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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.
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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.
Build fast and reliable data pipelines batch/streaming supporting unstructured and structured data
What do you like best about the product?
Data Governance and Simplified Schema.
Support for unstructured along with structured data enabling support for any use cases to build machine learning, business intelligence, and streaming features. Also support Streaming Live Tables which is a new feature in latest version.
Support for unstructured along with structured data enabling support for any use cases to build machine learning, business intelligence, and streaming features. Also support Streaming Live Tables which is a new feature in latest version.
What do you dislike about the product?
performance benchmark needs to be verified with other competitors like Snowflake. Looks like(as per the documentation) the latest version is blazing fast.
What problems is the product solving and how is that benefiting you?
Unstructured and Structured data in a unified repository to build Machine Learning and BI capabilities.
Recommendations to others considering the product:
How simple to deliver BigData applications. Hassle-free administration and maintenance.
The Future of Data is Databricks Lakehouse!
What do you like best about the product?
Databricks support services needs a special nod, they have come to the table day in and day out with solutions and ideas to better our enterprise environment for any channel we were working with. Also, the support within the platform multi-format data, github support, and an open-source experience are what I love best about the platform.
What do you dislike about the product?
I'd like a better more seamless way to integrate development teams into our environment. This does feel a bit challenging at times with some minor re-work, but I think there could be progress made in this area. Particularly speaking to how you manage workloads for teams with multiple workspaces.
What problems is the product solving and how is that benefiting you?
It's solving many problems but mostly eliminating siloed development environments and centralization of code as a service for global development and product creation. We have in the past had many areas of sources of truth in data and now we are building a more streamlined ecosystem of data services with a centralized solution of truth for Data Opreations.
Data bricks review
What do you like best about the product?
Data bricks Lake House architecture seems promising
What do you dislike about the product?
I don't see much video tutorials. If we have tutorials for free we can learn more
What problems is the product solving and how is that benefiting you?
We are building etl platform where we use data bricks
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