Dataiku DSS Integrations

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

Build cutting-edge, market-ready AI applications with out-of-the-box and customizable APIs and models. Quickly infuse generative AI into production workloads using studios, SDKs, and APIs. Gain a competitive edge by building AI apps powered by foundation models, including those from OpenAI, Meta, and Microsoft. Detect and mitigate harmful use with built-in responsible AI, enterprise-grade Azure security, and responsible AI tooling. Build your own copilot and generative AI applications with cutting-edge language and vision models. Retrieve the most relevant data using keyword, vector, and hybrid search. Monitor text and images to detect offensive or inappropriate content. Translate documents and text in real time across more than 100 languages.

The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API.

MeaningCloud is the easiest, most powerful, and most affordable way to extract the meaning from unstructured content: documents, articles, social conversations, web content, etc. We provide text analytics products to extract the most accurate insights from any content in many languages. And we do it SaaS and On-prem. We work for different industries (pharma, finance, media, retail, hospitality, telco, etc.) developing personalized and industry-oriented solutions.  Pay only for what you use, without any activation fees, minimum time commitment and with the most generous free plan of the market. If you don't like it, you can stop using it, just like that. Without software to install or infrastructure to deploy. All the reliability and scalability of solutions in the cloud, and the possibility of testing it for free.

Toucan is a customer-facing analytics platform that empowers organizations to drive engagement with the best end-user experience. From data connections to the distribution of insights anywhere they're needed, Toucan makes it easy. As a result, Toucan analytics are used 3x more than the industry average. Users can connect to any data, cloud-based or other, streaming or stored, with hundreds of connectors. Preparation of data is equally simple with data readiness features that lets business people perform tasks that would ordinarily require an expert. Visualization takes the form of “data storytelling” where every chart is accompanied by context, collaboration, and annotation so that users understand the “why” and not just the “what” of their data. Finally, deployment and management are made easy with one-touch deployment from staging to production, easy embedding, and publishing to any device.

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models. Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire machine learning workflow. You need to stitch together tools and workflows, which is time-consuming and error-prone. SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost. Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps. SageMaker Studio gives you complete access, control, and visibility into each step required.

Modulos AG, founded in 2018, is a Swiss pioneer in Responsible AI Governance and the first AI Governance platform to achieve ISO 42001 certification. With a mission to empower organizations to govern AI products and services responsibly in regulated environments, Modulos streamlines and accelerates the AI compliance process. The platform enables businesses to efficiently manage risks and align with key regulatory frameworks like the EU AI Act, NIST AI RMF, ISO 42001, and more. As a result, Modulos helps clients avoid economic, legal, and reputational risks, fostering trust and long-term success in their AI initiatives.

Cloud AutoML is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs. It relies on Google’s state-of-the-art transfer learning and neural architecture search technology. Cloud AutoML leverages more than 10 years of proprietary Google Research technology to help your machine learning models achieve faster performance and more accurate predictions. Use Cloud AutoML’s simple graphical user interface to train, evaluate, improve, and deploy models based on your data. You’re only a few minutes away from your own custom machine learning model. Google’s human labeling service can put a team of people to work annotating or cleaning your labels to make sure your models are being trained on high-quality data.

DataOps.live, the Data Products company, delivers productivity and governance breakthroughs for data developers and teams through environment automation, pipeline orchestration, continuous testing and unified observability. We bring agile DevOps automation and a powerful unified cloud Developer Experience (DX) ​to modern cloud data platforms like Snowflake.​ DataOps.live, a global cloud-native company, is used by Global 2000 enterprises including Roche Diagnostics and OneWeb to deliver 1000s of Data Product releases per month with the speed and governance the business demands.

From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape. Struggle with sluggish performance and excessive memory usage, as every data point demands processing. Large datasets become cumbersome, complicating the user experience and data analysis. Scenarios are made easy with Taipy Studio. A powerful VS Code extension that unlocks a convenient graphical editor. Get your methods invoked at a certain time or intervals. Enjoy a variety of predefined themes or build your own.

