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Good analytics tools are essential to extract useful intelligence from your website, sales, and finance data. You might end up choosing several different specialized data-tracking tools for discrete purposes, but some users prefer a centralized dashboard to cover everything in one place. I’ve explored the best of both worlds. Browse my pick of the best tools below.

What Is Cloud Analytics?

Cloud analytics is the collection, tracking, and analysis of data hosted in the cloud. Cloud-hosted data can take advantage of more processing power than data held on local servers, providing a suitable platform for significant data set analysis. The right cloud analytics tools can save you time and money, streamline your reporting abilities, and maximize scalability.

Best Cloud Analytics Tools Summary

Tools Price
Alteryx From $80/user/month
Tableau From $75/user/month
Looker From $5,000/month
Grow From $1,500/month
GoodData From $1000/month
Klipfolio PowerMetrics From $49/month
Microsoft Power BI From $10/user/month
Qlik Sense From $30/user/month
IBM Watson Analytics From $150/user/month
Oracle Analytics From $16/user/month
Amazon QuickSight From $9/user/month
Zoho Analytics From $24/month
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Overviews Of The 12 Best Cloud Analytics Tools

Here’s my take on the best cloud analytics tools. I summarized the features of each tool, focusing on reporting and data visualization, cost reduction, collaboration, and usability.

Best for data preparation and advanced analytics

  • 30-day free trial
  • From $80/user/month
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Rating: 4.5/5

Alteryx is like a power-up for your data analytics, enriching insights with advanced data science. It helps teams make informed decisions with predictive and prescriptive models suggesting the next action.

Why I picked Alteryx: I chose Alteryx because of its intelligent preparation and analysis abilities, including feature engineering, auto modeling, generative AI, and NLP. These elements propel the scheduling and orchestration of the data prep and analysis stages to the top players in cloud analytics.

Alteryx Standout Features and Integrations:

Features include active data profiling, role-based access control, and the ability to schedule and orchestrate data pipelines. Standouts for me are the support for software development lifecycles and predictive data transformation, allowing you to integrate data into your workflows.

Integrations include native pairings with Snowflake, Tableau, AWS, Data Visualization, Azure, and Power BI, where Alteryx is the orchestration engine automating and modeling the data collected from these tools.

Pros and cons

Pros:

  • Scalable for enterprises
  • Automated processes
  • Easy to use

Cons:

  • Expensive business plan
  • Limited data visualization

Best for creating interactive dashboards

  • 14-day free trial
  • From $75/user/month
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Rating: 4.4/5

Tableau is a market leader in cloud analytics platforms, combining BI and visual analytics to transform how teams use data to solve problems. Data exploration is at its core, allowing users to discover insights and share reports.

Why I picked Tableau: I chose Tableau because of its interactive dashboards and unlimited data exploration capabilities. Using NLP to navigate challenges and action plans, you can build visualizations with statistical modeling.

Tableau Standout Features and Integrations:

Features include line patterns and multi-row calculations, which I think makes data analysis easier to navigate. I like the Tableau GPT tool, which uses AI to provide smart in-product guidance, user query predictions, and contextual insights into your workflow. It also employs a dedicated trust layer to ensure enterprise data security and compliance.

Integrations include native connections with Microsoft Excel, Amazon Redshift, Databricks, Dropbox, Google Analytics 4, Google Sheets, Marketo, OneDrive, Salesforce, and about 80 others. You can use the Tableau API for additional integration options.

Pros and cons

Pros:

  • Accurate NLP
  • Self-service data preparation
  • Unlimited data exploration

Cons:

  • Steep learning curve
  • Expensive for multiple licenses

Best for embedded analytics and data exploration

  • 30-day free trial
  • From $5,000/month
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Rating: 4.4/5

Part of the Google Cloud, Looker is a BI platform that you can self-service, build custom applications with, or model to your existing BI environment. Looker Studio is a data visualization portal where you can connect hundreds of data sources and create customized reports.

Why I picked Looker: Looker’s powerful data exploration and automation are why I chose it for this list. I think it's an easy way to provide a central source of truth for the whole team, with accurate and consistent data. You can embed analytics into any app or webpage and customize metrics for each department for tailored reporting.

Looker Standout Features and Integrations:

Features include report automation and forecasting. A standout for me is the semantic layer architecture which supports setting data security frameworks by enabling you to set up row and column-level permissions.

Integrations include native connections with Salesforce, Shopify, Airtable, Google Ads, Mailchimp, Google Analytics, Slack, HubSpot, Dropbox, and Quickbooks. You can import SQL data sources and connect other apps with a custom API.

