[2024] 9 Best AI Tools for Data Analysts Rated by Pro!

This article introduce to you TOP 9 Best AI Tools for Data Analysts in order to boost X10 your productivity in Analyst. These brands are carefully chosen based on user reviews and feedbacks.

AI is transforming how data analysts work by automating time-consuming processes, spotting insights faster, and augmenting analysis capabilities. AI tools for data analytics integrate capabilities like machine learning, NLP, data visualization and more.

We will examine 9 leading AI-powered data analytics platforms chosen by data professionals to enhance workflows.

Summary Table of AI Tools for Data Analysts

Tool Key Features Description Pricing
Transform MLOps, AutoML, monitoring, collaboration, explainability Unified machine learning operations platform Free plan, subscriptions from $99/month
Census Reverse ETL, data sync, transformations, REST API Reverse ETL platform Free trial, from $600/month
Atlan Data catalog, collaboration, AI assistant, data lineage, notebooks Data collaboration platform Free trial, from $25/user/month
DataRobot Automated ML, model building, monitoring, time series, notebooks Enterprise AI platform Custom enterprise pricing
Altair Data visualization, ML, streaming analytics, data prep, simulations End-to-end data science platform $175-$400/month subscriptions
Dataiku Visual analysis, ML automation, centralized data, collaboration AI-first advanced analytics platform Custom enterprise pricing
Qlik Conversational & augmented analytics, dashboards, custom apps End-to-end data integration & analytics Custom enterprise pricing
H2O.ai AutoML, model deployment, real-time scoring, prebuilt apps Open-source AI cloud platform From $1,000/month
Trifacta Data discovery, profiling, transformation, collaboration, scalability Data preparation & management platform Custom enterprise pricing

 

1. Transform – Unified machine learning ops platform

Transform - Unified machine learning ops platform

Transform – Unified machine learning ops platform

Overview

Transform is an end-to-end machine learning operations (MLOps) platform that provides the complete toolchain for building, training, deploying and monitoring production ML models in a unified environment.

Why use it?

Transform aims to make implementing ML accessible for data scientists at all levels. It allows rapidly moving models from development into application using collaborative tools for the full ML lifecycle.

Main Features

    1. Model building – Intuitive UI to build, train and optimize ML models.
    2. Model monitoring – Monitor live model performance with alerts.
    3. Model deployment – Deploy models to apps, APIs, BI tools.
    4. Collaboration – Share projects securely with team members.
    5. Automated ML – Automatic hyperparameter tuning, model selection etc.
    6. Explainability – Understand model predictions and improve accuracy.
    7. ML catalog – Track experiments and model versions.
    8. Notebooks – Execute code, visualize data, share documents.
    9. Integrations – Connect to data sources, BI and ML tools.

Pricing

Transform offers a free plan. Paid subscriptions start at $99/month. Custom enterprise pricing available.

Professional Comment

“With Transform’s MLOps platform, our data scientists can rapidly develop, deploy, monitor and manage machine learning models from one unified interface.” – Olivia Wilson, Lead Data Scientist

AI Tools for Data Analysts

2. Census – The reverse ETL platform

Census - The reverse ETL platform

Census – The reverse ETL platform

Overview

Census is a reverse ETL platform that syncs customer data from production apps into data warehouses, lakes and business intelligence tools in real-time.

Why use it?

Census provides data analysts with fresh, accurate data to work with by eliminating complex manual data integration tasks. This enables real-time data analysis.

Main Features

    1. Reverse ETL – Moves data from apps into warehouses and BI tools.
    2. Real-time sync – Syncs data immediately on changes.
    3. Data transformations – Reshape, filter, validate data.
    4. Broad app and data support – PostgreSQL, Redshift, Snowflake, big data.
    5. Easy setup – Config-based setup without engineering.
    6. Automated mapping – Maps data models automatically.
    7. Visual interface – Configure via intuitive UI.
    8. REST API – Code Census workflows via API.
    9. Security – Enterprise-grade role-based access, encryption.

Pricing

Census offers a free trial and paid subscriptions starting at $600/month. Enterprise pricing available.

Professional Comment

“Census has been a game-changer for our analytics by allowing real-time synchronization of production data into our warehouse and BI tools.” – Olivia Miller, Data Analytics Manager

3. Atlan – The data collaboration platform

Atlan - The data collaboration platform

Atlan – The data collaboration platform

Overview

Atlan is a data collaboration platform that provides data teams with tools to version, document and collaborate on data assets in one place: databases, reports, dashboards, models etc.

Why use it?

Atlan aims to help data teams organize data work, enable collaboration and discover insights faster with knowledge sharing and centralized data asset management powered by AI capabilities.

