Best Data Science Software in New Zealand - Page 3

Compare the Top Data Science Software in New Zealand as of November 2024 - Page 3

  • 1
    Oracle Cloud Infrastructure Data Flow
    Oracle Cloud Infrastructure (OCI) Data Flow is a fully managed Apache Spark service to perform processing tasks on extremely large data sets without infrastructure to deploy or manage. This enables rapid application delivery because developers can focus on app development, not infrastructure management. OCI Data Flow handles infrastructure provisioning, network setup, and teardown when Spark jobs are complete. Storage and security are also managed, which means less work is required for creating and managing Spark applications for big data analysis. With OCI Data Flow, there are no clusters to install, patch, or upgrade, which saves time and operational costs for projects. OCI Data Flow runs each Spark job in private dedicated resources, eliminating the need for upfront capacity planning. With OCI Data Flow, IT only needs to pay for the infrastructure resources that Spark jobs use while they are running.
    Starting Price: $0.0085 per GB per hour
  • 2
    IBM Analytics for Apache Spark
    IBM Analytics for Apache Spark is a flexible and integrated Spark service that empowers data science professionals to ask bigger, tougher questions, and deliver business value faster. It’s an easy-to-use, always-on managed service with no long-term commitment or risk, so you can begin exploring right away. Access the power of Apache Spark with no lock-in, backed by IBM’s open-source commitment and decades of enterprise experience. A managed Spark service with Notebooks as a connector means coding and analytics are easier and faster, so you can spend more of your time on delivery and innovation. A managed Apache Spark services gives you easy access to the power of built-in machine learning libraries without the headaches, time and risk associated with managing a Sparkcluster independently.
  • 3
    SAS Visual Statistics
    With SAS Visual Statistics, multiple users can explore data, then interactively create and refine predictive models. Your data scientists and statisticians can act on observations at a granular level using the most appropriate analytical modeling techniques. The result? You'll unearth insights at unprecedented speeds, and find new ways to grow revenue. Easily build and refine models to target specific groups or segments, and run numerous scenarios simultaneously. You can ask more what-if questions to get better results. And put results into action with an automatically generated score code. Empower multiple users to interact with data visually – to add or change variables, remove outliers, etc. Instantly see how changes affect your model's predictive power, and make refinements quickly. Data science teams have the ultimate flexibility of working in their language of choice, so they can use their skills to the fullest. SAS Visual Statistics unites all analytical assets.
  • 4
    SAS Viya
    SAS® Viya® data science offerings provide a comprehensive, scalable analytics environment that's quick and easy to deploy, enabling you to meet diverse business needs. Automatically generated insights enable you to identify the most common variables across all models, the most important variables selected across models and assessment results for all models. Natural language generation capabilities are used to create project summaries written in plain language, enabling you to easily interpret reports. Analytics team members can add project notes to the insights report to facilitate communication and collaboration among team members. SAS lets you embed open source code within an analysis and call open source algorithms seamlessly within its environment. This facilitates collaboration across your organization because users can program in their language of choice. You can also take advantage of SAS Deep Learning with Python (DLPy), our open-source package on GitHub.
  • 5
    SAS Visual Data Science
    Access, explore and prepare data while discovering new trends and patterns. SAS Visual Data Science helps you create and share smart visualizations and interactive reports through a single, self-service interface. It uses machine learning, text analytics and econometrics capabilities for better forecasting and optimization, plus it manages and registers SAS and open-source models within projects or as standalone models. Visualize and discover relevant relationships in your data. Create and share interactive reports and dashboards, and use self-service analytics to quickly assess probable outcomes for smarter, more data-driven decisions. Explore data and build or adjust predictive analytical models with this solution running in SAS® Viya®. Data scientists, statisticians, and analysts can collaborate and iteratively refine models for each segment or group to make decisions based on accurate insights.
  • 6
    SAS Data Science Programming
    Create, embed and govern analytically driven decision flows at scale in real-time or batch. SAS Data Science Programming enables data scientists who prefer a programmatic-only approach to access SAS analytical capabilities at all stages of the analytics life cycle, including data, discovery and deployment. Visualize and discover relevant relationships in your data. Create and share interactive reports and dashboards, and use self-service analytics to quickly assess probable outcomes for smarter, more data-driven decisions. Explore data and build or adjust predictive analytical models with this solution running in SAS® Viya®. Data scientists, statisticians, and analysts can collaborate and iteratively refine models for each segment or group to make decisions based on accurate insights. Solve complex analytical problems with a comprehensive visual interface that handles all tasks in the analytics life cycle.
  • 7
    SAS Visual Data Science Decisioning
    Integrate analytics into real-time ​interactions and event-based capabilities​. SAS Visual Data Science Decisioning features robust data management, visualization, advanced analytics and model management. It supports decisions by creating, embedding and governing analytically driven decision flows at scale in real-time or batch. It also deploys analytics and decisions in the stream to help you discover insights. Solve complex analytical problems with a comprehensive visual interface that handles all tasks in the analytics life cycle. SAS Visual Data Mining and Machine Learning, which runs in SAS® Viya®, combines data wrangling, exploration, feature engineering, and modern statistical, data mining, and machine learning techniques in a single, scalable in-memory processing environment. Access data files, libraries and existing programs, or write new ones, with this developmental web application accessible through your browser.
  • 8
    Metaflow