Pros and cons

Pros:

  • Easy to use and navigate
  • Easy integration with data sources
  • Customizable dashboards

Cons:

  • Data upload speeds can be slow
  • Can be expensive

Best for full-stack business intelligence

  • Free trial available
  • From $1,500/month
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Rating: 4.3/5

Grow is a BI tool ideal for growing companies because it scales effectively and makes data accessible through a central source of truth. Key values and data recognition are automatic and allow custom metrics to be set for every team and department.

Why I picked Grow: Grow lets you connect and store data from hundreds of data sources and SQL databases, providing full-stack BI. This all-encompassing and cost-reducing environment is why I chose Grow. Even if your data spans billions of rows, Grow can accommodate you.

Grow Standout Features and Integrations:

Features include connecting raw data from databases, CRMs, ad platforms, social media, accounting and finance, marketing analytics, and files. I love how you can create a customizable central dashboard and blend multiple data sources to develop intuitive insights and reports.

Integrations include hundreds of native connections with business tools and apps. Popular native integrations include Salesforce, Shopify, Airtable, Asana, Freshbooks, Google Ads, and Hubspot. If there is no connection for your data source, you can do a data export directly or to an SQL database. A custom REST API is also available.

Pros and cons

Pros:

  • Unlimited data exploration
  • No code required
  • Hundreds of native integrations

Cons:

  • No free plan
  • Can be costly for individuals and start-ups

Best for advanced self-service analytics

  • 30-day free trial
  • From $1000/month
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Rating: 4/5

GoodData is a cloud-based BI and analytics platform that allows you to build low-code and no-code solutions. It is customizable and powerful enough to deliver data at any scale.

Why I picked GoodData: I selected GoodData because of its advanced self-service data exploration abilities. The user interface provides a drag-and-drop function so users can create interactive dashboards and data visualizations without any coding or expert knowledge.

GoodData Standout Features and Integrations:

Features include customizable dashboards — you can even white-label them! One of my favorite GoodData features is the ability to integrate and embed real-time analytics dashboards into any application.

Integrations include native connections with Snowflake, Amazon Redshift, Google BigQuery, Databricks, Greenplum, and SQL databases. Additional integrations can be made with the Python SDK, React SDK, or the GoodData REST API.

Pros and cons

Pros:

  • White-label features
  • Drag-and-drop user interface
  • Embed analytics into any application

Cons:

  • Steep learning curve
  • No free plan

Best for small businesses

  • 14-day free trial
  • From $49/month

Klipfolio PowerMetrics ensures your team is aligned on the same page from anywhere with real-time data and metrics — and not a line of code in sight. Combining metrics and data in one view encourages businesses to filter, segment, and analyze for efficient decision-making.

Why I picked Klipfolio PowerMetrics: I think Klipfolio PowerMetrics’ features are perfect for small businesses and start-ups, as it’s built around collaboration and these teams often need to pull together to find business-wide solutions. It takes a metrics-first approach, meaning you can share, compare, and analyze your business metrics on one dashboard while your data is modeled and prepped behind the scenes.

Klipfolio PowerMetrics Standout Features and Integrations:

Features include segmentation and filtering that can be used for specific goals. I think this is distinctive and suited for goal-driven businesses. You can set your business goals, create metrics, and assign data; then, you can make graphs and reports based on these goal filters to see if you’re on track.

Integrations include 17 native connections with Facebook, LinkedIn, Instagram, YouTube, Google Ads, HubSpot, Shopify, Xero, and Salesforce, among the favorites. You can connect data sources with Google Sheets and Microsoft Excel. You can request integrations from the MetricsHQ team if they are missing.

Pros and cons

Pros:

  • Large library of metrics
  • Clean user interface
  • Custom metrics

Cons:

  • Dated user documentation
  • Limited API settings

Best for business intelligence and reporting

  • Free plan available
  • From $10/user/month

Microsoft Power BI uses Copilot, a next-generation AI tool that analyzes and turns your data into interactive reports. Tell your Copilot what you need or ask a question and it will pull data, analyze it, and visualize it into a report, summary, calculation, or narrative — whatever you request.

Why I picked Microsoft Power BI: I chose Microsoft Power BI because it creates beautiful and impactful dashboards and reports for your BI data. It provides a secure, centralized hub where you can create databases from any source and create an accessible single source of truth.

Microsoft Power BI Standout Features and Integrations:

Features include engaging data visualizations that you can create with the drag-and-drop interface. I liked how the platform offers AI to support and provides a tailored experience. Reports and insights can be shared across apps and tools to translate growth and action plans across teams.

Integrations include native connections like Oracle, DropBox, Slack, Todoist, Asana, Google Drive, Twitter, and all Microsoft tools. You can also pull data from custom APIs through the Power BI app.

Pros and cons

Pros:

  • Powerful AI features
  • Affordable
  • Next-level data visualization

Cons:

  • App only supported on Windows
  • Data upload limits

Best for augmented analytics

  • 30 Days Free Trial
  • From $30/user/month

The Qlik Sense cloud analytics platform is powered by AI turning real-time data into auto-generated action plans and insights. Driving immediate activity creates a proactive and collaborative environment for business growth.

