What do you like best about the product?

I really like Databricks Genie, It helps me to identify the error and give suggestions to resolve it.
Also If I ask to imrove the current code to faster performance Genie's suggestion are helpful. It helps to implement the ETL logic in effiecient way.

What do you dislike about the product?

Most of the features which I use are helpful but some sql functionalities are not supported such as Update table using join.

What problems is the product solving and how is that benefiting you?

Switching from on-prem server to Cloud with Databricks are beneficial because of follows:
1. On prem major challenge was it's hard maintain the code version and deployment. Using Databricks it's simpler maintain the versions of code and deploy it on different environment(as it's supports GIT)
2. Easy to scale, We can easily scale up and scale down the cluster configuration which causes cost effiecncy, improve in performance in execution.

What do you like best about the product?

I used Databricks to optimise customer segmentation strategy for a retail campaign. It helped me to analyse millions of records, clean the data and create the ML model based on purchasing behavior. The Delta Lake technology ensured data consistency during the process. Its ability to integrate with our Azure data lake made is easy to access datasets.

What do you dislike about the product?

Tableau integration with Databricks was challenging and I encountered issues while setting up real-time data visualisation. Despite the challenges, the platform enabled me to automate data pipelines, which saved me hours.

What problems is the product solving and how is that benefiting you?

Our operations team used Databricks to monitor and optimse supply chain performance. It has become an essential tool for us to enhance both individual productivity and team collaboration. Its impact can be felt acoss multiple projects.

What do you like best about the product?

My team recently used Databricks to implement a machine learning model for fraud detection. We used the Delta Lake for data preprocessing and insured real time updates from our database. One of the most helpful features in Databricks is the Delta Lake functionality, which ensures data consistency. The platform supports both Python and SQL, which fills the cap between Data engineers and Analysts. This makes it easy for teams to collaborate. Customer support is another highlight as they respond quickly and provide clear guidance.

What do you dislike about the product?

While integrating Databricks with our existing Azure Data Lake, we faced issues syncing access permissions for multiple datasets. Additionally, their pricing models makes it better suited for large organisations, but for smaller teams scaling up can be expensive.

What problems is the product solving and how is that benefiting you?

In recent projects our sales and operation teams needed unified view of supply chain metrics. Using Databricks, we collected data from multiple sources and created a centralised dashboard and enabled real time reporting. This improved our decision making speeed and helped us prevent bottlenecks.

What do you like best about the product?

It has been very amazing in creating data pipelines for data transformation and data analysis + queries easily in dashboard. It is best for data engineers in our company , they use it daily for implementing ML and setting up workflow using Databricks.

What do you dislike about the product?

I think trial period can be bit enhanced for testing this vast platforms. In terms of functionality i see no issues.

What problems is the product solving and how is that benefiting you?

Databricks played big role in warehouse , ML feature with Ai capabilities for managing workflow in team project . Plus it is very helpful in data transformation and analysis which is very much needed.

What do you like best about the product?

I have been using databricks for a more than a year now. It integrates very well with our cloud providers and divides the work in different workspaces from Dev, Test, Pre and Production environment handlings TBs worth of data seamlessly.

What do you dislike about the product?

I think the cluster activation time could be improved. Also it is slow when it comes to fetch data from legacy systems like SQL server.
That takes up a lot of time

What problems is the product solving and how is that benefiting you?

We use databricks as our data warehouse and also as the source that is used by data analysts in the organisation. The intelligence platform helps write code seamlessly and deliver much faster compared. We have reduced the resolve time from 2 weeks to 3-4 days.

What do you like best about the product?

Everything was excellent ,The most important thing was the user friendly

What do you dislike about the product?

Nothing ,every thing was excellent ,No other dislilke

What problems is the product solving and how is that benefiting you?

