Top 25 Data Management Tools for Modern Businesses

Data is everywhere, but making sense of it? That’s the real challenge. 

With systems that don’t talk to each other and processes that drain time, business analysts and IT managers often find themselves firefighting instead of innovating.

Enter data management tools. 📊

In this guide, we’re spotlighting 25 of these modern software solutions that can simplify your workflow and get your data under control.

Let’s start with how to pick the perfect tool for your needs.

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Here’s our roundup of the 25 best data management tools available today:

1. ClickUp: Best for AI-powered, team-centric data management

2. Informatica: Best for scalable data integration and governance

3. Talend: Best for versatile cloud-based data integration

4. IBM Cloud Pak for Data: Best for AI-driven, cloud-native data solutions

5. Amazon Web Services: Best for scalable cloud data storage and analytics

6. Google Cloud: Best for real-time data pipelines and AI analytics

7. Oracle Autonomous Database: Best for automated master data management

8. Snowflake: Best for multi-cloud data warehousing and data sharing

9. Denodo Platform 9.1: Best for data virtualization and unified access

10. SAP Data Intelligence: Best for complex data orchestration 

11. Microsoft Purview: Best for hybrid data governance 

12. Collibra Data Intelligence Cloud: Best for data cataloging and lineage tracking

13. Veritone Data Refinery: Best for AI-driven unstructured data analysis

14. Microsoft Azure AI Foundry: Best for AI model integration in data pipelines

15. Tableau: Best for intuitive data visualization and self-service BI

16. Qlik Sense: Best for associative data exploration and advanced analytics

17. Alteryx: Best for automating data prep and advanced analytics 

18. KNIME: Best for developing data science pipelines and ML models

19. Looker by Google: Best for unlimited data exploration and cloud BI

20. Polymer: Best for turning raw data into actionable dashboards

21: ASK BOSCO©: Best for conversational and voice-assisted analytics

22. DataRobot: Best for automating AI model development

23. H2O.ai: Best for open-source AI frameworks and scalable ML 

24. Akkio: Best for no-code AI predictions and real-time analytics

25. MonkeyLearn: Best for text data analysis using NLP

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What Should You Look for in a Data Management Tool?

A great data tool not only organizes information but also enables faster decision-making. Key features to seek are:

• Automation capabilities: Select a tool that handles repetitive tasks like data cleansing or reporting
• Real-time insights: Look for a tool that provides up-to-the-minute data analytics to keep your decisions relevant
• User-friendly interface: Pick a tool that’s intuitive for non-technical users but robust enough for IT professionals
• Strong security: Find a tool that takes necessary data security precautions for your sensitive information

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The 25 Best Data Management Tools

Explore these top master data management tools to do more with your data.

Comprehensive data integration and management tools

First up, let’s look at a list of comprehensive data integration and management tools:

1. ClickUp (Best for AI-powered, team-centric data management)

ClickUp, the everything app for work, brings data management strategy and team collaboration under one roof. Its AI-powered neural network, ClickUp Brain, automates repetitive tasks like data entry and real-time reporting while analyzing historical project data to predict future timelines. 

You can also ask Brain questions about existing projects and it will pull data from relevant tasks, docs, and chats to give you the latest, most relevant information.

ClickUp’s Custom Views and dashboards make it easy to organize and visualize key metrics, from workload allocation to budget management. It integrates smoothly with other tools—like Tableau and Salesforce—pulling diverse datasets together. 

Plus, ClickUp’s security policies ensure strong data governance and compliance using role-based access control and audit logs.

Customer data is hosted by Amazon Web Services (AWS), which is SOC 2 Type 2 certified and adheres to industry-specific security standards to maintain the security and compliance of the cloud. Moreover, ClickUp’s security teams routinely perform application, performance, and penetration testing to mitigate risks and data theft.