Why I picked Qlik Sense: I chose Qlik because of its AI-driven approach to analytics. Although most analytics tools provide some AI features, Qlik Sense distinguishes itself with the quality of its machine learning. Generative AI removes the challenge of knowing what questions to ask to gain the insights you need, and AI predictions guide data analysis and foster business growth.

Qlik Sense Standout Features and Integrations:

Features include fast, flexible, and interactive data visualization and exploration. I liked that its intelligent data alerts inform users of any outliers or sudden changes so you can take swift action with automatic event-driven triggers.

Integrations are limited, in my opinion, compared with competitors. However, Qlik Sense does have native connections with Amazon AWS, Google, Microsoft, Snowflake, SAP, Confluent, and Databricks. Open APIs mean you can connect other tools.

Pros and cons

Pros:

  • Interactive dashboards
  • Low code solution
  • AI data forecasting

Cons:

  • Difficult to extract data
  • Lacking some basic charts

Best for leveraging AI-powered analytics

  • 30-day free trial
  • From $150/user/month

IBM Watson Analytics allows analysts to build and manage AI models, automating life cycles and speed times to value. It accelerates business growth with transparent data the team can share and understand.

Why I picked IBM Watson Analytics: I chose IBM Watson Analytics because of the new Watsonx AI, which is powered up and ready for enterprise-level AI-powered data analysis and insights. You can train Watsonx, validating and fine-tuning the machine learning models to understand your business and your data in a way that helps you scale.

IBM Watson Analytics Standout Features and Integrations:

Features include the IBM Watson Studio, which helps you refine data and optimize your decision-making process with predictive models. The studio allows you to compare metrics side-by-side, making risk assessment a breeze. I think IBM Watson Analytics is an excellent solution for financial analytics as you can plan, budget, and forecast your data.

Integrations include native connections with Box, DropBox, Salesforce, Twitter, and all IBM cloud solutions. You can connect other tools with custom APIs.

Pros and cons

Pros:

  • Accurate NLP
  • Affordable
  • Coachable and scalable AI

Cons:

  • Poor user documentation
  • Steep learning curve

Best for scalability

  • Free plan available
  • From $16/user/month

Oracle Analytics is a business analytics platform suitable for businesses of all sizes, and it offers self-service features and the ability to work with large data loads. With data forecasting, teams can make accurate decisions and action plans for business growth.

Why I picked Oracle Analytics: In my opinion, Oracle Analytics is a great tool to help scale your business. I love that a free plan is available where you can work with a wide range of features. These can then be upgraded and new features added as and when needed, so you only pay for what you use.

Oracle Analytics Standout Features and Integrations:

Features include text and voice search queries and business questions to gain insight into your data; I love how accessible it is, as not all tools on this list offer verbal instruction. NLP also makes it easy to communicate with your data. Custom map analytics and pathfinding allow you to explore data relationships visually.

Integrations include 37 native connections, like Google Analytics, Salesforce, DropBox, Amazon Redshift, Azure Synapse, Google Drive, and Snowflake. You can connect to any Java Database Connectivity-based (JDBC) data source, and the Oracle REST API allows you to integrate with many other data sources.

Pros and cons

Pros:

  • Advanced accessibility
  • Highly scalable
  • Reusable data models

Cons:

  • No mobile app
  • Complex pricing model

Best for data visualization

  • 30-day free trial
  • From $9/user/month

Amazon QuickSight is a business intelligence (BI) tool for data-driven organizations. With natural language processing (NLP) and generative artificial intelligence (AI) powers, it provides a single source of truth for the whole team.

Why I picked Amazon QuickSight: I chose Amazon QuickSight because of its extensive filtering capabilities, allowing you to gain visual insights into your data in a way that makes sense to you. Key highlights make data analysis quick, and detailed graphs enable you to provide granular reports. You can scale your data visualization with interactive dashboards, paginated reports, and embedded analytics.

Amazon QuickSight Standout Features and Integrations:

Features include natural language queries to analyze your data and gain actionable next steps. I love that it’s like a genuine conversation with someone who can provide fast and accurate responses to help guide your business. You can scale QuickSight to accommodate tens of thousands of users, but you only pay for what you need, making it cost-effective.

Integrations include native connections with most Amazon tools, including Aurora and Redshift. There are also native integrations with Jira, Adobe Analytics, Salesforce, Snowflake, and various SQL databases. There is always the Amazon QuickSight API if you need additional integrations.

