Choosing the right cloud analytics platform can feel like trying to escape from quicksand — the more you struggle, the deeper you sink into confusion.

It’s easy to feel lost among multiple features, benefits and technical jargon. This article can be the lifeline you need for selecting a suitable BI solution and includes a discussion of the top cloud platforms and handy tips.

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SaaS is cloud-hosted, so when you opt for SaaS, you’re using the public cloud. You can opt for a cloud subscription for computing, storage and network connectivity to host your own enterprise applications.

Read our SaaS (Software as a Service) article to learn more.

Best Cloud Analytics Platforms

Our research analysts curated a list of the best cloud analytics tools. We discuss the top five here. It’s worth mentioning here that Oracle Analytics Cloud (OAC) is a cloud platform, while the rest are SaaS tools.

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Power BI

Microsoft’s Power offering is a suite of SaaS analytics tools for reporting, data mining and visualization. It’s scalable and accessible from anywhere with an internet connection.

The solution connects to several cloud-based and on-premise sources and deploys on all primary cloud services. It’s available as a subscription service in two editions, Pro and Premium.

Convey metrics via customizable graphics in cloud analytics platforms. Source

Highest Rated Modules According to Our Data

• Data Management — 100
• Embedded Analytics — 100
• Mobile BI — 100
• Dashboarding and Data Visualization — 94
• Data Querying — 90

Top Benefits

• Manage Data: Prepare, blend, model, explore and govern organizational data using a Python integration and a robust query editor.
• Predict Business Trends: Anticipate opportunities and preempt risks with scenario, what-if and time-series analysis. Train and validate models directly in Power BI and automate them using AutoML.
• Access Insights 24*7: Gain in-app analytics with embedded insights and stay connected with the Power BI Mobile app. Keep informed with periodic data refreshes and consistent tile caching in the background.
• Perform Complex Queries: Gain information with a click using the Get Quick Insights option in Power BI. Take advantage of in-memory analytics and live connection to shared datasets in the Power BI Service.
• Scale Seamlessly: Add computing, memory and storage with Premium P1, P2 and EM3. Premium is a capacity hybrid cloud model. Azure Synapse Analytics provides scalability to the platform.

Primary Features

• Dashboards: Tell a data story by combining contextual data on a single screen. Dashboards are available in the Power BI service only. The mobile app enables viewing and sharing dashboards, but authoring isn’t available.
• Offline Mobile Mode: Stay updated when out of the office — interact with previously accessed dashboards when offline. Power BI Mobile provides only read-only report access in offline mode.
• Streaming Analytics: Incorporates information from IoT devices by integrating with Azure Stream Analytics and Azure IoT Hub.
• No-Code Guided Analysis: Drag and drop data objects to build complex queries without needing to know SQL. Connect to sources, build data models and load them into Power BI with easy user actions in the query editor.
• Data Modeling: Feed visualizations by mapping data relationships. Build reusable data models with SQL Server Analysis Services.

Limitations

• Microsoft limits individual dataset storage to 1 GB in the Pro edition.
• It doesn’t display visuals if not rendered within 225 seconds.
• Power BI Premium has concurrency limits for each session and applies throttling once it reaches the query limit, impacting performance.

Features Not Fully Supported According to Our Data

• Sentiment Analysis — Supported With Additional Modules
• Animations — Supported With Custom Development
• Geocoding — Supported With Partner Integrations
• IoT Analytics — Supported With Additional Modules
• Text-Based Natural Language Reports — Supported With Partner Integrations

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Oracle Analytics Cloud (OAC)

It’s a cloud service providing data analysis and business intelligence in the Oracle Cloud. Scalable and collaborative, it supports a mobile app and natural language processing (NLP) capability.

It’s available as a subscription model based on service tiers and user count. OAC integrates custom scripts in Python and R to create advanced, complex visualizations.

Intelligent recommendations enable data enrichment and guided analysis. You can perform text searches for objects, reports and visualizations or directly query data sources. OAC supports 28 languages.