ClickUp best features

• Tracks project data via ClickUp Dashboards using 50+ custom attributes
• Offers robust KPI tracking via ClickUp Templates for managing data performance
• Enables smooth team collaboration via ClickUp Chat without switching apps

ClickUp limitations

• Offers a vast array of features, which can be slightly overwhelming

ClickUp pricing

• Free Forever
• Unlimited: $7/month per user
• Business: $12/month per user
• Enterprise: Contact for pricing
• ClickUp Brain: Add to any paid plan for $7 per user per month

ClickUp ratings and reviews

• G2: 4.7/5 (9,000+ reviews)
• Capterra: 4.6/5 (4,000+ reviews) 

2. Informatica (Best for scalable data integration and governance)

Informatica is one of the most popular scalable data management tools that help businesses turn scattered data sources into clear, actionable insights. Thanks to its cloud-native design and low-code/no-code functions, it’s flexible enough to work for everyone—from small startups to large enterprises.

The platform makes it easy to combine on-premises and cloud resources with its hybrid deployment options. Plus, features like change data capture (CDC) and event-driven architecture ensure smooth multi-source connectivity.

Informatica best features

• Unified data integration tools help you connect data from various sources, including traditional databases like Oracle, cloud platforms like Salesforce, and big data systems like Hadoop, all in real time
• Advanced data quality management identifies inconsistencies in datasets using data profiling, supported by automated data cleansing and custom quality rules
• Clear rules for data access ensure usage with data lineage tracking, compliance with regulations like GDPR and HIPAA, and role-based access control

Informatica limitations

• Doesn’t work well with dynamic datasets

Informatica pricing

• Custom pricing

Informatica ratings and reviews

• G2: 4.3/5 (100+ reviews)

3. Talend (Best for versatile cloud-based data integration)

Talend is a cloud-based data integration platform for mid-sized businesses to connect, and manage data from diverse sources into a unified, actionable format, simplifying data pipeline creation.  

Its open-source foundation allows data customization and collaboration through shared repositories and version control.  

Talend best features

• Extensive data integration capabilities with 1,000+ pre-built connectors for databases, cloud services, and applications, supporting both ETL and ELT processes 
• Comprehensive data quality management with built-in quality checks that let you define custom rules to cleanse and validate data during integration
• Master data management (MDM) solution that helps you govern critical data, providing a single, trusted view to improve data quality

Talend limitations

• Steep learning curve of its graphical interface

Talend pricing

• Custom pricing

Talend ratings and reviews

• G2: 4/5 (60+ reviews)
• Capterra: 4.3/5 (20+ reviews)

4. IBM Cloud Pak for Data (Best for AI-driven, cloud-native data solutions)

IBM Cloud Pak for Data is designed to facilitate AI-driven data and analytics solutions across hybrid cloud environments. It’s ideal for industries needing strong compliance in project management databases.

This modular platform helps you build a data fabric that connects siloed data across the entire data lifecycle—from collection and organization to analysis and model deployment. 

The platform is built on Red Hat OpenShift, ensuring that it can run in various environments, including on-premises, private clouds, and public clouds like AWS, Azure, and Google Cloud.

IBM Cloud Pak for Data best features

• Integrated data fabric offering advanced data virtualization, helping your team access and query data from multiple sources without moving it
•  AI-driven analytics integrating IBM Watson AI for advanced ML and NLP, and automated model evaluation using tools like Watson OpenScale
• Data governance supported by IBM Knowledge Catalog, helping you create a centralized metadata repository to classify, catalog, and manage data access 

IBM Cloud Pak for Data limitations

• Initial configuration can be complex

IBM Cloud Pak for Data pricing

• Custom pricing

IBM Cloud Pak for Data ratings and reviews

• G2: 4.3/5 (90 reviews)

5. Amazon Web Services (Best for scalable cloud data storage and analytics)

Amazon Web Services (AWS) is a cloud computing platform tailored for organizations of all sizes. 