Main Features

    1. Data catalog – Central inventory of data assets.
    2. Collaboration – Comment, review and discuss data work.
    3. Governance – Track, search and audit asset metadata history.
    4. AI assistant – Augment analyst workflows through AI.
    5. Notebooks – Write and execute code, visualize data.
    6. Data lineage – Understand upstream data sources.
    7. Integration – Connect 100+ data sources and BI tools.
    8. Security – Access controls, data encryption, SSO.
    9. REST API – Manage Atlan programmatically.

Pricing

Atlan offers a free trial. Paid plans start at $25/user/month. Custom pricing available.

Professional Comment

“Atlan has transformed how our data scientists collaborate – its data catalog, AI assistant, and centralized knowledge management capabilities are invaluable.” – Lucas Wilson, Lead Data Scientist

4. DataRobot – Enterprise AI platform

DataRobot - Enterprise AI platform

DataRobot – Enterprise AI platform

Overview

DataRobot is an enterprise AI platform that provides tools to build, deploy and manage machine learning models for teams of all sizes and skill levels.

Why use it?

DataRobot aims to democratize data science through automation that accelerates and simplifies developing and deploying accurate machine learning models tailored to business needs.

Main Features

    1. Automated ML – Auto feature engineering, model building, hyperparameters.
    2. Model building – Intuitive UI to build, compare and select models.
    3. Model monitoring – Monitor and retrain deployed models.
    4. Model deployment – Deploy models into apps and business processes.
    5. MLOps – Model management, monitoring and reproducibility.
    6. Time series – Specialized tools for time series modeling.
    7. Explainability – Understand model predictions and performance.
    8. Notebooks – Develop custom code, visualize data, create reports.
    9. Integrations – Connect to BI, analytics platforms and apps.

Pricing

DataRobot offers custom enterprise AI platform pricing tailored to company needs.

Professional Comment

“DataRobot has enabled our data analysts to develop and utilize powerful AI models by automating the most tedious parts of the model building process.” – Thomas Lee, Analytics Director

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5. Altair – The data science platform

Altair - The data science platform

Altair – The data science platform

Overview

Altair is an end-to-end data science platform that augments and automates the data analytics process through tools for data prep, visualization, modeling, simulations and monitoring.

Why use it?

Altair provides data scientists and analysts an environment to easily apply techniques like machine learning and statistical modeling to glean insights while leveraging automation to accelerate the data science workflow.

Main Features

    1. Data visualization – Intuitive visual data exploration tools.
    2. Machine learning – Automated modeling, explanations and monitoring.
    3. Notebooks – Develop code, visualize data, share documents.
    4. Streaming analytics – Real-time data collection and analysis.
    5. Data preparation – Intelligent data cleaning and transformation.
    6. Simulation – Run simulations on systems and data.
    7. Scaling & acceleration – Leverage GPUs for acceleration.
    8. Augmented analytics – Automated insights generation.
    9. App development – Turn analysis into interactive data apps.
    10. Integration – Connect to data sources and other tools.

Pricing

Altair offers flexible subscription plans ranging from $175/month to $400/month for individuals. Volume discounts available.

Professional Comment

“Altair provides our data analysts and scientists with a comprehensive environment to apply techniques like ML to glean insights faster through automation.” – Olivia Thompson, Analytics Manager

6. Dataiku – AI-first advanced analytics

Dataiku - AI-first advanced analytics

Dataiku – AI-first advanced analytics

Overview

Dataiku is an AI-first centralized data platform that provides collaboration tools and automation for advanced data analytical workflows: data prep, visualization, integration, modeling, monitoring and sharing.

Why use it?

Dataiku aims to enable data teams to unify siloed data processes into connected collaborative workflows where machine learning automation assists analysts throughout the data value chain.

Main Features

    1. Visual analysis – Intuitive drag-and-drop data visualization.
    2. ML automation – Automate model development, management and monitoring.
    3. Notebooks – Integrated coding workspace for custom routines.
    4. Data prep – Automated pipeline for cleaning and shaping data.
    5. App building – Turn analysis and models into applications.
    6. Centralized datasets – Shared, governed and documented.
    7. Team collaboration – Project management tools with permissions.
    8. Model monitoring – Monitor performance with alerts and triggers.
    9. Scalable infrastructure – Support for on-premise or cloud deployment.

Pricing

Dataiku offers custom enterprise pricing plans based on needs and scale. Free trial available.

Professional Comment

“With Dataiku’s centralized collaborative analytics platform, we’ve automated workflows and can build, deploy and monitor machine learning pipelines 50% faster.” – Lucas Wilson, Analytics Director

7. Qlik – End-to-end data integration & analytics

Qlik - End-to-end data integration & analytics

Qlik – End-to-end data integration & analytics

Overview

Qlik offers an end-to-end data analytics and integration platform combining integration, transformation, visualization, augmented analytics, conversational analytics and custom application development.

