Best AI tools for< Cloud Data Engineer >

Lightup is a cloud data quality monitoring tool with AI-powered anomaly detection, incident alerts, and data remediation capabilities for modern enterprise data stacks. It specializes in helping large organizations implement successful and sustainable data quality programs quickly and easily. Lightup's pushdown architecture allows for monitoring data content at massive scale without moving or copying data, providing extreme scalability and optimal automation. The tool empowers business users with democratized data quality checks and enables automatic fixing of bad data at enterprise scale.

Qubinets is a cloud data environment solutions platform that provides building blocks for building big data, AI, web, and mobile environments. It is an open-source, no lock-in, secured, and private platform that can be used on any cloud, including AWS, Digital Ocean, Google Cloud, and Microsoft Azure. Qubinets makes it easy to plan, build, and run data environments, and it streamlines and saves time and money by reducing the grunt work in setup and provisioning.

Trifacta API Documentation provides reference information on all of the available endpoints for each product edition. This website does not factor disabled features or your specific account permissions. To review API documentation for the endpoints to which your account has access, please select Help menu > API Documentation from the Trifacta application menu.

Dflux is a cloud-based Unified Data Science Platform that offers end-to-end data engineering and intelligence with a no-code ML approach. It enables users to integrate data, perform data engineering, create customized models, analyze interactive dashboards, and make data-driven decisions for customer retention and business growth. Dflux bridges the gap between data strategy and data science, providing powerful SQL editor, intuitive dashboards, AI-powered text to SQL query builder, and AutoML capabilities. It accelerates insights with data science, enhances operational agility, and ensures a well-defined, automated data science life cycle. The platform caters to Data Engineers, Data Scientists, Data Analysts, and Decision Makers, offering all-round data preparation, AutoML models, and built-in data visualizations. Dflux is a secure, reliable, and comprehensive data platform that automates analytics, machine learning, and data processes, making data to insights easy and accessible for enterprises.

Alluxio is a data orchestration platform designed for the cloud, offering seamless access, management, and running of AI/ML workloads. Positioned between compute and storage, Alluxio provides a unified solution for enterprises to handle data and AI tasks across diverse infrastructure environments. The platform accelerates model training and serving, maximizes infrastructure ROI, and ensures seamless data access. Alluxio addresses challenges such as data silos, low performance, data engineering complexity, and high costs associated with managing different tech stacks and storage systems.

Pointly is an intelligent, cloud-based B2B software solution that enables efficient automatic and advanced manual classification in 3D point clouds. It offers innovative AI techniques for fast and precise data classification and vectorization, transforming point cloud analysis into an enjoyable and efficient workflow. Pointly provides standard and custom classifiers, tools for classification and vectorization, API and on-premise classification options, collaboration features, secure cloud processing, and scalability for handling large-scale point cloud data.

Neurelo is a cloud API platform that offers services for PostgreSQL, MongoDB, and MySQL. It provides features such as auto-generated APIs, custom query APIs with AI assistance, query observability, schema as code, and the ability to build full-stack applications in minutes. Neurelo aims to empower developers by simplifying database programming complexities and enhancing productivity. The platform leverages the power of cloud technology, APIs, and AI to offer a seamless and efficient way to build and run applications.

Global Nodes is a global leader in innovative solutions, specializing in Artificial Intelligence, Data Engineering, Cloud Services, Software Development, and Mobile App Development. They integrate advanced AI to accelerate product development and provide custom, secure, and scalable solutions. With a focus on cutting-edge technology and visionary thinking, Global Nodes offers services ranging from ideation and design to precision execution, transforming concepts into market-ready products. Their team has extensive experience in delivering top-notch AI, cloud, and data engineering services, making them a trusted partner for businesses worldwide.

Datamation is a leading industry resource for B2B data professionals and technology buyers. Datamation’s focus is on providing insight into the latest trends and innovation in AI, data security, big data, and more, along with in-depth product recommendations and comparisons. More than 1.7M users gain insight and guidance from Datamation every year.

DevRev is an AI-native modern support platform that offers a comprehensive solution for customer experience enhancement. It provides data engineering, knowledge graph, and customizable LLMs to streamline support, product management, and software development processes. With features like in-browser analytics, consumer-grade social collaboration, and global scale API calls, DevRev aims to bring together different silos within a company to drive efficiency and collaboration. The platform caters to support people, product managers, and developers, automating tasks, assisting in decision-making, and elevating collaboration levels. DevRev is designed to empower digital product teams to assimilate customer feedback in real-time, ultimately powering the next generation of technology companies.