Visual data analysis makes cloud analytics platforms accessible to all users. Source

Highest Rated Modules According to Our Data

• Dashboarding and Data Visualization — 97
• Data Management — 95
• Reporting — 93
• Mobile BI — 90
• Advanced Analytics — 89

Top Benefits

• Boost Your Bottom Line: Pay for what you use and scale according to the workload. Save time with automated data refreshes and report generation. Capitalize on opportunities with automated alerts.
• Build Data Stories: Convey insights with interactive data dashboards, pre-built templates, powerful visualizations and AI capabilities, thanks to the Oracle Cloud Infrastructure.
• Integrate With Oracle Applications: Supports Oracle’s HCM, ERP and CRM software. Save time with pre-built data models and take advantage of the robust security of the Oracle Cloud.
• Stay Performant: Gain consistent, fast performance with elastic scaling and a cloud-native design. Supports regression, scenario and what-if analysis and provides statistical functions. Built-in augmented data prep is available.
• Gain Customer Analytics: Perform segmentation and cohort analysis by aggregating data from multiple sources. Limited out-of-the-box support for sentiment and text analysis is available.

Primary Features

• Interactive Dashboards: Embed dashboards using JavaScript libraries and iFrames. Configure user actions to drill down, add/remove columns, create calculated items and hide or display subtotals.
• Data Exploration: Eliminate guesswork with the Explain feature. Uncover key drivers, identify buyer segments and discover anomalies. Analyze financial, sales and operational data and evaluate campaign performance.
• Data Querying: Supports complex and scheduled queries, multi-pass SQL and live connection to data sources.
• Mobile App: Day by Day is Oracle’s native mobile app and provides dashboarding, reporting, offline access, geospatial analysis, push notifications and alerts.
• Reporting: Get ad hoc reporting, scheduled delivery, built-in alerts, conditional formatting, interactivity, exporting and voice-based report generation.

Limitations

• Small and mid-sized businesses may find it expensive.

Features Not Fully Supported According to Our Data

• Scenario and What-if Analysis — Supported With Additional Modules
• Sentiment Analysis — Moderately Supported Out of the Box
• Batch Updates — Not Supported
• IoT Analytics — Supported With Additional Modules
• Mapping and Maps API Integration — Moderately Supported Out of the Box

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TIBCO Spotfire

Spotfire is available as a cloud and SaaS tool that utilizes machine learning, natural language search and automation for augmented analytics. It offers data wrangling for cleaning and enriching data while analyzing it simultaneously.

Spotfire continuously indexes data sources and recommends related data for inclusion in analyses. It has a native R engine for predictive analytics, modeling, clustering and forecasting.

Spotfire X enables drill-down into micro levels for root cause analysis and applies text-mining algorithms to discover hidden relationships in non-numerical data (tables, documents and concepts).

View text reports and geospatial data in one view using cloud analytics platforms. Source

Highest Rated Modules According to Our Data

• IoT Analytics — 100
• Mobile BI — 100
• Data Management — 99
• Geospatial Visualizations and Analysis — 94
• Dashboarding and Data Visualization — 91

Top Benefits

• Boost Efficiencies: Gain insights faster — get started quicker with pre-built connectors and eliminate manual data integration. Spotfire has in-memory analytics, self-service dashboards and visual data exploration.
• Sell Better: Identify clusters of frequently bought-together products, revealing potential cross-sell opportunities. Maximize your returns by targeting high-potential customers with cross-sell campaigns.
• Scale Seamlessly: Manage workloads of any size with elastic scalability and extend functionality by integrating with other cloud services.
• Boost Efficiency: Promote team collaboration via shared dashboards in real time. Stay informed about content changes with versioning.
• Forecast Trends: Anticipate the expected and the unexpected with predictive and prescriptive analytics, thanks to ML algorithms.

