in use and sometime notebooks cells stuck in between run so team can work on it bit.
What problems is the product solving and how is that benefiting you?
I use it mainly in azure dala lake connection it can easily connect with storage and by applying transformation we can easily push tha data. Most important I use pyspark and sql spark in one notebook meaning we can write script whatever language we want. I use it for etl flow by connecting with azure data factory.
Databricks lakehouse
What do you like best about the product?
Everything is on a single platform like ETL, Sql dashboard and running ML models.
Simplied version for creating scheduled jobs using workshops and the best part is Delta Lake.
Simplied version for creating scheduled jobs using workshops and the best part is Delta Lake.
What do you dislike about the product?
Every piece of code should be in the form of notebooks which sometimes makes it difficult to manage. It can be more user friendly if they give different options.
What problems is the product solving and how is that benefiting you?
Time travel feature allows to version database instead of keeping redundant or replicas. This has optimized both in terms of human efforts and cost.
Lakehouse is the Marriage of cloud based DW and Data Lake
What do you like best about the product?
It is a cloud native modern data estate service which handles core DW concepts around competing with snowflake and delta live table schema requirements like CDC like a champ
What do you dislike about the product?
Lakehouses are great but not the answer to everything when it comes to all the needs of cloud scale analytics and AI
What problems is the product solving and how is that benefiting you?
Lakehouse model enables you to work in a truly unified architectyou are that provides highly performant and structured streaming capabilities, and most importantly for me, data science, machine learning and Visualization capabilities.
Databricks Lakehouse is one shop stop any bigdata analytics
What do you like best about the product?
Databricks lakehouse is one shop stop for analytics with Big data case
What do you dislike about the product?
Databricks have many releases one going and that might create a need for customer to constantly updates there infrastructure
What problems is the product solving and how is that benefiting you?
It helps optimise Spark engine by building a wrapper compute on Spark cluster and this help run huge volume based queries much faster
One Stop Shop for Data Engineers
What do you like best about the product?
One platform to access Notebooks, tables, AI/Ml Platform
What do you dislike about the product?
No debugger like other IDE's, difficult to navigate notebooks and functions
What problems is the product solving and how is that benefiting you?
Formed Datalake to reduce efforts and time for internal teams
Best conference in data and analytics now
What do you like best about the product?
The extensive detailed content that is not shy from being deeply technical and in the same time industry-focused to depth. The amount of information covered here is incredible from data & analytics to GPUs to K8s to industry discussions
What do you dislike about the product?
there is no on-demand hands-on labs. and we cannot download all slides for all sessions. The timing of the sessions was also a challenge.
I didn't like the scheduling features too.
I didn't like the scheduling features too.
What problems is the product solving and how is that benefiting you?
Mainly it solves the ability to ask questions against the data regardless of their nature (streaming and batch); without the need to move the data around to other platforms etc.
Recommendations to others considering the product:
Follow the guidance
Fantastic Data Engineering and Data Science platform
What do you like best about the product?
Best Data Engineering features. Love it.
What do you dislike about the product?
Very expensive. Wish it would cost less.
What problems is the product solving and how is that benefiting you?
It is solving data ingestion problems and dataset preparation problems. This is benefitting me by making automated Data Engineering easy to implement by myself.
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