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What is Databricks Data Intelligence Platform?
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Overall experience with Databricks Data Intelligence Platform
“Adopting Databricks Shifts Data Integration Approach but Increases Learning Demands”
“Databricks Platform Facilitates Workflow But Notebook Performance Remains Slow”
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Databricks is a global company focusing on data and AI. At the core of Databricks is the Databricks Data Intelligence Platform which allows entire organizations to use data and AI to power a wide range of business use cases. It's built on a lakehouse to provide an open, unified foundation for all data and governance and is powered by a Data Intelligence Engine that understands the uniqueness of the organizations’ data. Databricks simplifies and accelerates enterprises' data and AI goals by unifying data, analytics and AI on one platform. Its key mission is to assist data teams in addressing some of the world's most challenging problems.
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Databricks Data Intelligence Platform Likes & Dislikes
What I really like about Databricks is that it is constantly innovating. The UI is constantly evolving along with its features. I believe I heard a quote that within a year over a hundred different features are released, and not only are features released but they continue to build on them so its not like once a new feature is released old ones are then removed. Secondly I really like its ability to be able to basically ingest any form of modern data (json, parquet, csv, xls, xml you name it) and be able to ingest it and start to derive insights right away during ingestion. The last thing that I really like about Databricks is the fact that it is truly trying to become a hub for all things data including data governance, analysis, data science, machine learning and a dash of reporting.
- Easy access to data tables (both writing and reading) - Ease of setting up scheduled jobs - Relatively easy to use interface
1. AI and ML capabilities are phenomenal and the possibilities of the Platform becoming a powerhouse for deploying ML Models and Systems is quite a lot. 2. The ease of managing multiple assets within the same location with Unity Catalog and Workspace-Based Asset Deployment provides a feeling of seamless integration. 3. The ability to connect different Systems as data sources to databricks is an amazing feature,and they never seem to disappoint with the speed of how they bring updates.
In the same breath though I do admit there is a bit of a steep learning curve given the fact that there are so many new features constantly being released. Its a real challenge keeping up with all the innovative features, things are moved around and names are changed (delta live tables to now Lakeflow Declarative Pipelines). A second thing that can be frustrating is when the odd chance there is some sort of error that it can be very difficult to pin down what the real source of the error is since there are so many moving pieces (is it a package, is it the data lake, is it code logic issue etc). The last thing that can be frustrating is that since this is a tool that can be hosted on multiple cloud providers at times reading up on documentation it can be confusing as to whether or not the article is applicable to my particular provider.
The Databricks notebooks are very slow.
The constant changes to the UI and critical functionalities can sometimes feel overwhelming, The changes are not quite as big as that, but I have had instances where I had to revisit code or features just because something changed, can possibly introduce LTS versions if possible.
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Peer Discussions
Databricks Data Intelligence Platform Reviews and Ratings
- Data EngineerGov't/PS/EdEducationReview Source
Adopting Databricks Shifts Data Integration Approach but Increases Learning Demands
My organization up until just before 2021 was by and large an on premise shop. So most of our ETL tools, reporting and business intelligence tech stack was all based on premise. That all changed in the last few years as there has been a major shift towards embracing more of what cloud providers can enable our organization. Our journey began with Azure and talking about reporting, data science, machine learning and ELT/ETL you have to look at Azure Databricks. Databricks can seem a bit daunting at first as there is a lot of features packed into it but after using it for a month you will definitely get the hang of things and how to find things. Its definitely been a tool that has become our go-to when looking towards any sort of data integration or analysis - BI Developer50M-1B USDEnergy and UtilitiesReview Source
Databricks ETL Pipelines UI Simplified, but Frequent Updates Can Feel Overwhelming
In regard to the recent updates, Databricks has simplified its ETL pipelines UI which makes it easier to use, apart from that we have recently started using Power BI tasks which makes the integration between Data Lakes and downstream reports, apart from that I think it's truly revolutionary approach in centralized security through Unity Catalog is truly commendable. - Senior Software Engineer10B+ USDManufacturingReview Source
Platform Streamlines ML Asset Governance and Centralizes Data Engineering Efforts
We are a platform that provides databricks utilities to multiple data engineering, AI and ML use cases. This has become a main tool for our customers in the cloud since the mlops features that are provided are bringing the possibility to create value faster than other ML tools in the market. With the unity catalog, we gained a lot of governance over the ML assets and data layers. Serverless compute has reduced infrastructure management significantly, despite additional networking configuration needed to access storage. - DATA AND ANALYTICS MANAGER10B+ USDBankingReview Source
Lakehouse Architecture Enables Scalable, Flexible Workflows Across Diverse Data Workloads
DataBrick's Data intelligence platform feels like powerful, enterprise-grade analytics and AI ecosystem - built to unify data engineering, data science, analytics, and, machine learning in one cloud native environment. Its centered on the lake house architecture, which combines data warehouse ad data lake principles, while providing scalable performances and flexibility for diverse workloads. - Data Governance Expert1B-10B USDBankingReview Source
Databricks: A comprehensive solution for Data Integration, Processing and Analytics
The Databricks Data Intelligence Platform is a centralized platform to handle all our data related tasks, from organizing, storing, managing, transforming, mining data, analyzing data through simple dashboards. The platform also provides the ability to build models as well as pre-made models, especially LLMs. Till now, it has basically met our needs, except some features that are still under development (slowly).