Pros and cons

Pros:

  • Paginated reports
  • Highly scalable
  • Uses natural language queries

Cons:

  • Some data sources lack real-time updates
  • No free plan

Best for data-driven storytelling

  • Free plan available
  • From $24/month
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Rating: 4.2/5

Zoho Analytics allows you to connect and transform large amounts of data into interactive reports to engage your entire team. The AI assistant can identify and explore metrics, trends, outliers, and insights.

Why I picked Zoho Analytics: I included Zoho Analytics because of its collaboration and storytelling features. You can share and publish views, where teams can add comments. Access controls can be customized, and you can create immersive presentations and build portals for a deeper shared understanding of your data.

Zoho Analytics Standout Features and Integrations:

Features include widgets, charts, pivot tables, and tabular views for data visualization. The augmented analytics features are robust with generative insights and trend predictions. The real standout for me is the what-if analysis, which allows you to forecast the differences between scenarios when one or more variables are changed.

Integrations include native connections with Salesforce, HubSpot, Mailchimp, Google Analytics, LinkedIn, Eventbrite, Facebook, Twitter, YouTube, and all tools in the Zoho Suite. The Zoho Analytics API allows you to connect other tools and apps.

Pros and cons

Pros:

  • Excellent technical support
  • Attractive data visualization
  • Drag-and-drop interface

Cons:

  • Only one workspace for each data source
  • Cost to add viewers

Other Cloud Analytics Options

Here are some cloud analytics tools that didn’t make my top list, but I think are still worth checking out:

  1. Reveal

    Best for embedded analytics

  2. Domo

    Best for simplifying data analysis and workflows

  3. Databricks

    Best for Apache Spark users

  4. SAP BusinessObjects

    Best for data forecasting

  5. Salesforce Einstein Analytics

    Best for Salesforce users

  6. Microsoft Azure

    Best for data warehouses and big data systems

  7. Yellowfin

    Best for simplicity and storytelling

  8. Pentaho

    Best for open-source data integration

  9. Thoughtspot

    Best for natural language data analysis

  10. Sisense Fusion Analytics

    Best AI-powered embedded analytics

Selection Criteria For Cloud Analytics Tools

I've used many cloud analytics tools in business and data analysis. While some cover a select one or two areas, some provide a central dashboard for the entire business. Whichever your preferred approach to cloud analytics is, each tool on my list has been selected using the following evaluation criteria:

Core Functionality

Here are the core functionalities the tools must offer to make it onto my list:

  • Drives growth and scalability
  • Saves you time
  • Fosters a unified approach; breaks down silos between teams

Key Features

Here are the essential features required to deliver the core functionality outlined above:

  • Reports and visualization tools: An analytics tool without reporting and data visualization is like loyalty without trust. Each tool on my list has varying reporting and functionality and dashboard customization.
  • Sharing and collaboration: One of the primary benefits of cloud analytics is the ability to collaborate and share data with your teams globally. Downloadable and shareable reports are essential.
  • Cost reduction: Cloud analytics is typically a more cost-effective option than on-premise solutions due to the lack of hardware and software required. However, I have considered tool prices, usability, and AI technology to reduce time and financial costs further.
  • Security and backups: Robust security policies and technologies have been considered for each tool I’ve selected, along with backup abilities, frequency, and storage.

Usability

I prioritized tools that offered clean dashboards and reporting features, creating a positive user experience. You want to gather and understand your data quickly without getting overwhelmed by cluttered interfaces and complex customization settings.

Integrations

I chose cloud analytics tools that integrate with other platforms, such as CRMs, sales, e-commerce tracking software, communication apps, and data collection tools. I’ve included top integrations to save you time.

Flexibility and Customization

I selected tools that offer flexibility and customization in a way that grows with your business. Allowing you to hyperfocus on one area of analytics in your business or navigate full business intelligence dashboards means you can scale at a rate that suits you and your team.

People Also Ask

Still unsure how cloud analytics tools can save you time and money, streamline your reporting abilities, and maximize your scalability? These frequently asked questions and answers should help:

How Do You Use Cloud Analytics?

Hosting vast amounts of data on local servers can be expensive and needs maintenance. Hosting this data in the cloud on a purpose-built platform allows teams to focus on the analysis and not on concerns about speed or security. Cloud analytics tools can save businesses time, money, and resources while allowing them to scale without limits and become more profitable.

Join the conversation and tell us which tools work best for your business growth. Any missing from my list?

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By Paulo Gardini Miguel

Paulo is the Director of Technology at the rapidly growing media tech company BWZ. Prior to that, he worked as a Software Engineering Manager and then Head Of Technology at Navegg, Latin America’s largest data marketplace, and as Full Stack Engineer at MapLink, which provides geolocation APIs as a service. Paulo draws insight from years of experience serving as an infrastructure architect, team leader, and product developer in rapidly scaling web environments. He’s driven to share his expertise with other technology leaders to help them build great teams, improve performance, optimize resources, and create foundations for scalability.