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This reduction in both time and money resulted in real-time impact and significant cost savings.
For a lot of different tasks, including machine learning, it is a nice solution.
When it comes to big data processing, I prefer Databricks over other solutions.
I have seen a return on investment with time savings and productivity gains, as we have consistent, governed data models that reduce the risk of errors by eliminating manual data entry.
I have seen a return on investment, as I mentioned earlier about time saving and productivity gains, with a consistent governed data model that reduces the risk of errors.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
I rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.
Our systems team, operating on a lot of Red Hat Enterprise Linux and maintaining long-term relations with IBM, benefits from good support coverage.
I rate technical support from IBM as eight out of ten, indicating a high quality of service.
they are slow to respond to my queries
The sky's the limit with Databricks.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
The scalability of IBM Cognos is very good, as it has continued growing with my organization's needs, allowing us to analyze and store a significant amount of data and handle our organization's growth efficiently.
It can be scaled out to other teams, but requires building cubes and implementing policies.
They release patches that sometimes break our code.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
Databricks is definitely a very stable product and reliable.
Even though we deal with a huge amount of data, it is capable of handling it, making it very stable.
I rate the stability of this solution as nine out of ten, indicating it is highly stable.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
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.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
Integration with Azure login makes trouble.
There is room for improvement in self-service analytics and predictiveness.
Since IBM Cognos is a futuristic platform with many robust features, it takes time to grasp all the features and how they work, so there is a learning curve.
It is not a cheap solution.
I believe that in terms of credits for Databricks, we're spending between £15,000 and £20,000 a month.
I rate pricing as a four, meaning it is more expensive compared to other solutions.
I believe the pricing is affordable and pocket-friendly for every organization.
Databricks' capability to process data in parallel enhances data processing speed.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
The AI features in IBM Cognos helped me gain deeper insights into our business processes, enabling me to make data-driven decisions easily and understand which points need our attention and which areas of our business are performing well.
IBM Cognos transforms raw data into insights and analytics, enabling our data team to make great insights and data-driven decisions easily.
I love the seamless and efficient data integration capability of IBM Cognos Analytics, where it allows us easy merging of data from various sources such as customer feedback and sales figures.
| Product | Market Share (%) |
|---|---|
| Databricks | 10.0% |
| Snowflake | 15.9% |
| Teradata | 8.4% |
| Other | 65.7% |
| Product | Market Share (%) |
|---|---|
| IBM Cognos | 1.3% |
| Microsoft Power BI | 8.9% |
| Tableau Enterprise | 6.2% |
| Other | 83.6% |


| Company Size | Count |
|---|---|
| Small Business | 26 |
| Midsize Enterprise | 12 |
| Large Enterprise | 56 |
| Company Size | Count |
|---|---|
| Small Business | 34 |
| Midsize Enterprise | 23 |
| Large Enterprise | 88 |
Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.
Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.
What features make Databricks unique?
What benefits can users expect from Databricks?
In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.
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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