AWS’s architecture is built for flexibility, letting you choose from a variety of storage options, including object storage with Amazon S3, relational databases with Amazon RDS, and NoSQL solutions with Amazon DynamoDB. 

Plus, it provides tools like serverless computing with AWS Lambda and automated scaling with EC2 to support a wide range of operational needs.

AWS best features

• Scalable storage with Amazon S3, including multiple classes like Standard and Glacier, advanced features like versioning and lifecycle policies, and S3 Storage Lens for insights
• Data analytics services, including Amazon Athena for interactive querying, Amazon Redshift for data warehousing, and Amazon Kinesis for real-time data processing 
• Data encryption for both at-rest and in-transit data, secure key management through AWS KMS, and activity tracking with AWS CloudTrail

AWS limitations

• Complex pricing structure can lead to unexpected costs

AWS pricing

• Free tiers
• Pay-as-you-go: Pricing varies by usage and instance type

AWS ratings and reviews

• G2: 4.7/5 (70+ reviews)

6. Google Cloud (Best for real-time data pipelines and AI analytics)

Google Cloud is ideal for industries needing high-speed, low-latency data processing for large-scale analytics. 

The platform integrates advanced AI tools, such as AutoML and TensorFlow, helping you use data for predictive analytics and intelligent applications. Additionally, Google Cloud’s serverless architecture simplifies the deployment of applications and workflows.

Another offering of Google Cloud is its integration of gen AI capabilities and large language models (LLMs), which allow teams to interact with data using natural language. LMs also boost productivity by providing code recommendations.

Google Cloud best features

• Pub/Sub functionalities for asynchronous communication between independent application components, designed for high throughput and low latency
• Advanced analytics with BigQuery offering a fully managed data warehouse for fast SQL queries on large datasets, processing petabytes with built-in machine learning (ML) capabilities
• Identity and access management (IAM) ensuring fine-grained resource access control, while data loss prevention (DLP) helps you discover, classify, and safeguard sensitive information

Google Cloud limitations

• Setting up permissions can get tricky when managing access for a team

Google Cloud pricing

• Free plan
• Pay-as-you-go: Pricing varies by usage and instance type

Google Cloud ratings and reviews

• G2: 4.5/5 (51,000+ reviews)
• Capterra: 4.7/5 (2,000+ reviews) 

7.  Oracle Autonomous Database (Best for automated master data management)

Oracle Autonomous Database automates many of the traditional database management tasks, making it ideal for organizations looking to simplify their MDM processes. 

Designed for both transactional (OLTP) and analytical (OLAP) workloads, this unified platform supports a wide range of data types. This capability helps you run a variety of applications—from online transaction processing systems to complex analytical queries—without needing separate database environments. 

Oracle Autonomous Database best features

• Automated MDM with self-driving capabilities that automates tasks like backups and scaling, integrates data from multiple sources, and maintains data quality with built-in profiling and cleansing tools
• Built-in ML capabilities that enable trend analysis across text, graphs, and spatial data using SQL-based queries 
• A self-securing architecture with continuous protection through automatic updates, robust encryption, and fine-grained access controls

Oracle Autonomous Database limitations

• Typically uses a lot of memory

Oracle Autonomous Database pricing

• Free tier
• Pay-as-you-go: Pricing varies based on product and usage

Oracle Autonomous Database ratings and reviews

• G2: 4.3/5 (900+ reviews)
• Capterra: 4.6/5 (400+ reviews)

8. Snowflake (Best for multi-cloud data warehousing and data sharing)

Snowflake is a cloud-native platform that helps with real-time access and tabular data storage in a unified data warehouse.

Designed to handle large volumes of structured and semi-structured data, Snowflake’s architecture supports independent scaling to meet varying workload demands.

The platform also complies with standards like HIPAA, PCI DSS, and GDPR, ensuring that organizations meet regulatory requirements for cloud data transfer.

