Zoho Analytics vs Sisense: In-Depth Comparison of Leading BI Platforms 2024

12.07.24 02:45 PM By CreatorScripts

Comparing Data Integration Options: An Interactive Experience

Zoho Analytics vs Sisense Comparison

Zoho Analytics vs Sisense Comparison

Zoho Analytics

  • Full-fledged, self-service BI and Analytics software
  • 250+ native and live data connectors
  • Unified Business Analytics with automatic data blending
  • AI Assistant (Ask Zia) for search-driven analytics
  • Collaborative Analytics with fine-grained access controls
  • Cloud-native with proprietary platform and storage infrastructure
  • Complies with GDPR, SOC Type 2, ISO/IEC 27017, 27018, and 27001

Sisense

  • Complete end-to-end BI platform
  • Extensive integration with various data sources
  • Supports complex data modelling
  • Rich visualizations with extensive charts
  • AI capabilities for insights (Sisense Alexa Skill)
  • Deployment options: Cloud, On-premise, Hybrid
  • Complies with various industry standards

Feature Comparison

Detailed Comparison

Zoho Analytics:

Files and Feeds, Cloud Storage, Cloud Databases, Local Drive Files, Web URL and FTP, Amazon S3, Google Drive, OneDrive, Dropbox, AWS Redshift, etc.

Sisense:

Similar range with extensive third-party integrations.

Both platforms support:

  • Auto-join tables
  • Define lookup to relate tables
  • Data formatting and cleansing
  • SQL Querying and Filtering
  • Arithmetic functions
  • Statistical functions
  • Time-based functions

Zoho Analytics:

Starts at $30/user/month, with details available on request.

Sisense:

Pricing on request, starting around $35/user/month according to third-party sources.

Fact Checked Information

  1. Data Integration:
    • Zoho Analytics having 250+ native and live data connectors is accurate [1].
    • Both platforms do offer extensive integration with various data sources [1][4].
  2. Unified Business Analytics:
    • Zoho Analytics does provide automatic data blending across sources [1].
    • Both platforms support ad hoc visual analytics [1][4].
  3. Augmented Analytics:
    • Zoho Analytics has an AI assistant called Ask Zia, which is correct [1].
    • Sisense has AI capabilities including Sisense Alexa Skill [4].
  4. Collaborative Analytics:
    • Both platforms offer extensive sharing and collaboration features [1][4].
  5. Data Security and Privacy:
    • Zoho Analytics complies with the mentioned standards (GDPR, SOC 2, ISO 27001/17/18) [1].
    • Sisense also complies with various security standards [4].
  6. Deployment:
    • Zoho Analytics is primarily cloud-native [1].
    • Sisense offers cloud, on-premise, and hybrid deployments [4].
  7. Pricing:
    • Zoho Analytics starting at $30/user/month is accurate [1].
    • Sisense pricing is not publicly available, so the $35/user/month figure cannot be verified directly from Sisense sources.
  8. Features Comparison:
    • The detailed features comparison appears generally accurate based on the information from both companies' websites [1][4].

Overall, the comparison provides a fair and mostly accurate representation of both platforms. However, for the most up-to-date and precise information, especially regarding pricing and specific features, it's always best to consult the official websites or contact the companies directly.

Citations:

  1. https://www.zoho.com/analytics/help/overview.html
  2. https://help.zoho.com/portal/en/community/topic/a-complete-overview-of-zoho-analytics
  3. https://www.zoho.com/analytics/solutions.html
  4. https://docs.sisense.com/main/SisenseLinux/new-to-sisense.htm
  5. https://www.sisense.com/about/
  6. https://dtdocs.sisense.com/article/integrations
  7. https://www.zoho.com/analytics/sisense-alternative-software.html
  8. https://www.selecthub.com/business-intelligence-tools/sisense-vs-zoho-analytics/
  9. https://www.zoho.com/analytics/features.html
  10. https://www.rocket.bi/post/sisense-overview

What is Zoho Analytics used for?

Zoho Analytics is a data analytics and business intelligence platform that helps businesses and organizations transform their data into insights and make informed decisions. Zoho Analytics provides a range of features and tools to collect, store, and analyze data, as well as create and share reports, dashboards, and other data visualizations.

Is Zoho Analytics easy to use?

Zoho Analytics is designed to be user-friendly, with a simple and intuitive interface, drag-and-drop functionality, and pre-built templates. The platform also provides a range of resources and tutorials to help users get started and make the most of its features and tools. Whether Zoho Analytics is easy to use will depend on the user's experience and familiarity with data analytics and business intelligence platforms.

Which companies use Zoho Analytics?

Zoho Analytics is used by a range of businesses and organizations of different sizes and industries, including startups, SMBs, and enterprise companies. Zoho Analytics is a versatile platform that can meet the needs of different types of organizations and data analytics requirements.

How do I access Zoho Analytics?

Zoho Analytics is accessible online and can be accessed from any device with an internet connection. To access Zoho Analytics, you need to sign up for an account on the Zoho website and log in to the platform. Once you've logged in, you can start using the platform's features and tools to collect, store, and analyze your data.

Can I use Python in Zoho Analytics?

Zoho Analytics does not directly support the use of Python. However, it is possible to integrate Zoho Analytics with Python using APIs and other data integration tools. This can allow users to access and analyze data stored in Zoho Analytics using Python and other programming languages.

Is SQL enough for data analyst?

SQL (Structured Query Language) is a powerful tool for data analysis and is widely used in the industry. However, it is not the only tool used by data analysts and may not be enough for all data analysis tasks. Data analysts may also use a range of other programming languages, tools, and platforms, depending on the specific needs and requirements of their data analysis projects.

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