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When it comes to big data processing, I prefer Databricks over other solutions.
For a lot of different tasks, including machine learning, it is a nice solution.
Whenever we reach out, they respond promptly.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
They release patches that sometimes break our code.
Cluster failure is one of the biggest weaknesses I notice in our Databricks.
It can handle large datasets.
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
If I could right-click to copy absolute paths or to read files directly into a data frame, it would standardize and simplify the process.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
Pentaho Business Analytics is hard to learn and not suited for initial users as it requires knowledge of operating systems, Java, and other technical skills.
Pentaho Business Analytics is priced similarly to other competitors such as QlikView and Tableau.
Databricks' capability to process data in parallel enhances data processing speed.
Developers can share their notebooks. Git and Azure DevOps integration on the Databricks side is also very helpful.
It is a stable product, and it can handle large datasets.
Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.
Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.
What are the key features of Databricks?
What are the benefits or ROI to look for in Databricks reviews?
Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.
Pentaho is an open source business intelligence company that provides a wide range of tools to help their customers better manage their businesses. These tools include data integration software, mining tools, dashboard applications, online analytical processing options, and more.
Pentaho has two product categories: There is the standard enterprise version. This is the product that comes directly from Pentaho itself with all of the benefits, features, and programs that come along with a paid application such us analysis services, dashboard design, and interactive reporting.
The alternative is an open source version, which the public is permitted to add to and tweak the product. This solution has its advantages, aside from the fact that it is free, in that there are many more people working on the project to improve its quality and breadth of functionality.
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