Snowflake best features

• Cross-cloud support helps you operate across multiple cloud environments, giving you the flexibility to select the provider 
• Separation of storage and compute lets you scale storage and compute independently based on workload needs
• Built-in data sharing features enable secure sharing of live data with other Snowflake accounts without complex ETL processes, along with data marketplace integration for sharing datasets with external partners

Snowflake limitations

• Lacks native support for unstructured data

Snowflake pricing 

• Standard, Enterprise, Business Critical: Starts at $2/credit; price varies by region and platform
• On-demand storage: Starts at $20/TB per month; price varies by region
• Virtual Private Snowflake: Custom pricing

Snowflake ratings and reviews

• G2: 4.6/5 (500+ reviews)
• Capterra: 4.7/5 (80+ reviews)

9. Denodo Platform 9.1 (Best for data virtualization and unified access)

Denodo Platform 9.1 is a real-time data virtualization solution for organizations that need to work with a variety of datasets—such as JSON, XML, and traditional relational databases—within a single framework.

The platform uses a semantic layer to help you interact with the data without the need for complex ETL processes.

Denodo also ensures data security with robust features like data masking and encryption. Plus, it includes comprehensive audit trails with logging capabilities to track user activity and boost accountability.

Denodo Platform 9.1 best features

• Unified data access helps you connect to a wide range of data sources—including databases, cloud storage, and APIs—without needing to replicate or move the data
• The AI-powered Denodo Assistant with NLP capabilities helps you query data using natural language and provides intelligent recommendations
• Integration with the AI SDK for application development simplifies the inclusion of structured and unstructured data into gen AI data models while supporting Retrieval-Augmented Generation (RAG) 

Denodo Platform 9.1 limitations   

• Lacks a queue for transactions in case you want to save them because the source is down

Denodo Platform 9.1 pricing

• Custom pricing

Denodo ratings and reviews 

• G2: 4.1/5 (30+ reviews)

10. SAP Data Intelligence (Best for complex data orchestration)

SAP Data Intelligence is a data governance software tailored for organizations using SAP ecosystems, offering data orchestration across diverse systems.

One of its key strengths is the ability to manage the entire data lifecycle, from ingestion and processing to analytics and governance.

You can automate workflows and ensure that data is processed efficiently across different systems. The platform also emphasizes security and compliance, offering governance features like data lineage tracking. 

SAP Data Intelligence best features

• Pipeline modeling connecting SAP and non-SAP source systems, enabling real-time extraction, transformation, and enrichment of data
• Automated discovery and cataloging of structured and semi-structured data assets, along with smooth connectivity to a wide range of data sources (including streaming platforms)
• Integrated ML workflow management within a single interface, along with an AutoML functionality that automates the selection of algorithms and hyperparameters

SAP Data Intelligence limitations

• Integration with non-SAP applications is difficult

SAP Data Intelligence pricing

• Custom pricing 

11. Microsoft Purview (Best for hybrid data governance

Microsoft Purview supports project data governance templates and compliance for regulated industries, helping manage master data across hybrid and multi-cloud environments.

The platform provides a unified platform for data discovery, classification, and policy enforcement, offering businesses visibility into their data estates.

Plus, integration with the Microsoft ecosystem, including Azure Services, Microsoft 365, and Power BI, creates a cohesive environment for data governance initiatives.

Microsoft Purview best features

• Unified data governance framework including a data catalog with metadata from various sources, automated data discovery across on-premises and cloud environments, and data lineage view
• Automated data classification using ML algorithms, custom sensitivity labels, and integrations with DLP functions to prevent unauthorized access
• eDiscovery capabilities like advanced indexing for searchable content, conversation threading to organize messages from Microsoft Teams, and predictive coding based on prior coding decisions

Microsoft Purview limitations

• API could be improved for better connectivity with non-Microsoft API sources

Microsoft Purview pricing

• Free

Microsoft Purview ratings and reviews

• G2: 4.6/5 (20 reviews)

12. Collibra Data Intelligence Cloud (Best for data cataloging and lineage tracking)

Collibra Data Intelligence Cloud focuses on data privacy and lineage management, which is ideal for businesses managing complex datasets.