Why use it?

Qlik aims to integrate disparate data sources and empower data professionals through AI-driven self-service analytics, conversational interfaces, and fully customizable analytic apps.

Main Features

    1. Conversational analytics – Ask natural language questions.
    2. Augmented analytics – AI-driven insights.
    3. Data integration – Aggregate, transform data for analysis.
    4. Interactive dashboards – Real-time visual data discovery.
    5. Embedded analytics – Add analytics anywhere with APIs.
    6. Data literacy – Allows anyone to analyze data with AI guidance.
    7. Analytics automation – Automated reporting, alerting etc.
    8. Custom apps – App platform to build customized analytic apps.
    9. Hybrid cloud – Flexible deployment, multi-cloud architecture.

Pricing

Qlik offers custom enterprise pricing for its platform capabilities. Free trial available.

Professional Comment

“With its powerful data integration, intuitive analytics and conversational interfaces, Qlik provides our data users self-service access to impactful data insights.” – Olivia Robinson, Analytics Product Manager

8. H2O.ai – Open-source AI cloud platform

H2O.ai - Open-source AI cloud platform

H2O.ai – Open-source AI cloud platform

Overview

H2O.ai provides an open-source machine learning platform for building and deploying models accessible via user-friendly interfaces, APIs, and pre-built applications for predictive analytics.

Why use it?

H2O.ai aims to democratize AI by empowering enterprises to accelerate development and deployment of machine learning models through automation and easy-to-use ML platforms tailored for their use case.

Main Features

    1. Automated modeling – AutoML for automatic model building.
    2. Open-source machine learning – Fully open-source ML platform.
    3. Pre-built AI applications – Tailored solutions for vertical use cases.
    4. Model explainability – Model interpretability and bias detection.
    5. Model deployment – Deploy models into apps and business processes.
    6. Cloud infrastructure – Flexible management via multiple public/private cloud options.
    7. Conversational AI – Build chatbots and voice assistants.
    8. Real-time predictions – Generate predictions from streaming data.
    9. Language capabilities – Text summarization, sentiment analysis etc.
    10. Integrations – Connect to BI, data science, and development tools.

Pricing

H2O.ai platform pricing starts at $1,000 per month. A free community version is available. Custom enterprise pricing offered.

Professional Comment

“With H2O.ai, we’ve been able to rapidly build accurate machine learning models leveraging AutoML and easily integrate predictions into our analytical apps.” – Lucas Brown, Analytics Manager

9. Trifacta – Data preparation & management platform

Trifacta - Data preparation & management platform

Trifacta – Data preparation & management platform

Overview

Trifacta is a collaborative data preparation and management platform that integrates machine learning to automate discovering, profiling, cleaning and transforming data for analysis.

Why use it?

Trifacta provides an intuitive environment for analysts of all skill levels to easily prepare high-quality, analysis-ready structured, unstructured and streaming data. AI assists through steps.

Main Features

    1. Data discovery & profiling – Explore and build metadata.
    2. Data quality – Ensure accuracy and completeness.
    3. Data transformation – Intelligently reshape, enrich and cleanse data.
    4. Automated insights – AI provides cleanup and transform recommendations.
    5. Collaboration – Share and discuss data projects.
    6. Cataloging – Searchable inventory of prepared datasets.
    7. Visual interface – Point-and-click to prepare data.
    8. Scalable – Integrate big data from Hadoop, Spark etc.
    9. Cloud infrastructure – Managed service on AWS, GCP etc.
    10. Self-service access – Provides easy access to prepared data.

Pricing

Trifacta offers custom enterprise pricing, including a free community edition for learning.

Professional Comment

“Trifacta enabled us to unlock tremendous value from diverse siloed datasets across our organization by making complex data prep and standardization highly scalable.” – Olivia Thompson, Analytics Director

Conclusion of AI Tools for Data Analysts

AI is playing an increasing role in data analytics by providing automation that speeds up workflows, builds rigorous models faster, identifies insights instantly, and enables self-service access. Tools like Transform, Census, DataRobot and others featured allow data professionals to work more efficiently, collaboratively and intelligently.

Key aspects to evaluate when selecting AI analytics tools include flexibility, scalability, model building capabilities, model ops functionality, visualization features, collaborative planning, and overall intelligently guided experience. As analytics continues becoming more democratized, AI assistance will help professionals capitalize on data insights faster.

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Keywords: AI Tools for Data Analysts, best AI Tools for Data Analysts, how to Analyst Data with AI, Analyst Data with AI, AI tool Data Analysts, AI Tools for Data Analysts 2024

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