Unified Data Management
Problem: Managing diverse data types (structured, unstructured, and semi-structured) across different storage systems (data lakes, data warehouses) often leads to silos, complexity, and inefficiency.
Solution: Databricks provides a unified platform for all types of data through Delta Lake, which combines the scalability of data lakes with the performance and governance of data warehouses.
Benefit: You get a single platform to manage both batch and streaming data efficiently, reducing complexity and improving scalability. This simplifies your pipeline and reduces costs by eliminating the need for multiple tools.
2. Collaboration Between Teams
Problem: Data engineers, data scientists, and business analysts often work in silos with different tools, which slows down collaboration and innovation.
Solution: Databricks enables collaborative development with tools like Databricks Notebooks for coding, visualization, and sharing insights in real-time across teams.
Benefit: This improves communication and accelerates the development of data-driven applications, like the music recommendation system you're building, by allowing different teams to work together seamlessly.
3. Scalability and Performance
Problem: Processing large datasets can be slow and resource-intensive with traditional data platforms, leading to performance bottlenecks.
Solution: Databricks leverages Apache Spark to provide high-performance distributed data processing, enabling you to process massive datasets quickly.
Benefit: Faster data processing means quicker insights, helping you manage large data flows more effectively in real-time pipelines like the one you are working on with Databricks.
4. Data Governance and Security
Problem: As data volumes grow, ensuring data quality, compliance, and security becomes challenging, especially in industries with strict regulations.
Solution: Databricks includes comprehensive data governance features, including data lineage tracking, access controls, and auditing capabilities, all integrated within the platform.
Benefit: This makes it easier for you to manage data governance for compliance and audit needs, ensuring secure access to data and making sure your data workflows are compliant with regulations.
5. AI and ML Enablement
Problem: Building and deploying machine learning models often requires specialized tools, which can be hard to integrate with data platforms.
Solution: Databricks integrates directly with tools like MLflow for managing the full ML lifecycle, from model training to deployment.
Benefit: This allows you to integrate machine learning models into your application easily, enabling more advanced analytics and AI-driven features such as emotion-based music recommendations.
6. Real-Time Data Processing
Problem: Many organizations struggle to process and analyze real-time data effectively.
Solution: Databricks supports real-time data streaming, enabling companies to process and analyze data as it arrives.
Benefit: For real-time applications, like the music recommendation system you’re working on, this allows instant processing of data inputs (such as user emotions or age), ensuring timely and relevant recommendations.

What do you like best about the product?

he Databricks Data Intelligence Platform is highly regarded for several reasons:

Unified Data Management: It combines the best features of data lakes and data warehouses into a single platform, known as the Lakehouse. This allows for seamless management of both structured and unstructured data.

Scalability and Performance: The platform is designed to handle large-scale data processing and analytics, making it suitable for enterprises of all sizes. It offers robust scalability and high performance2.
Open Source Integration: Databricks embraces open-source technologies like Apache Spark, Delta Lake, and

What do you dislike about the product?

Cost: Some users find the pricing to be on the higher side, especially for smaller organizations or individual users.

Complexity: Despite its powerful features, the platform can be complex to set up and manage, particularly for those who are new to data engineering and analytics.

What problems is the product solving and how is that benefiting you?

Data Silos: By unifying data lakes and data warehouses into a single Lakehouse architecture, Databricks eliminates data silos. This ensures that all data, whether structured or unstructured, is accessible from one platform.

Scalability Issues: The platform is designed to handle large-scale data processing, making it suitable for enterprises of all sizes.

What do you like best about the product?

What I like best about Databricks is how it brings everything into one place—it makes working with big data and running machine learning tasks easy and fast. Plus, it allows teams to collaborate smoothly, saving time and effort.

What do you dislike about the product?

What I dislike about Databricks is that it can be a bit overwhelming for beginners, and the cost can add up quickly if you're not careful with how you use resources.

What problems is the product solving and how is that benefiting you?

Databricks helps solve the problem of handling large amounts of data by making it easy to analyze, process, and share insights quickly. It's benefiting me by saving time and allowing my team to collaborate more effectively on data projects, all in one platform.

What do you like best about the product?

Ai and ml analytics would be the great tool that would be useful for the etl/elt process

What do you dislike about the product?

Nothing anything is good with the great interface and fast response thank you

What problems is the product solving and how is that benefiting you?

Yes it would be very great to use the tool very easy to use

What do you like best about the product?

Best apllication for data warehousing and machine learning. Their ease to use interface gives a great user experience to work on their platform. Databricks have multiple features and their reliable services make work more easier.

What do you dislike about the product?

I don't have any problem with their services and their tools and fatures are enough for me. They implement exactly what i want and their needful services gives reliable services.

What problems is the product solving and how is that benefiting you?

DataBricks have multiple features like ETL tools, MLOps Platform, Machine learning courses, and data warehouse. We can also use Databricks for big data analysis and solve big query through haddop and Databricks.