The platform makes it easier to create a complete view of data, ensuring you can quickly find, understand, and trust the information you need. Plus, it includes collaboration tools like commenting and sharing so teams can work together more effectively.

The updated Workflow Designer further boosts business process automation, making it even easier to consolidate data management.

Collibra Data Intelligence Cloud best features

• Data cataloging on an intuitive interface for easily accessing datasets, automatically capturing metadata, and enriching the catalog with context about ownership and usage
• End-to-end lineage visualization tracking data from source to destination, showing transformations and processes it undergoes, along with impact analysis 
• Integration of AI models with trusted datasets, alongside tools like Power BI and Tableau for advanced analytics, and access to a data marketplace for curated datasets

Collibra Data Intelligence Cloud limitations

• Deploying across an entire organization can be challenging 

Collibra Data Intelligence Cloud pricing

• Custom pricing

 Collibra Data Intelligence Cloud ratings and reviews

• G2: 4.3/5 (80+ reviews)

13. Veritone Data Refinery (Best for AI-driven unstructured data analysis)

Veritone Data Refinery is designed to turn large volumes of raw, unstructured data—like video, audio, and text—into structured datasets ideal for training advanced AI models like LMMs and LLMs.

By applying domain-specific metadata tags, the platform boosts searchability and provides additional context, making it easier for users to find and use the right datasets for their specific needs.

Veritone Data Refinery best features

• Data silos consolidation into a single actionable repository, ensuring compliance with GDPR and SOC2 standards, along with intellectual property optimization
• Enhanced monetization opportunities using third-party data licensing of refined datasets, custom AI solutions, and a suite of 20+ apps across various sectors
• Integration with the aiWARE™ platform for a comprehensive AI ecosystem helping with the deployment of AI solutions across different apps with real-time analytics

Veritone Data Refinery limitations

• Being a new platform, its success depends on how quickly enterprises adopt it

Veritone Data Refinery pricing

• Custom pricing

14. Microsoft Azure AI Foundry (Best for AI model integration in data pipelines)

Microsoft Azure AI Foundry helps simplify the integration of AI models into a fully managed data pipeline, perfect for organizations looking to harness AI effectively. 

The platform supports the entire lifecycle of AI application development by building collaboration among data scientists, developers, and IT professionals. 

It also incorporates ethical guidelines to mitigate risks related to bias and unfairness in AI solutions and includes safety filters that evaluate model outputs for accuracy.

Microsoft Azure AI Foundry best features

• Unified development environment with an integrated toolchain combining Azure services, prebuilt app templates, and collaboration features 
• Advanced model management featuring a model catalog for exploring pre-trained models, complete with evaluation tools and version control
• Connection to Azure Services like Azure OpenAI, Azure Machine Learning, and Azure Data Factory, integrating data pipelines into AI workflows

Microsoft Azure AI Foundry limitations

• Safety evaluations currently don’t allow for plug-ins or extensibility

Microsoft Azure AI Foundry pricing

• Custom pricing

15. Tableau (Best for intuitive data visualization and self-service BI)

Tableau is one of the top data visualization tools for self-service analytics, offering quick, actionable insights. 

The platform helps with self-service business intelligence (BI), requiring no coding—you can easily create complex visualizations by dragging and dropping fields onto the canvas.

With Tableau Server and Tableau Cloud integrations, dashboards can be securely published, providing consistent data access to team members across the organization.

Plus, features like commenting and annotations help teams provide direct feedback on visualizations, while the mobile app ensures dashboards are accessible.