    Metaflow

    Metaflow

    Successful data science projects are delivered by data scientists who can build, improve, and operate end-to-end workflows independently, focusing more on data science, less on engineering. Use Metaflow with your favorite data science libraries, such as Tensorflow or SciKit Learn, and write your models in idiomatic Python code with not much new to learn. Metaflow also supports the R language. Metaflow helps you design your workflow, run it at scale, and deploy it to production. It versions and tracks all your experiments and data automatically. It allows you to inspect results easily in notebooks. Metaflow comes packaged with the tutorials, so getting started is easy. You can make copies of all the tutorials in your current directory using the metaflow command line interface.
  • 9
    Hex

    Hex

    Hex

    Hex brings together the best of notebooks, BI, and docs into a seamless, collaborative UI. Hex is a modern Data Workspace. It makes it easy to connect to data, analyze it in collaborative SQL and Python-powered notebooks, and share work as interactive data apps and stories. Your default landing page in Hex is the Projects page. You can quickly find projects you created, as well as those shared with you and your workspace. The outline provides an easy-to-browse overview of all the cells in a project's Logic View. Every cell in the outline lists the variables it defines, and cells that return a displayed output (chart cells, Input Parameters, markdown cells, etc.) display a preview of that output. You can click any cell in the outline to automatically jump to that position in the logic.
    Starting Price: $24 per user per month
  • 10
    Cornerstone AI

    Cornerstone AI

    Cornerstone AI

    The traditional system of bespoke data review is not keeping up with the quantity and speed of data. Cornerstone AI has developed a self-learning AI platform to automatically create smarter data rules to clean and organize your data, getting you to better analytical datasets faster. Clinical data that is costing your team time and effort to clean and prepare. Clinical trial, EHR, registry, digital health, claims, image, and sensor data are all supported by our platform. Our platform scans each table and data point, inferring structure and validity. With this, we organize tables for analysis and remove & correct errors in your data. An instant data quality report, highlighting features with most errors. Automated or UI-based correction of those errors, API access to connect directly to your data pipeline, and audit trail for everything. We do not keep, aggregate, or resell your data. Your data is yours and is only used for you.
  • 11
    JetBrains DataSpell
    Switch between command and editor modes with a single keystroke. Navigate over cells with arrow keys. Use all of the standard Jupyter shortcuts. Enjoy fully interactive outputs – right under the cell. When editing code cells, enjoy smart code completion, on-the-fly error checking and quick-fixes, easy navigation, and much more. Work with local Jupyter notebooks or connect easily to remote Jupyter, JupyterHub, or JupyterLab servers right from the IDE. Run Python scripts or arbitrary expressions interactively in a Python Console. See the outputs and the state of variables in real-time. Split Python scripts into code cells with the #%% separator and run them individually as you would in a Jupyter notebook. Browse DataFrames and visualizations right in place via interactive controls. All popular Python scientific libraries are supported, including Plotly, Bokeh, Altair, ipywidgets, and others.
    Starting Price: $229
  • 12
    iGenius crystal
    Any teams can access key insights independently by just talking — no training or data literacy skills required. Crystal can be tailored to a specific organization’s needs, meaning your teams and crystal can combine to drive actionable insights. Crystal monitors your data 24/7 and can alert you on important changes, ensuring you will get the answers you need, as well as the ones you didn’t know you needed. Available on mobile and desktop, your teams can get immediate insights anywhere without sifting through reports. Bring your use case to life in days, not months, with crystal’s user-friendly setup. Complete with low-code no-code data source connection and setup, you can make more of your existing BI investments and get immediate business value.
  • 13
    Zerve AI

