Moving data from in-house databases / apps
Why Zoho Analytics is a superior BI & Reporting tool when compared to Spreadsheets?
The spreadsheet, especially Microsoft Excel, is the most widely used business intelligence and reporting tool across any enterprise (small or big). It acts both as a data collection/integration tool as well as a good reporting & analysis tool. It has been the de-facto tool for both business analysis and reporting.
However, in the new age of on-demand business software and the need for a collaborative and always connected business setup, there are areas in which spreadsheets are limiting as your business intelligence tool.
Where Spreadsheets are found lacking as a Business Intelligence Tool
Top Takeaways in favor of Zoho Analytics
Detailed Comparision: Spreadsheets vs Zoho Analytics
The following table captures more in detail on how Zoho Analytics compares itself favorably against Spreadsheets, for your analysis and reporting needs.
|Data Input & Sources supported (Data Integration)|
Summary: Offers a reasonable set of options to input data.
Summary: Offers a wider and more functional set of options to input data.
Summary: Basic reporting and analysis is easy to do. More powerful and advanced reporting/analysis becomes complex.
Summary: Complex analysis of data and powerful reporting is easy to do.
Summary: Merging and querying disparate datasets is difficult to do.
Summary: Complex querying is possible as it supports SQL.
Note: A Visual Query Builder is also in the pipeline.
|Sharing and Collaboration|
Summary: Sharing and collaboration is difficult and error-prone.
Summary: Being online, sharing and collaboration becomes much easier.
Summary: Difficult to define relationships across different data sets.
Summary: Defining relationships across tables is easy.
Summary: Securing data is hard to achieve and is almost impossible.
Summary: Your data is with professional hands and hence safe.
|Scalability: Size of Data and Speed|
Summary: Sluggish responsiveness when dealing with larger datasets.
Summary: Quick responsiveness even for very large datasets as the system is designed to handle huge volumes of data.
Summary: Data integrity is hard to achieve.
Summary: The underlying design takes care of data integrity (single version of truth) by itself.
Summary: High licensing and maintenance costs.
Summary: Affordable monthly, pay-as-you-go subscriptions.
Note: Check out our affordable pricing plans.