Tableau best features

• Interactive visualizations with features like filtering and drilling down into specific data points, and customizable dashboards for a comprehensive view of data
• Extensive data connectivity supporting cloud services, databases, spreadsheets, and big data platforms, with real-time access to live data sources
• Advanced analytical features, including predictive analytics for forecasting and trend analysis, geospatial analysis, and statistical functions like regression or clustering within visualizations

Tableau limitations

• Limited collaboration options beyond Tableau Server or Tableau Online

Tableau pricing

• Tableau Creator: $75/month per user
• Tableau Explorer: $42/month per user
• Tableau Viewer: $15/month per user

• Enterprise: Starts at $35/month per user
• Tableau+: Custom pricing

Tableau ratings and reviews

• G2: 4.4/5 (2,000+ reviews)
• Capterra: 4.6/5 (2,000+ reviews)

16. Qlik Sense (Best for associative data exploration and advanced analytics)

Qlik Sense offers associative data exploration and analytics, ideal for businesses looking to navigate data without the limitations of traditional query-based tools. 

It ensures that no data is overlooked, retaining all values in the analysis to uncover hidden opportunities. 

The platform empowers users across various roles with self-service capabilities, democratizing access to valuable insights.

Plus, its advanced integration with R and Python allows for the use of ML models and predictive analytics directly within Qlik, while its AI-powered insights further help with decision-making.

Qlik Sense best features

• Dynamic data relationships that highlight related data while graying out unrelated information, paired with exploratory analysis
• Interactive dashboards and visualizations featuring a drag-and-drop interface, real-time data updates, and storytelling capabilities
• Smooth data connectivity with broad support for various databases, cloud services, and big data platforms, enhanced by data blending and automated data preparation 

Qlik Sense limitations

• Requires manual reloading or refreshing of data

Qlik Sense pricing

• Client-managed services: Custom pricing
• Qlik Cloud Analytics: 
  • Standard: Starting at $825/month at 25 GB for 20 users
  • Premium: Starting at $2500/month at 50 GB for 20 users
  • Enterprise: Custom pricing

Qlik Sense ratings and reviews

• G2: 4.4/5 (900+ reviews)
• Capterra: 4.5/5 (200+ reviews)

17. Alteryx (Best for automating data prep and advanced analytics)

Alteryx is built to automate data preparation and advanced analytics, helping organizations efficiently prepare, blend, and analyze data from multiple sources.  

The platform helps users, from data analysts to business executives, simplify workflows and insights without extensive programming expertise.  

Plus, integration with popular visualization tools like Tableau and Power BI lets you publish insights directly into dashboards for broader organizational sharing.  

Alteryx best features

• Automated data preparation with a no-code visual interface, comprehensive data cleansing tools, and workflow automation for repetitive tasks
• Advanced analytics tools for predictive modeling using regression and classification techniques, spatial analytics, and integration with R and Python for extended functionality
• Unified data preparation for joining, unioning, or appending datasets from various sources, and fuzzy matching and join tools based on similar attributes

Alteryx limitations

• Lacks robust real-time multi-user collaboration features

Alteryx pricing

• Designer Cloud
  • Professional: $4950/year per user
  • Enterprise: Custom pricing
• Designer Desktop: Custom pricing

Alteryx ratings and reviews

• G2: 4.6/5 (600+ reviews)
• Capterra: 4.8/5 (90+ reviews)

18. KNIME (Best for developing data science pipelines and ML models)

KNIME is an open-source platform for developing data science pipelines and ML models, well-suited for data stewardship across industries.

It offers a user-friendly visual interface, enabling data scientists and analysts to create complex workflows without requiring extensive coding knowledge. 

The platform ensures traceability and reproducibility of data workflows, making it easier to track and replicate analyses. 

Plus, KNIME provides advanced ML support, including AutoML capabilities for automating model training and evaluation.