    Zerve AI

    Zerve AI

    Merging the best of a notebook and an IDE into one integrated coding environment, experts can explore their data and write stable code at the same time with fully automated cloud infrastructure. Zerve’s data science development environment gives data science and ML teams a unified space to explore, collaborate, build, and deploy data science & AI projects like never before. Zerve offers true language interoperability, meaning that as well as being able to use Python, R, SQL, or Markdown all in the same canvas, users can connect these code blocks to each other. No more long-running code blocks or containers, with Zerve enjoying unlimited parallelization at any stage of the development journey. Analysis artifacts are automatically serialized, versioned, stored, and preserved for later use, meaning easily changing a step in the data flow without needing to rerun any preceding steps. Fine-grained selection of compute resources and extra memory for complex data transformation.
  • 14
    Alteryx Designer
    Drag-and-drop tools and generative AI enable analysts to prepare & blend data up to 100 faster than traditional solutions. Self-service data analytics platform puts the power in every analyst’s hands and removes expensive bottlenecks in the analytics journey. Alteryx Designer is a self-service data analytics platform designed to empower analysts by enabling them to prepare, blend, and analyze data using intuitive, drag-and-drop tools. The platform supports over 300 tools for automation and integrates with more than 80 data sources. With a focus on low-code and no-code capabilities, Alteryx Designer allows users to easily create analytic workflows, accelerate analytics processes with generative AI, and generate insights without needing advanced programming skills. It also enables the output of results to over 70 different tools, making it highly versatile. Designed for efficiency, it allows businesses to speed up data preparation and analysis.
  • 15
    Microsoft R Open
    Microsoft continues its commitment and development in R, not only in the latest Machine Learning Server release, but also in the newest Microsoft R Client and Microsoft R Open releases. You can also find R and Python support in SQL Server Machine Learning Services on Windows and Linux, and R support in Azure SQL Database. R components are backwards compatible. You should be able to run existing R script on newer versions, with the exception of dependencies on packages or platforms that are no longer supported, or known issues that require a workaround or code change. Microsoft R Open is the enhanced distribution of R from Microsoft Corporation. The current release, Microsoft R Open 4.0.2, is based the statistical language R-4.0.2 and includes additional capabilities for improved performance, reproducibility and platform support. Compatibility with all packages, scripts and applications that work with R-4.0.2.
  • 16
    Analance
    Combining Data Science, Business Intelligence, and Data Management Capabilities in One Integrated, Self-Serve Platform. Analance is a robust, salable end-to-end platform that combines Data Science, Advanced Analytics, Business Intelligence, and Data Management into one integrated self-serve platform. It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance.
  • 17
    H2O.ai