New Relic is an AI monitoring platform that offers an all-in-one observability solution for monitoring, debugging, and improving the entire technology stack. With over 30 capabilities and 750+ integrations, New Relic provides the power of AI to help users gain insights and optimize performance across various aspects of their infrastructure, applications, and digital experiences.

DataLab is a data notebook that smartly leverages generative AI technology to enable users to 'chat with their data'. It features a powerful IDE for analysis, and seamlessly transforms work into shareable reports. The application runs in a cloud-hosted environment with support for R/Python, SQL, and various data science packages. Users can connect to external databases, collaborate in real-time, and utilize an AI Assistant for code generation and error correction.

AIONTECH Solutions is an AI and data solutions provider that empowers businesses to fully utilize data, fostering innovation and ensuring long-term success. They offer cutting-edge AI and data solutions, advanced data analytics, innovation, and a comprehensive suite to unlock the full potential of data. The company is trusted by clients for providing services in BI & Analytics, Cloud Services, Sustainability Services, Data Science and Analytics, and more.

Teraflow.ai is an AI-enablement company that specializes in helping businesses adopt and scale their artificial intelligence models. They offer services in data engineering, ML engineering, AI/UX, and cloud architecture. Teraflow.ai assists clients in fixing data issues, boosting ML model performance, and integrating AI into legacy customer journeys. Their team of experts deploys solutions quickly and efficiently, using modern practices and hyper scaler technology. The company focuses on making AI work by providing fixed pricing solutions, building team capabilities, and utilizing agile-scrum structures for innovation. Teraflow.ai also offers certifications in GCP and AWS, and partners with leading tech companies like HashiCorp, AWS, and Microsoft Azure.

Databricks is a data and AI company that provides a unified platform for data, analytics, and AI. The platform includes a variety of tools and services for data management, data warehousing, real-time analytics, data engineering, data science, and AI development. Databricks also offers a variety of integrations with other tools and services, such as ETL tools, data ingestion tools, business intelligence tools, AI tools, and governance tools.

Tredence is a data science and AI services company that provides end-to-end solutions for businesses across various industries. The company's services include data engineering, data analytics, AI consulting, and machine learning operations (MLOps). Tredence has a team of experienced data scientists and engineers who use their expertise to help businesses solve complex data challenges and achieve their business goals.

Keebo is an AI tool designed for Snowflake optimization, offering automated query, cost, and tuning optimization. It is the only fully-automated Snowflake optimizer that dynamically adjusts to save customers 25% and more. Keebo's patented technology, based on cutting-edge research, optimizes warehouse size, clustering, and memory without impacting performance. It learns and adjusts to workload changes in real-time, setting up in just 30 minutes and delivering savings within 24 hours. The tool uses telemetry metadata for optimizations, providing full visibility and adjustability for complex scenarios and schedules.

DBiz.ai is a high-performing product and engineering company that partners with organizations using AI-first strategies to develop digital solutions. They empower customers to preserve and enhance their current business while building the innovative future they desire through AI-driven solutions. DBiz.ai harnesses the power of AI technology to drive business success with innovative solutions, nurturing a thriving community and empowering humanity to ignite positive change using AI technology. They bridge the gap between end customer needs, business objectives, and IT organizations, inspiring and advising businesses to drive innovation and growth with cutting-edge BizDevOps strategy and advanced AI-enabled Platform Engineering Framework.

Hopsworks is an AI platform that offers a comprehensive solution for building, deploying, and monitoring machine learning systems. It provides features such as a Feature Store, real-time ML capabilities, and generative AI solutions. Hopsworks enables users to develop and deploy reliable AI systems, orchestrate and monitor models, and personalize machine learning models with private data. The platform supports batch and real-time ML tasks, with the flexibility to deploy on-premises or in the cloud.

DevSecCops is an AI-driven automation platform designed to revolutionize DevSecOps processes. The platform offers solutions for cloud optimization, machine learning operations, data engineering, application modernization, infrastructure monitoring, security, compliance, and more. With features like one-click infrastructure security scan, AI engine security fixes, compliance readiness using AI engine, and observability, DevSecCops aims to enhance developer productivity, reduce cloud costs, and ensure secure and compliant infrastructure management. The platform leverages AI technology to identify and resolve security issues swiftly, optimize AI workflows, and provide cost-saving techniques for cloud architecture.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

Wren Engine is a semantic engine designed to serve as the backbone of the semantic layer for LLMs. It simplifies the user experience by translating complex data structures into a business-friendly format, enabling end-users to interact with data using familiar terminology. The engine powers the semantic layer with advanced capabilities to define and manage modeling definitions, metadata, schema, data relationships, and logic behind calculations and aggregations through an analytics-as-code design approach. By leveraging Wren Engine, organizations can ensure a developer-friendly semantic layer that reflects nuanced data relationships and dynamics, facilitating more informed decision-making and strategic insights.