KNIME best features

• Visual workflow design connecting various nodes representing different data operations for a clear overview of the entire process
• Extensive integration with diverse data sources, including big data frameworks like Apache Spark
• Productionization and deployment features, available through KNIME Business Hub, help you transition workflows with tools for scheduling, monitoring, and automating processes

KNIME limitations

• Requires extensive configuration for simple Excel tasks

KNIME pricing

• KNIME Community Hub
  • Personal Plan: Free
  • Team Plan: $99/month
• Enterprise: Custom pricing

KNIME ratings and reviews

• G2: 4.4/5 (60+ reviews)
• Capterra: 4.6/5 (20+ reviews)

19. Looker by Google (Best for unlimited data exploration and cloud BI)

Looker by Google is a cloud-based BI platform with a user-friendly interface. Acquired by Google in 2019, it integrates into the Google Cloud Platform, providing you with a centralized, interactive hub for data analysis and reporting. 

The platform’s robust features cater to businesses of all sizes, helping them harness the full potential of data.

Looker by Google best features

• Advanced data modeling with LookML, Looker’s unique modeling language, helps define relationships within data and create custom metrics
• Integration with Google Cloud Services offers scalability, security features, and access to Google’s AI and ML tools for data mapping and custom configurations
• Native connection with Google BigQuery for real-time analytics, helps you perform real-time analytics directly on your data warehouse

Looker by Google limitations

• Reliance on LookML can create bottlenecks for self-service client reporting tools

Looker by Google pricing

• Platform Edition: Custom pricing
• User Licensing: Custom pricing

Looker by Google ratings and reviews

• G2: 4.4/5 (1,400+ reviews)
• Capterra: 4.6/5 (200+ reviews)

20. Polymer (Best for turning raw data into actionable dashboards)

Polymer is a real-time data visualization platform designed for businesses across various sectors, including e-commerce, marketing, and enterprise.

It helps integrate diverse data sources with project management analytics. Plus, its user-friendly interface allows anyone to explore data, create reports, and generate visualizations without a steep learning curve.

The platform also features a dynamic policy engine that helps you customize your security, including identifying and remediating exposed data while providing alerts for risky data-sharing activities.

Polymer best features

• AI-powered dashboard generation automatically creates insightful dashboards, letting you quickly visualize data while predicting outcomes based on historical and real-time data
• Integration with popular data sources like Google Analytics, Shopify, and Facebook Ads helps you gather and synchronize data from multiple platforms
• Robust security features that protect sensitive data like personally identifiable information (PII) and protected health information (PHI) across SaaS platforms

Polymer limitations

• Lacks essential data connectors

Polymer pricing

• Starter: $50/month per user
• Pro: $100/month per user
• Teams: $250/month per 3 users
• Enterprise: Custom pricing

21. ASK BOSCO® (Best for conversational and voice-assisted analytics)

ASK BOSCO® is an AI-powered analytics platform designed to boost conversational and voice-assisted reporting for marketers and agencies, offering a user-friendly interface and advanced ML capabilities.  

The platform’s predictive analytics capabilities help forecast future performance and allocate media spending, helping businesses make data-driven decisions about their marketing budget.

ASK BOSCO® best features

• The AI reporting suite automates report generation, helping you ask questions about data and receive insights, trends, and recommendations based on algorithmic modeling
• Conversion tracking, such as pixel-based tracking and server-to-server integration helps with detailed performance monitoring
• Audience segmentation and traffic analysis help target specific demographics based on behavior or preferences and assess traffic sources to evaluate performance across channels

ASK BOSCO® limitations

• Doesn’t always pull in the data correctly

ASK BOSCO® pricing

• Custom pricing

ASK BOSCO® ratings and reviews

• G2: 4.7/5 (40+ reviews)

Predictive analytics and machine learning tools

Looking for help with predictive analytics and machine learning? These tools can help you:

22. DataRobot (Best for automating AI model development)

DataRobot is an automated ML platform that simplifies the development and deployment of predictive models. Its user-friendly interface helps you integrate models into existing systems via REST APIs. 