    H2O.ai

    H2O.ai

    H2O.ai is the open source leader in AI and machine learning with a mission to democratize AI for everyone. Our industry-leading enterprise-ready platforms are used by hundreds of thousands of data scientists in over 20,000 organizations globally. We empower every company to be an AI company in financial services, insurance, healthcare, telco, retail, pharmaceutical, and marketing and delivering real value and transforming businesses today.
  • 18
    KNIME Analytics Platform
    One enterprise-grade software platform, two complementary tools. Open source KNIME Analytics Platform for creating data science and commercial KNIME Server for productionizing data science. KNIME Analytics Platform is the open source software for creating data science. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone. KNIME Server is the enterprise software for team-based collaboration, automation, management, and deployment of data science workflows as analytical applications and services. Non experts are given access to data science via KNIME WebPortal or can use REST APIs. Do even more with your data using extensions for KNIME Analytics Platform. Some are developed and maintained by us at KNIME, others by the community and our trusted partners. We also have integrations with many open source projects.
  • 19
    HyperCube

    HyperCube

    BearingPoint

    Whatever your business need, discover hidden insights quickly and easily using HyperCube, the platform designed for the way data scientists work. Put your business data to work. Unlock understanding, discover unrealized opportunities, generate predictions and avoid risks before they happen. HyperCube takes huge volumes of data and turns it into actionable insights. Whether a beginner in analytics or a machine learning expert, HyperCube is designed with you in mind. It is the Swiss Army knife of data science, combining proprietary and open source code to deliver a wide range of data analysis features straight out of the box or as business apps, customized just for you. We are constantly updating and perfecting our technology so we can deliver the most innovative, intuitive and adaptable results Choose from apps, data-as-a-services (DaaS) and vertical market solutions.
  • 20
    Pyramid Analytics

    Pyramid Analytics

    Pyramid Analytics

    The goal of Decision intelligence is to empower employees with insights to make faster more informed decisions to capitalize on opportunities, take corrective measures, and drive innovation. Meet the data and analytics platform purpose-built to power faster, sharper decisions for the enterprise of the future. Driven by a new class of engine. Streamlining the entire analytics workflow. One platform for any data, any person, any analytics needs. This is the future of intelligent decisions. A whole new intelligence platform, combining data preparation, business analytics, and data science into one unified architecture. Streamline the entire decision-making process. So everything from discovery to publishing and modeling is inter-connected (and easy to use). Runs at hyper-scale for any data-driven decision. Unlocks advanced data science for any business need, from the C-Suite to the frontline.
  • 21
    OpenText Magellan
    Machine Learning and Predictive Analytics Platform. Augment data-driven decision making and accelerate business with advanced artificial intelligence in a pre-built machine learning and big data analytics platform. OpenText Magellan uses AI technologies to provide predictive analytics in easy to consume and flexible data visualizations that maximize the value of business intelligence. Artificial intelligence software eliminates the need for manual big data processing by presenting valuable business insights in a way that is accessible and related to the most critical objectives of the organization. By augmenting business processes through a curated mix of capabilities, including predictive modeling, data discovery tools, data mining techniques, IoT data analytics and more, organizations can use their data to improve decision making based on real business intelligence and analytics.
  • 22
    DataRobot

    DataRobot

    DataRobot

    AI Cloud is a new approach built for the demands, challenges and opportunities of AI today. A single system of record, accelerating the delivery of AI to production for every organization. All users collaborate in a unified environment built for continuous optimization across the entire AI lifecycle. The AI Catalog enables seamlessly finding, sharing, tagging, and reusing data, helping to speed time to production and increase collaboration. The catalog provides easy access to the data needed to answer a business problem while ensuring security, compliance, and consistency. If your database is protected by a network policy that only allows connections from specific IP addresses, contact Support for a list of addresses that an administrator must add to your network policy (whitelist).
  • 23
    Appsilon