This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.

A repository providing basic concepts, technical challenges, and resources on data engineering in Spanish. It is a curated list of free, Spanish-language materials found on the internet to facilitate the study of data engineering enthusiasts. The repository covers programming fundamentals, programming languages like Python, version control with Git, database fundamentals, SQL, design concepts, Big Data, analytics, cloud computing, data processing, and job search tips in the IT field.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.

This repository provides a hands-on lab for learning about Neo4j and Google Cloud Vertex AI. It is intended for data scientists and data engineers to deploy Neo4j and Vertex AI in a Google Cloud account, work with real-world datasets, apply generative AI, build a chatbot over a knowledge graph, and use vector search and index functionality for semantic search. The lab focuses on analyzing quarterly filings of asset managers with $100m+ assets under management, exploring relationships using Neo4j Browser and Cypher query language, and discussing potential applications in capital markets such as algorithmic trading and securities master data management.

SambaNova AI Starter Kits is a collection of open-source examples and guides designed to facilitate the deployment of AI-driven use cases for developers and enterprises. The kits cover various categories such as Data Ingestion & Preparation, Model Development & Optimization, Intelligent Information Retrieval, and Advanced AI Capabilities. Users can obtain a free API key using SambaNova Cloud or deploy models using SambaStudio. Most examples are written in Python but can be applied to any programming language. The kits provide resources for tasks like text extraction, fine-tuning embeddings, prompt engineering, question-answering, image search, post-call analysis, and more.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

VectorETL is a lightweight ETL framework designed to assist Data & AI engineers in processing data for AI applications quickly. It streamlines the conversion of diverse data sources into vector embeddings and storage in various vector databases. The framework supports multiple data sources, embedding models, and vector database targets, simplifying the creation and management of vector search systems for semantic search, recommendation systems, and other vector-based operations.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.

Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's low-code Connector Development Kit (CDK). Airbyte is used by data engineers and analysts at companies of all sizes to move data for a variety of purposes, including data warehousing, data analysis, and machine learning.

Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. For more architecture details, see Milvus Architecture Overview. Milvus was released under the open-source Apache License 2.0 in October 2019. It is currently a graduate project under LF AI & Data Foundation.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

Hopsworks is a data platform for ML with a Python-centric Feature Store and MLOps capabilities. It provides collaboration for ML teams, offering a secure, governed platform for developing, managing, and sharing ML assets. Hopsworks supports project-based multi-tenancy, team collaboration, development tools for Data Science, and is available on any platform including managed cloud services and on-premise installations. The platform enables end-to-end responsibility from raw data to managed features and models, supports versioning, lineage, and provenance, and facilitates the complete MLOps life cycle.

Guides in data engineering tasks with a focus on practical solutions.

Cloud Engineer Expert, guiding in cloud tech, projects, career, and industry trends.

I will help you to integrate the popular distributed event streaming platform Apache Kafka into your own cloud solutions.

Your friendly Data Engineering teacher

Expert in cloud computing, offering insights on services, security, and infrastructure.

The KQL Query Helper GPT is tailored specifically for assisting users with Kusto Query Language (KQL) queries. It leverages extensive knowledge from Azure Data Explorer documentation to aid users in understanding, reviewing, and creating new KQL queries based on their prompts.

Python script assistant for AWS Lambda and SQS

Assists with NoSQL programming by providing code examples, debugging tips, and best practices.

Detailed Guide in SQL Server Backup/Restore

Expert in backend development and file handling.

Expert in all aspects of Google Cloud Platform.

Cybernetic humanoid expert in extraterrestrial tech, driven to merge past and future.

AI Cloud Certification Assistant: Google Cloud expert with timed exams and specific service exercises.

Cloud computing ace with an old school vibe.

Expert in cloud-native solutions, provides tailored tech advice and cost estimates.

Optimizes cloud-based networks for efficient organizational operations.

A detailed expert trained on all 5,671 pages of Apple CloudKit, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️

A role-play enabled Amazon/AWS interview coach specializing in STAR format and Leadership Principles.

Your very own Elasticsearch Copilot

Friendly Azure guide for beginners