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Real time Data Power Tool.
What do you like best about the product?
Team collaboration feature is the liked feature in this tool which helps to collaborate with collogues, security and compliance are robust in Databricks. This support open Lakehouse architecture.for unified storage.
What do you dislike about the product?
The manual tunneling option are limited in this , not suitable for beginners.
What problems is the product solving and how is that benefiting you?
for dicovering assets using smart search we using this tool , it is very efficient.
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Unified Analystics and AI platform
What do you like best about the product?
The processing ability to process data at scale is accurate , and can be integrated with many software ,Databricks is highly reliable and very easy to use, Easy integrated with BI tool also
What do you dislike about the product?
High cost for beginners , need low tier plan for beginners.
What problems is the product solving and how is that benefiting you?
we use this data analytics and data governance and Ai model development ,Databricks Data intelligence is extraordinary.
Databricks make enterprise scale ML project easier to manage.
What do you like best about the product?
We have build a fraud detection system for a European finntech product using Databricks Data Intelligence Platform. The project required ingesting large volume of transaction data, cleaning it and training multiple machine, learning models using historical fraud patterns. Feature like tight integration with ML flow, alone helped us avoid the usual mess of managing models across Juypter notebooks and cloud storage. It’s collaborative environment allowed our ML engineers and data scientists to work together in Databricks notebooks in the same interface. Additionally, the ability to schedule retraining jobs made it easier to put a model into production with minimum effort.
What do you dislike about the product?
While MLflow is great, the UI for comparing runs can feel a bit outdated and lacks advanced filtering options. Managing features stores also felt slightly inefficient without more granular access control for different user roles.
What problems is the product solving and how is that benefiting you?
Our ML pipeline is far more stable and efficient after we implemented Databricks. We have a standardised our development workflows and now our engineers, analyst and business teams can access the same datasets and results in a single environment. This has dramatically improved our team collaboration.
Amazing Platform for Big Data Analysis and Data Management
What do you like best about the product?
One of the best Data management platform, I really like their ease to use integration and predefine templates that help a lot on data analytics without and efforts.
What do you dislike about the product?
I really like their services and their affordability and customer support always provide hassle free services.
What problems is the product solving and how is that benefiting you?
Mainly we are using Databricks only for Data analytics and data warehousing and both our work completing on time without any hassle and their user friendly infrastructure gives hassle free services that make our work more ease to use and best for our data management.
Highly scalable and developer friendly data solution.
What do you like best about the product?
I used the Databricks Data Intelligence Platform to build a real-time vehicle processing pipeline for a client in the logistics sector. The project involved collecting sensor data from hundreds of delivery trucks and processing it to detect anomalies and trigger alerts in real time. What I like best was how easily Databricks integrated with Azure Event Hubs because it allows me to stream data in and start processing instantly. I also used Delta Lake for storing clean data, which became the foundation of our analytic dashboard. Additionally, the Databricks rest API allowed us to trigger jobs from our monitoring systems, which enhances the automation to a great extend.
What do you dislike about the product?
Although the product is powerful, the learning curve for structured streaming was quite steep for new team members. I also encountered some integration limitations while sending alerts directly to external APIa from within notebooks. But we found workaround which involves using Azure Functions outside Databricks, which added some extra complexity.
What problems is the product solving and how is that benefiting you?
It has a major impact on our team’s productivity. Previously, our data engineers, cloud, architecture and analytic team worked on different tools which leads to delay and communication gaps. Now, with Databricks as the central platform, we collaborate in real time and debug issues together in shared notebooks.
Faster processing and scalability
What do you like best about the product?
It's a flexible solution that works well, it's designed to distribute data. It can easily scale to handle large amounts of data and offers numerous high-level features. I like the replication features.
What do you dislike about the product?
It could be better if there was a more optimized user interface, it can introduce relatively high latency for operations with small files.
What problems is the product solving and how is that benefiting you?
It helps process larger files in a shorter period of time and supports various resources manager and engines. This product is renowned for its reliability and meets the need to process large amounts of data.
Great advanced analytical tool that utilises Spark to fullest
What do you like best about the product?
Its ability to combine big data processing with machine learning makes it possible to do advanced analytics and data engineering efficiently in one space. Its scalable design and collaborative workspace also make it simple for teams to work together and process large datasets without slowing down the system
What do you dislike about the product?
One downside of the Databricks Data Intelligence Platform is the steep learning curve for new users, especially when navigating complex features like Delta Lake and managing large-scale workloads
What problems is the product solving and how is that benefiting you?
It provides a unified environment for analytics, machine learning, and data engineering, addressing issues like managing massive datasets, scaling machine learning models and enables team collaboration. While collaborative notebooks improve teamwork, increasing productivity and speeding the implementation of data-driven solutions, its interaction with Apache Spark and Delta Lake guarantees effective data processing, consistency, and version control.
Why Databricks Data Intelligence Platform?
What do you like best about the product?
Databricks simplifies big data processing with AI-powered analytics, seamless integration, and collaborative workspaces, making data-driven decisions faster and more efficient. Implementation is smooth, and customer support is helpful.
What do you dislike about the product?
Databricks is great, but the cost can escalate quickly, especially with high workloads and auto-scaling.
What problems is the product solving and how is that benefiting you?
Databricks makes working with data easier by combining analytics, AI, and storage in one place. It helps teams work faster, automate tasks, and get insights quickly—saving time and effort.
Game changer
What do you like best about the product?
This lake house architecture brings the best of both data lakes and warehouses , so we don't have to deal with the unnecessary complexity. Delta lakes ensures reliability while the notebook based interface makes collaboration seamless. The platform ability to handle batch, streaming, and machine learning workloads in one place is a huge advantage.
What do you dislike about the product?
The pricing can get expensive, especially if workloads aren't optimized properly, also while the notebooks are great they could use better version control for collaborative work . the initial learning curve can be a bit steep for those new to spark but once you get the hang of it. It is powerful tool
What problems is the product solving and how is that benefiting you?
Databricks simplifies big data processing by providing a unified platform for batch and streaming workloads. It eliminates the complexity of managing infrastructure, ensuring scalability and performance without much manual effort . The collaborative notebooks make it easy to work with items and delta Lake improves data reliability. overall it saves a lot of time and effort in managing data workloads
Easy to use, easy to access support system, unified lakehouse architecture and timely new features.
What do you like best about the product?
Flexibility of using languages like Python, Pyspark and SQL. New file arriving feature. variety of options to connect with almost all kind of source. Very simple implementation of unity catalog which was hard to manage initially. Volumn that works seamless with python/pandas code.
What do you dislike about the product?
Databricks diagnose error suggestion. Failed to provide queries for like mail attachment extraction, AES 256 encrypt code etc. Very good for support in python, pyspark and SQL code but not in rare usecase like mentioned above.
What problems is the product solving and how is that benefiting you?
Complex logic and Expensive processing, Unified batch and stream processing, data governance by unity catalog, use of separate BI tool etc.
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