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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.
Using ThoughtSpot has resulted in significant time savings and improved business sales by allowing us to identify sellers and buyers across regions, facilitating targeted marketing.
Whenever we reach out, they respond promptly.
ThoughtSpot provides a dedicated customer success person and the ability to submit tickets online, with a response time of no more than a day.
I stopped opening tickets due to insufficient and untimely responses.
The knowledge base for ThoughtSpot is less robust compared to others.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Tableau, Power BI, or Looker have separate tools for preparation, customization, and storytelling.
The platform does not have technical problems with scaling data or connections.
Scalability depends on your contract with them, whether it's consumption-based or row-based.
They release patches that sometimes break our code.
Cluster failure is one of the biggest weaknesses I notice in our Databricks.
The upgrades are smooth with no downtime, which is super important.
I use it primarily for large datasets, and it performs faster than regular data visualization tools such as Power BI, which has limits on dataset size.
The responsiveness of accessing live data is exceptional and faster than most other BI tools.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
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 prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
Enhancing integration capabilities with other tools like DBT would also be beneficial as it would make our lives easier.
Currently, it is not as customizable as the options available on Power BI or Tableau.
Handling governance when there are many models and dashboards is complex.
HubSpot is expensive.
ThoughtSpot's pricing is reasonable and in line with other BI tools.
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.
Its compatibility with most databases, including the latest from FlexMovely and Redshift, allows users to create joins and worksheets easily.
The main core of HubSpot is to create models, connect data pipelines, and create business models and dashboards on top of them.
ThoughtSpot excels in being self-service oriented, allowing users who aren't developers to easily create their own reports and visualizations, making it very intuitive.
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.
ThoughtSpot is a powerful business intelligence tool that allows easy searching and drilling into data. Its ad hoc exploration and query-based search features are highly valued, and it is easy to set up, stable, and scalable.
The solution is used for reporting purposes, self-service BI, and embedding into other applications for customers to do self-service analytics. It helps businesses with metrics, KPIs, and important insights by sourcing data from various sources into one golden source and visualizing it in an easy way for the business to consume. The pricing model is ideal, charging for data rather than the number of users.
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