The platform supports both batch and real-time predictions, providing the flexibility to meet diverse application needs. It’s particularly beneficial for organizations looking to leverage AI without requiring extensive expertise in data science. 

DataRobot best features

• Automated model selection and training that evaluates hundreds of algorithms in parallel upon uploading a dataset
• Advanced feature engineering generates new features from existing data to boost model performance
• Continuous optimization via tracking metrics like prediction accuracy and data drift, ensuring models adapt to changing conditions and remain reliable in dynamic environments

DataRobot limitations

• Lacks ETL (Extract, Transform, Load) capabilities

DataRobot pricing

• Custom pricing

DataRobot ratings and reviews

• G2: 4.4/5 (20+ reviews)

23. H2O.ai (Best for open-source AI frameworks and scalable ML)

H2O.ai is an open-source platform designed for AI and ML model development that is useful for industries where rapid, explainable AI is needed for personalization and risk assessment.

It integrates with popular programming languages like Python and R, and features a user-friendly web GUI called Flow, making it accessible for data scientists and developers of all skill levels.

H2O Wave further enhances the platform by helping with the development of interactive AI applications, simplifying the real-time building and deployment of models.

H2O.ai best features

• Advanced AutoML functionality that automates algorithm selection, hyperparameter tuning, and model evaluation, generating a leaderboard to help you quickly identify the best model 
• Flexibility in supporting distributed computing environments like Hadoop and Spark, with an in-memory architecture that scales linearly for enterprise-level applications
• Comprehensive algorithm support for a wide range of ML algorithms, including gradient boosting machines, generalized linear models, and deep learning frameworks

H2O.ai limitations

• Scaling large datasets introduces operational complexities

H2O.ai pricing

• Custom pricing

H2O.ai ratings and reviews

• G2: 4.5/5 (20+ reviews)

24. Akkio (Best for no-code AI predictions and real-time analytics) 

Akkio is a no-code AI platform designed to democratize access to ML and predictive analytics for businesses of all sizes. 

It simplifies the model creation process with an intuitive drag-and-drop interface, helping you easily upload datasets and generate predictions. 

Plus, Akkio includes ongoing monitoring and automatic retraining features to maintain model accuracy over time.

Akkio best features

• AutoML technology automates the ML workflow, helping you quickly generate accurate models tailored to your specific needs
• Flexible deployment options help integrate AI models into existing systems whether through APIs or direct integration with popular business apps like CRM and e-commerce platforms
• The Chat Data Prep tool uses gen AI to automate data preparation tasks, acting like an intuitive chat interface that helps you interact with your data in a conversational manner 

Akkio limitations

• Needs the ability to retain training, avoiding the need to reboot at every conversation session

Akkio pricing

• User-level plans
  • View: Free
  • Basic: $49/month per user
  • Professional: $99/month per user
• Organization-wide plans
  • Build-on package: Starting at $999/month
  • Enterprise: Custom pricing

25. MonkeyLearn (Best for text analysis using NLP) 

MonkeyLearn specializes in text analysis through NLP, helping businesses extract valuable insights from unstructured text data like customer reviews, social media posts, and emails. 

The platform’s intuitive graphical user interface simplifies the model-building process, offering tutorials and a straightforward design that ensures users can browse the platform with ease.

MonkeyLearn best features

• Advanced sentiment analysis to gauge customer emotions and opinions expressed in text, helping you understand public sentiment about your products or services
• Custom model training helps you use your unique datasets to create relevant models, while the pre-trained models for tasks like keyword extraction and topic classification provide a quick and efficient start
• Integration with tools like Google Sheets, Excel, and Zapier simplifies incorporating text analysis into existing workflows

MonkeyLearn limitations

• Restricts the number of queries based on the subscription plan

MonkeyLearn pricing

• Starting at $299/month per feature

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