Primary Features

• Pre-Built Connectors: Connect to over 200 sources. Spotfire supports live data querying on big data where it resides in databases. Or you can pull slices of data into the platform on demand.
• Regression Analysis: Supports regression, classification trees, time series and statistical functions. You can explore different results by changing values in formulas with sliders.
• AWS-Azure Integration: Perform sentiment analysis with language identification, text translation and key phrase extraction. Spotfire uses Python to connect to AWS and Azure.
• Embedded Analytics: Embed into websites, open Spotfire analyses from clickable links and integrate with other web apps. Third-party chart packages extend visual analysis capabilities.
• Mobile Insights: Supports mobile reports and dashboards, offline access, location analysis, notifications, alerts and QR code scanning.

Limitations

• Doesn’t provide voice-based reporting.
• Doesn’t support triggering workflows in the embedding application.

Features Not Fully Supported According to Our Data

• Sentiment Analysis — Supported With Partner Integrations
• Column-Level Security — Supported With Custom Development
• Augmented Data Preparation — Not Supported
• Contextual Insights — Not Supported
• Animations — Supported With Custom Development

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Qlik Sense

It’s a SaaS offering from the Qlik Cloud Analytics platform that can consolidate Qlik Sense, QlikView and other BI apps in a single hub. It utilizes data storytelling and an object library for advanced visualizations.

Real-time data analytics, drag-and-drop source connectivity, collaboration options and an associative engine characterize the solution. The Insight Advisor provides guided data discovery and model analysis.

Qlik Sense Automatically processes datasets with features like derived fields, binning, and concatenation. Qlik Management Console serves as a central administration point.

Cloud analytics platforms provide NLG functionality like the Insight Advisor. Source

Highest Rated Modules According to Our Data

• Dashboarding and Data Visualization — 100
• Data Management — 100
• Mobile BI — 93
• Data Querying — 92
• Advanced Analytics — 91

Top Benefits

• Gain a Competitive Edge: Improve operations with performance tracking. Build apps without needing additional development and allocate resources realistically.
• Accelerate Analytics: Discover critical insights with no-code visual tools and a user-friendly interface. Delegate information-gathering to machine learning and perform guided analysis with intelligent recommendations.
• Deploy Flexibly: Use the solution in private or public clouds, including on Kubernetes.
• Access From Anywhere: Stay updated via mobile browsers and apps on mobile phones and iPads. Download Qlik apps entirely or in part when offline.
• Get Value Addition With Qlik Products: Draw on the extensive Qlik suite for conversational analytics, location data and indexing using Qlik NPrinting, Qlik Big Data Index, Qlik GeoAnalytics, Qlik DataMarket and Qlik InsightBot.

Primary Features

• Data Connectivity: Connect to custom sources, big data lakes, and cloud and on-premise applications through ODBC, OLE DB and REST APIs. Integrates with Microsoft, SAP, Snowflake, Salesforce, AWS and GCP out of the box.
• Efficient In-Memory Storage: Analyze large datasets without lag — minimize retrieval time with in-memory storage. Compute data at lightning-fast speed, thanks to Qlik’s associative engine.
• User-Friendly Environment: Create dashboards and explore data with drag-and-drop functionality, associative searches and data storytelling tools.
• Predictive Analysis: Build and deploy predictive models independently using Qlik AutoML. Forecast trends by training models and interpreting Smart Load Charts that auto-predict anticipated values within visualizations.
• Embedded Analytics: Access and analyze data directly within workflows in CRM, eCommerce and helpdesk solutions using iFrames, JavaScript libraries and APIs.

Limitations

• Qlik Sense isn’t available natively on Linux and Mac OS.
• Performance can suffer when working with large datasets.

Features Not Fully Supported According to Our Data

• Scan Machine Readable Codes — Supported With Custom Development
• Geospatial Functions and Calculations — Supported With Additional Modules
• Integrated Workflow Actions — Supported With Custom Development
• Key Driver Analysis — Moderately Supported Out of the Box

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Dundas BI

It’s a SaaS analytics platform made to embed from the ground up. The application is available for single and multi-tenant deployments with shared, reusable content.

In-memory analysis, JavaScript-enabled extensibility and white-labeling are its stellar features. The vendor provides HTML5 compatibility for customizable visualizations and user-friendly dashboards.