The Unified Analytics Warehouse. Highest performing analytics and machine learning at extreme scale. As the criteria for data warehousing continues to evolve, tech research analysts are seeing new leaders in the drive for game-changing big data analytics. Vertica powers data-driven enterprises so they can get the most out of their analytics initiatives with advanced time-series and geospatial analytics, in-database machine learning, data lake integration, user-defined extensions, cloud-optimized architecture, and more. Our Under the Hood webcast series lets you to dive deep into Vertica features – delivered by Vertica engineers and technical experts – to find out what makes it the fastest and most scalable advanced analytical database on the market. From ride sharing apps and smart agriculture to predictive maintenance and customer analytics, Vertica supports the world’s leading data-driven disruptors in their pursuit of industry and business transformation.

Okera, the Universal Data Authorization company, helps modern, data-driven enterprises accelerate innovation, minimize data security risks, and demonstrate regulatory compliance. The Okera Dynamic Access Platform automatically enforces universal fine-grained access control policies. This allows employees, customers, and partners to use data responsibly, while protecting them from inappropriately accessing data that is confidential, personally identifiable, or regulated. Okera’s robust audit capabilities and data usage intelligence deliver the real-time and historical information that data security, compliance, and data delivery teams need to respond quickly to incidents, optimize processes, and analyze the performance of enterprise data initiatives. Okera began development in 2016 and now dynamically authorizes access to hundreds of petabytes of sensitive data for the world’s most demanding F100 companies and regulatory agencies. The company is headquartered in San Francisco.

Oncrawl provides data for technical SEO, to drive increased ROI and business success with your website. Oncrawl uses powerful analysis algorithms to reconcile third-party and natively collected data. Highly scalable and interconnected, Oncrawl is powered by the most advanced crawl and log analyzer technologies. Oncrawl's ability to help technical and marketing teams to understand, prioritize and measure the success of an organic growth strategy has earned the trust of major brands around the world. Oncrawl is used by technical SEO teams and teams they collaborate with, including product teams, content teams, and growth and marketing teams. Oncrawl's flexibility, scalability and commitment to data access make it possible to integrate Oncrawl into workflows tailored to industries that depend on a robust and profitable website, from e-commerce to news, travel, or listing sites including classifieds, job boards, and coupon sites.

The AI revolution is here. Innovation is moving at light speed, and the regulation landscape is constantly evolving. How can you make sure that your AI systems — and those of your vendors — remain secure, trustworthy, and compliant? Cranium helps cybersecurity and data science teams understand everywhere that AI is impacting their systems, data or services. Secure your organization’s AI and machine learning systems to ensure they are compliant and trustworthy, without interrupting your workflow. Protect against adversarial threats without impacting how your team trains, tests and deploys AI models. Increase AI regulatory awareness and alignment within your organization. Showcase the security and trustworthiness of your AI systems.

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

Run, manage, control and secure the apps, data and IT that run your business, from edge to cloud. HPE Ezmeral advances digital transformation initiatives by shifting time and resources from IT operations to innovations. Modernize your apps. Simplify your Ops. And harness data to go from insights to impact. Accelerate time-to-value by deploying Kubernetes at scale with integrated persistent data storage for app modernization on bare metal or VMs, in your data center, on any cloud or at the edge. Harness data and get insights faster by operationalizing the end-to-end process to build data pipelines. Bring DevOps agility to the machine learning lifecycle, and deliver a unified data fabric. Boost efficiency and agility in IT Ops with automation and advanced artificial intelligence. And provide security and control to eliminate risk and reduce costs. HPE Ezmeral Container Platform provides an enterprise-grade platform to deploy Kubernetes at scale for a wide range of use cases.

A new way of managing SaaS for large organizations to mitigate risk, optimize budgets, and implement unified governance. SaaS apps are omnipresent within organizations and they are skyrocketing out of IT's control. This is a complex landscape of decentralized IT led by business units, an 'underground digitalization' where various IT solutions are implemented for improved efficiency. Decentralized IT represents a systemic change and it has not yet been understood and managed. It creates major risks for companies (GDPR, security, and underperformance, to name a few) that must be addressed and governed. All large organizations will have to face this decentralization to accelerate their digitalization. Beamy continuously detects and monitors all SaaS apps used within your organization. Get the most of your SaaS stack by visualizing what is used, understanding shadow IT risks, and streamlining decision-making.

Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage.