Databricks Data Intelligence Platform

What do you like best about the product?

I like being able to integrate PySpark and natural language processing (NLP) models into a single workflow. It lets me query historical records with very high performance using SQL, while also running Python scripts to group results by keywords.

What do you dislike about the product?

Computing costs can be high, and cluster management expenses can escalate quickly if you don’t keep tight control over autoscaling and idle time.

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

I use it extensively for analytical processing and optimization, specifically for response methods and websites that have a large number of URLs tied to a complex e-commerce platform. This includes processing crawl data, JavaScript rendering, and AI bot logs. By combining these elements with the capabilities of traditional SEO tools and Databricks, we’re able to handle massive volumes of data and analyze indexing patterns in real time.

What do you like best about the product?

I like that Databricks lets me consolidate all our information in a lakehouse architecture in a clean and efficient way. I can create models and automated alerts for discrepancies in taxes, duties paid, or expired permits, which enables us to maintain a proactive approach to compliance. It replaces massive Excel files and manual processes with automated data models that cross-reference customs declarations with internal accounting records. The initial setup was easy.

What do you dislike about the product?

I would like Databricks to have more no-code templates or preconfigured native dashboards for business and regulatory compliance users.

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

I use Databricks to replace massive Excel files and manual processes with automated data models that cross-reference customs declarations against internal accounting records.

What do you like best about the product?

The best thing I like about Databricks is its overall end-to-end experience which makes it different from the other solutions. As a project manager, we had used Databricks in our organization for almost 3 years. In those 3 years, we have used it for its unified data lake for data warehouse. Also, it has helped us to reduce the time to market for our projects by almost 45%. With its unified environment, it has helped our teams to reduce friction and to move at a faster pace.

What do you dislike about the product?

There are no particular things that I dislike, but they may improve on auto-scaling compute since it can get small companies in trouble as it may create a budget overhead. Also, it is a code-heavy platform, which also means that non-tech users can't use it much.

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

It has helped us in environment unification which helped our teams collaborate better and achieve goals at a 50% faster pace. Secondly, due to its seamless UI and integrations within our systems, we have eliminated working in silos and minimized technical blockers.

What do you like best about the product?

I use Databricks to run ingestion, transformation, and reconciliation pipelines for several clients’ data on one platform, and to prepare feature tables for fraud detection. The setup was smoother than I expected: my workspaces, cluster policies, and Unity Catalog were ready within the first sprint. Genie Code drafts and debugs my PySpark, so I can spend more time on edge cases than boilerplate, and it often reads a job’s stack trace faster than I do. It also helped me pinpoint a provider file-format mismatch, so I could add an expectation and get reconciliation reports to the client’s finance team on time. Separate workspaces keep client projects apart, cluster policies help prevent oversized clusters on client budgets, and Unity Catalog gives me one place to manage table permissions and trace lineage when a source change breaks something downstream. Databricks helps me fix schema changes and failed jobs quickly so clients receive reliable data without delays.

What do you dislike about the product?

My main reservation is the pipelines dashboard. Since I deliver for several clients, their pipelines end up in one flat list and blur together. Assigning permissions pipeline by pipeline is tedious and, with client data involved, leaves too much room for error. Folders with inherited access, tags for client and environment, filters, and a summary of failed or delayed runs would make it easier to check one client’s pipeline health at a glance.

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

Databricks lets me run ingestion, transformation, and reconciliation pipelines for several clients’ data on one platform. Genie Code speeds up my PySpark development and debugging, so schema changes and failed jobs get fixed quickly and clients receive reliable data without delays.

What do you like best about the product?

I appreciated the security and the ability to trace the origin of each figure. It’s easy to identify the data source and make sure only authorized individuals can access confidential information. I also valued the color-coding, as well as the fact that it lets me combine data-cleaning code, SQL queries, and explanatory notes all in one place.

What do you dislike about the product?

I didn’t like having to require SQL or Python skills from finance professionals without adequate support. This created considerable resistance during the first few months.

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

Databricks addresses the slowness and fragmentation in financial analysis by replacing cumbersome spreadsheets and siloed systems with a high-speed platform that can process transactions in minutes and help automate month-end closes.

What do you like best about the product?

It is a unity data engineering, Analytics and machine learning platform. It helps in processing large scale data.

What do you dislike about the product?

Cost grow quickly
Cluster configurations, permissions and governance is becoming challenging in large organizations.

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

Slow processing of large datasets
Separate tools for data engineering, Analytics, AI and reporting.

What do you like best about the product?

I like Databricks' Unity Catalog, AI features, and governance features, which include data lineage, ABAC policies, AI agents, Genie, Genie code, and AI functions. These features simplify our work and are easy to configure and manage. I also switched to Databricks' workflows because of cost reduction and ease of maintenance and scaling. Plus, the initial setup was super easy. I'm really likely to recommend Databricks, and I gave it a 10 out of 10 on the recommendation scale.

What do you dislike about the product?

Databricks could use improvement in the frontend dashboard features to better align with other BI tools. Also, the UI for jobs, workflows, and pipelines is cumbersome, not very helpful, and difficult to navigate.

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

Databricks solves infrastructure scaling and performance bottlenecks with traditional data warehouses. It simplifies configuration and management, making it easy to maintain and scale, while reducing costs. These features significantly enhance my workflow.

What do you like best about the product?

I like Databricks for their ability to innovate quickly and deliver products to the market at a fast pace. The way they have developed products like Genie and agent bricks and continuously matured them is quite impressive. I appreciate how they integrate with other tools, especially in AI and BI dashboards. Building dashboards directly in Databricks instead of using external partners is helpful. The integration ecosystem with Unity catalog, which centralizes governance, is also impressive. Additionally, the support from Databricks during setup was smooth and the dedicated support team continues to be very helpful, especially in expanding our AI capabilities.

What do you dislike about the product?

Too many products to address similar problems at times creates confusion

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

Databricks helps us be AI-ready by providing a curated data platform and surfacing data in natural language, which improves accessibility and usability for end-users.

What do you like best about the product?

I really enjoyed the development experience. The real-time collaboration features and the integration with repositories make teamwork feel incredibly seamless, which is great.

What do you dislike about the product?

Migration works well alongside the proprietary platform, but Unity Catalog also strongly ties me to their business model.

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

Without a doubt, this is a powerful tool for modern data engineering. I was able to solve issues by turning slow pipelines into more robust, reliable processes, and so far everything has been running smoothly.

What do you like best about the product?

The things I loved the most in Databricks is the lakebase. It allows me to use the database like Postgres, which is a less burden to maintain a self-hosted Postgres.

What do you dislike about the product?

the price structure of the service they provide

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

It is solving me to maintain a huge data and its processing which help me to manage the data loads