Secure write-backs are available via custom forms, stored procedures and REST APIs. A free trial is available.

Get the complete picture with dashboards in cloud analytics platforms.

Highest Rated Modules According to Our Data

• Dashboarding and Data Visualization — 100
• Data Management — 100
• Embedded Analytics — 100
• Reporting — 96
• Advanced Analytics — 92

Top Benefits

• Acquire Two for the Price of One: Get dashboarding and reporting in one package — no hidden charges. Additionally, periodic data refreshes don’t cost extra.
• Analyze Complex Data: Generate comprehensive insights using statistical analysis and forecasting. Include all data types, whether numbers, strings or location coordinates.
• Gain Live Insights: Pull data in real time from visualizations and datasets in other dashboards and refresh it on demand or per schedule.
• Create Custom Reports: Design reports on the fly — define headers and footers and list nested and repeating groups. Prevent data silos with versioning and share reports using email and API calls.
• Keep Data Secure: Centralized monitoring, audit trails, encryption and robust authentication provide data quality assurance. Dundas supports OpenID Connect, SSO, SAML 2.0, Kerberos and Active Directory.

Primary Features

• Open Architecture: Get browser compatibility with JavaScript, HTML5 and CSS3. Automate workflows and add custom functions, transforms, controls and content delivery providers.
• Dashboards: Share data using pixel-perfect report designs, animations, pre-defined widgets and templates.
• Multi-Tenant Support: Keep objects, connectors, reports and dashboards exclusive while sharing computing and storage with other tenants. You can opt to store data separately if using the Dundas warehouse.
• Globalization: Configure culture-aware displays — define the user language, country and data viewing preferences in the platform settings. Format numbers, dates, times and settings according to the location.
• Integrations: Fully supports Apache Hive, Spark SQL, Google BigQuery, Salesforce, Microsoft Dynamics, HubSpot, SQL Server, MySQL, PostgreSQL and IBM DB2.

Limitations

• Offline mobile mode isn’t available.
• Doesn’t support 3D charts out-of-the-box.

Features Not Fully Supported According to Our Data

• PMML — Not Supported
• Augmented Data Prep — Not Supported
• IoT Analytics — Moderately Supported Out of the Box
• Voice-Based Natural Language Search — Supported With Partner Integrations
• Scan Machine-Readable Code — Supported With Custom Development

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How We Choose Products

Our team of writers and analysts at SelectHub is committed to giving you the best recommendations based on our data. To make our list, products had to meet two criteria:

1. Closely match the topic
2. Earn a top-5 analyst score in our selection platform

Our analyst scores are based on an in-depth research process using primary and secondary sources. This includes SelectHub Analyst Briefings, direct communication with vendors, and reviewing materials such as user reviews, product brochures, specification sheets, case studies, user manuals, and technical documentation.

Our platform’s Scoring Engine processes the research and computes the analyst score. The score also factors in platform settings such as industry and company size.

Cloud Software vs. SaaS

Similarities:

• Both are cloud-based, eliminating the need for on-premise infrastructure.
• Both offer data analysis and some level of data visualization.
• You can access both from anywhere with an internet connection.
• Examples include Amazon Redshift, Google BigQuery and Azure Synapse Analytics.

Differences:

• Cloud analytics software focuses on computing, storage and infrastructure, while SaaS analytics software provides business reporting.
• Cloud systems are more complex, requiring technical expertise.
• Cloud analytics platforms can be more expensive.
• SaaS offers limited customization compared to cloud platforms.
• Examples include Tableau Online, Microsoft Power BI, Domo and Zoho Analytics. Read our Best SaaS Reporting Tools article to learn more.

Hybrid Cloud vs. Multi-Cloud Platforms

A hybrid cloud provides greater control over data storage while offering the scalability and speed of the cloud. However, managing on-premises and cloud environments, including data security, is resource-intensive.

Additionally, vendor lock-in can limit future flexibility.

A multi-cloud setup includes private and public clouds, sometimes more than two.

