Find out what your peers are saying about Microsoft, Salesforce, SAP and others in BI (Business Intelligence) Tools.
In a world surrounded by data, tools that allow navigation of large data volumes ensure decisions are data-driven.
Power BI is easy to deploy within an hour, providing robust security against data leaks.
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.
Based on our implementation in one project, we are trying to raise more funding to expand its use.
ThoughtSpot saves a significant amount of time compared to other tools and is very user-friendly.
I would say out of all the support experience I've had, only 5% took quite a long time to respond to the support message.
The significant drawback I notice is that Microsoft's size makes it hard to get specific change requests addressed unless they involve a bug.
We have a partnership with Microsoft, involving multiple weekly calls with dedicated personnel to ensure our satisfaction.
The support is good because there is also a community available.
I stopped opening tickets due to insufficient and untimely responses.
ThoughtSpot provides a dedicated customer success person and the ability to submit tickets online, with a response time of no more than a day.
The knowledge base for ThoughtSpot is less robust compared to others.
You expect only a small percentage of users concurrently, but beyond a thousand concurrent users, it becomes difficult to manage.
With increasing AI capabilities, architectural developments within Microsoft, and tools like Fabric, I expect Power BI to scale accordingly.
As more data is processed, performance issues may arise.
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.
As our data has grown, I have validated huge datasets and complex models without significant issues.
In terms of stability, there's no data loss or leakage, and precautions are well-managed by Microsoft.
We typically do not have problems with end-user tools like Excel and Power BI.
It is very stable for small data, but with big data, there are performance challenges.
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 upgrades are smooth with no downtime, which is super important.
The responsiveness of accessing live data is exceptional and faster than most other BI tools.
Understanding how AWS charges for Amazon QuickSight usage is critical for all users wanting to visualize their data effectively.
This makes Power BI difficult to manage as loading times can reach one or two minutes, which is problematic today.
Access was more logical in how it distinguished between data and its formatting.
Microsoft updates Power BI monthly based on user community feedback.
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.
Enhancing integration capabilities with other tools like DBT would also be beneficial as it would make our lives easier.
It is not expensive, but it is also not cheap.
I found the setup cost to be expensive
Power BI isn't very cheap, however, it is economical compared to other solutions available.
The pricing for Microsoft Power BI is low, which is a good selling point.
HubSpot is expensive.
ThoughtSpot's pricing is reasonable and in line with other BI tools.
The natural language query is very important, and natural language processing is crucial for disseminating dashboards across multiple formats and mechanisms.
In today's data-driven environment, these tools are of substantial value, particularly for large enterprises with numerous processes that require extensive data analysis.
Within the organization, Microsoft Power BI is used to create dashboards and gain insights into data, enhancing data-driven decision-making.
To reduce the need for highly skilled personnel, we can engage someone who is just familiar and has a basic understanding of Microsoft Power BI, while AI can handle the major tasks through either agent AI or requirement analysis.
Its compatibility with most databases, including the latest from FlexMovely and Redshift, allows users to create joins and worksheets easily.
This alerting feature is very beneficial for our company at the moment, and we use it extensively.
When I upload a data dump, AI analytics suggest possible data visualizations and insights, which I can pin to dashboards or live boards for modification.
Amazon QuickSight is a fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. Using our cloud-based service you can easily connect to your data, perform advanced analysis, and create stunning visualizations and rich dashboards that can be accessed from any browser or mobile device.
Microsoft Power BI is a powerful tool for data analysis and visualization. This tool stands out for its ability to merge and analyze data from various sources. Widely adopted across different industries and departments, Power BI is instrumental in creating visually appealing dashboards and generating insightful business intelligence reports. Its intuitive interface, robust visualization capabilities, and seamless integration with other Microsoft applications empower users to easily create interactive reports and gain valuable insights.
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.
