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What differentiates Sisense from other similar products?

Sisense allows you to process gigabytes of data on a single server while serving multiple users. A drag and drop interface allows the transfer of data from many sources. You can change the position of the built-in chart widgets on the dashboard by dragging and dropping them there.

What is your favorite aspect of this product?

I like Sisense because it allows me to share dashboards online with multiple users. It provides the flexibility to connect to any data source, low-code or no-code tools, augmented analytics, and self-service capabilities. Data analysis, dashboard access and editing, and even running queries on the fly are possible. Teams can immediately integrate Sisense with their database or cloud-based data sources.

What do you dislike most about this product?

Elasticube's capabilities can be time-consuming and error-prone, and Sisense has some compilation issues.

What recommendations would you give to someone considering this product?

I recommend Sisense to improve customer interactions, increase sales and raise money. Offers understanding of complex data for better results. Large data sets from multiple sources can be combined into a single, consistent, enterprise-wide database.

What differentiates Sisense from other similar products?

Sisense excels with advanced analytics like consumer segmentation, forecasting, and regression. Using the collection of built-in widgets and approved plugins, you can create actionable app components and visualizations. Using a full range of toolkits and APIs, you can develop and tag.

What is your favorite aspect of this product?

I like Sisense for querying databases, building data models, and then using those models to build dashboards. To consolidate all your data in one location, you can securely connect to cloud data repositories and ingest data there. To get a complete understanding of your organization, you can combine data from many sources. Work teams will be able to view important KPIs and data from our processes thanks to this.

What do you dislike most about this product?

Using Sisense on a mobile device is not the best experience. Sisense subscription fees are expensive.

What recommendations would you give to someone considering this product?

Receiving Sisense to optimize raw data and gain insights. To improve performance, you can mix and cache multiple types of data or connect live to cloud data repositories. You can use SQL, Python, and R to serve your own models.

What differentiates Sisense from other similar products?

Sisense assists the developer in providing a graphical representation of the raw data. There are numerous alternatives available, such as a bar chart, a pie chart, a regional representation and so on. For our organization's database, we utilize Amazon Redshift. It is really simple to connect to a database and provide information to the user in a visual style without even going through the raw data in tabular form, it is also utilized to answer any business questions that a corporate leader may have. It is quite simple to use and comprehend, it was well received by business leaders with little technical experience.

What is your favorite aspect of this product?

Sisense is an exceptionally handy tool for inspecting data. It gives you a platform to explain the data in a chart/image/graph format, which greatly aids in visualizing the data. You can create pull-down charts, geographic maps, bubble charts, scatter plots, bar and column charts, and other types of charts. Cube functionality serves as the foundation for this. It also keeps information in mongodb, which aids in dashboard performance tracking. The visualization, tabber functionality, R and Python connectivity, and time series analysis are all excellent.

What do you dislike most about this product?

It offers less features than other popular programs such as Tableau, Power BI, and so on. It is also less intuitive than others. 91制片厂ing cubes first and then displaying them in a graph structure adds another layer of complexity. It becomes challenging for the developer to grasp and represent the logic of cube creation. There is relatively limited machine learning capabilities, for example. Additional capability is necessary to address the issue of olap (Online Analytical Processing). Dimension definition: layer, hierarchy, etc.

What recommendations would you give to someone considering this product?

I strongly advise you to use Sisense to address your end-to-end reporting and analytics problem. You can simply and naturally fix your problem. Anyone working in Business Intelligence, Data Analytics, or Data Science should give Sisense a shot. It may appear difficult to use at first, but with practice, it becomes second nature.