According to this Oracle Report, till 2023, 45% of multi-cloud enterprises opted for over five providers. Advantages of a multi-cloud setup include vendor lock-in avoidance, workload optimization and redundancy.

Every coin has two sides, and so does multi-cloud deployment. Balancing costs across providers requires intelligent planning. Securing data and applications across cloud environments can be complicated.

Choosing between a hybrid or multi-cloud solution can be complex. Here’s some advice to help you make an informed decision.

Assess your needs and priorities.

• Consider factors like scalability, security, data storage, compliance requirements and budget.
• What are your existing IT infrastructure and resources? Do you have on-premises hardware and expertise? Are you cloud-based?
• Do you require complete control over your environment, or are you open to a managed service?

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Software Selection Tips

Consider your future growth plans. Choose a solution that can scale and adapt to your future requirements.

Are you planning to expand to new markets? Multi-cloud offers better global reach and data storage options.

Factor in the following considerations.

• Security: Verify server data encryption and privacy practices. Understand the location of your data and the applicable data governance policies.
• Reliability & Performance: Ask if the cloud analytics software is reliable and performs well, especially with large data uploads. Check for historical downtime records and user reviews. Utilize free trials to test the platform’s performance before making a final decision.
• Features: Check for incorporating artificial intelligence and other advanced capabilities. Understand data processing limitations and evaluate third-party integration capabilities.
• Cost: Understand the pricing structures, whether per user, user group, monthly, annually or long-term contracts. Consider the cost of scaling and determine if the pricing aligns with your current and future budget.

Evaluate cloud providers by researching their reputation, track record and compliance certifications. Talk to industry peers and read user reviews.

Read our Lean Software Selection Methodology article for a step-by-step guide.

Cost Considerations

A subscription gives you usage rights with recurring fees for software updates and support, while a perpetual license grants indefinite access after a one-time purchase.

Subscription plans include the following flavors.

• Tiered Subscriptions: Different tiers offer varying features and functionalities, catering to diverse user needs and budgets.
• Volume Discounts: They depend on the number of licenses or units purchased. The more licenses purchased, the lower the cost per license.
• Freemium Model: It provides basic features for free, with premium features accessible through paid subscriptions.
• Usage-Based Billing:
  • Pay-As-You-Go: Pay only for the consumed storage or bandwidth — an excellent plan for unpredictable usage patterns. Be prepared for spikes in usage.
  • Committed Use Discounts: Committing to a specific level of resource usage upfront can lead to substantial discounts.
• Concurrent Use Licensing: It restricts the number of users who can access the software simultaneously and is useful if not all users need constant platform access.

Transferability and Upgrades

• License Transferability: Some licenses allow transfer to another user or organization. Check the vendor’s license agreement for terms.
• Upgrade Costs: Upgrades to newer versions may require additional purchases or fees, impacting long-term software maintenance costs.

Hidden Costs and Considerations

• Data Transfer Fees: Egress charges for data transfer outside the allowed network or volume limit can add hidden costs.
• Contract Lock-in: Long-term contracts can restrict flexibility and complicate switching providers.
• Automatic Renewal: Subscription fees automatically renew unless explicitly canceled, requiring vigilance.
• Support Fees: Technical support may not be part of the initial license purchase and may require additional fees.

The Tableau Viewer license costs $15 per user monthly, billed annually. Teradata Vantage starts at $5 hourly for computing and 19 cents per terabyte hourly for storage.

In 2022, the annual cost of an analytics stack for large enterprises was between three to eight million dollars.

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Next Steps

Cloud analytics platforms or SaaS tools — which should you choose?

Choose cloud analytics software if you need large dataset processing, robust manipulation capabilities and advanced analysis. You can still create powerful reports and dashboards.

Use SaaS analytics software if you need business reporting with a quick and easy-to-use solution and have a limited IT budget.

Ultimately, evaluating your specific needs and comparing the features and benefits of cloud and SaaS analytics software options is the best decision-making strategy.

Start your software selection journey with an advantage. Get our free comparison report to evaluate your preferred products for features you want.

Which cloud analytics tools have you used? How was your experience? Do let us know in the comments.