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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.
I rate technical support from IBM as eight out of ten, indicating a high quality of service.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
It can be scaled out to other teams, but requires building cubes and implementing policies.
They release patches that sometimes break our code.
Cluster failure is one of the biggest weaknesses I notice in our Databricks.
I rate the stability of this solution as nine out of ten, indicating it is highly stable.
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.
There is room for improvement in self-service analytics and predictiveness.
I rate pricing as a four, meaning it is more expensive compared to other solutions.
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.
IBM Cognos is a robust governed platform with significant security features and provides excellent graphics and reporting.
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.
IBM Cognos Business Intelligence provides a wide range of tools to help you analyze your organization's data. IBM Cognos BI allows businesses to monitor events and metrics, create and view business reports, and analyze data to help them make effective business decisions.
IBM Cognos applies techniques to describe, summarize, and compare data, and draw conclusions. This allows users to see trends and discover anomalies or variances that may not be evident by simply reading data. Data sources that contain information from different areas of a business can be stored in separate packages. Users can see only information that they have been granted access to, based on their group or role.
IBM Cognos BI consolidates the following business intelligence functions into a single web-based solution:
Reviews from Real Users
IBM Cognos stands out among its competitors for a number of reasons. Two major ones are its powerful analysis tool and its reporting capabilities.
Prasad B., a senior software engineer at a financial services firm, notes, “The product is a very good reporting tool and is very flexible. It allows for the users to get a scheduled report. We can receive automated reports as well. They are easy to schedule on a weekly or monthly basis. It is very fast. I mean in means of report output, it's very fast compared to the actual clients involved.”
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