    Appsilon

    Appsilon

    Appsilon provides innovative data analytics, machine learning, and managed services solutions for Fortune 500 companies, NGOs, and non-profit organizations. We deliver the world’s most advanced R Shiny applications, with a unique ability to rapidly develop and scale enterprise Shiny dashboards. Our proprietary machine learning frameworks allow us to deliver Computer Vision, NLP, and fraud detection prototypes in as little as one week. Above all, we are committed to making a positive impact on the world. Through our AI For Good Initiative, we routinely contribute our skills to projects that support the preservation of human life and the conservation of animal populations all over the globe. Recently, our team has worked to mitigate poaching in Africa with computer vision, provide satellite image analysis for assessing damage after natural disasters, and build tools to help with COVID-19 risk assessment. Appsilon is also a pioneer in open source.
  • 24
    TetraScience

    TetraScience

    TetraScience

    Accelerate scientific discovery and empower your R&D team with harmonized data in the cloud. The Tetra R&D Data Cloud combines the industry’s only cloud-native data platform built for global pharmaceutical companies, with the power of the largest and fastest growing network of Life Sciences integrations, and deep domain knowledge, to deliver a future-proof solution for harnessing the power of your most valuable asset: R&D data. Covers the full life-cycle of your R&D data, from acquisition to harmonization, engineering, and downstream analysis with native support for state-of-the-art data science tools. Vendor-agnostic with pre-built integrations to easily connect to instruments, analytics and informatics applications, ELN/LIMS, CRO/CDMOs. Data acquisition, management, harmonization, integration/engineering and data science enablement in one single platform.
  • 25
    Oracle Data Science
    A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results.
  • 26
    Brilent

    Brilent

    Brilent

    Brilent is a data science tech company developing a SaaS solution to help talent seekers quickly and effectively identify the right talent to hire. The exciting part about this intelligent technology is its simplicity. No tricks. It leverages the components recruiters find quite relevant. At the core of the Brilent engine are three simple elements: the job requirements; the candidate profile; and our unique repository of market data. Next comes the fun part. Our system gathers all the relevant data from the job requirements and candidate profiles. Using hundreds of variables from these familiar recruiting elements and the market data, we use our well-honed experience to apply artificial intelligence and machine learning algorithms to predict how likely a candidate is a good fit for a particular job. In other words, a whole lot of data crunching, and completed in seconds. Recruiters get a ranking of candidates according to the desired specifications.
  • 27
    HPE Ezmeral

    HPE Ezmeral

    Hewlett Packard Enterprise

    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.
  • 28
    dotData

    dotData

    dotData

    dotData frees your business to focus on the results of your AI and machine learning applications, not the headaches of the data science process by automating the full data science life-cycle. Deploy full-cycle AI & ML pipeline in minutes, update in real-time with continuous deployment. Accelerate data science projects from months to days with feature engineering automation. Discover the unknown unknowns of your business automatically with data science automation. The process of using data science to develop and deploy accurate machine learning and AI models is cumbersome, time-consuming, labor-intensive, and interdisciplinary. Automate the most time-consuming and repetitive tasks that are the bane of data science work and shorten AI development times from months to days.
  • 29
    FICO Analytics Workbench
    Predictive Modeling with Machine Learning and Explainable AI. FICO® Analytics Workbench™ is an integrated suite of state-of-the-art analytic authoring tools that empowers companies to improve business decisions across the customer lifecycle. With it, data scientists can build superior decisioning capabilities using a wide range of predictive data modeling tools and algorithms, including the latest machine learning (ML) and explainable artificial intelligence (xAI) approaches. We enhance the best of open source data science and machine learning with innovative intellectual property from FICO to deliver world-class analytic capabilities to discover, combine, and operationalize predictive signals in data. Analytics Workbench is built on the leading FICO® Platform to allow new predictive models and strategies to be deployed into production with ease.
  • 30
    Knoldus

    Knoldus

    Knoldus

    World's largest team of Functional Programming and Fast Data engineers focused on creating customized high-performance solutions. We move from "thought" to "thing" via rapid prototyping and proof of concept. Activate an ecosystem to deliver at scale with CI/CD to support your requirements. Understanding the strategic intent and stakeholder needs to develop a shared vision. Deploy MVP to launch the product in the most efficient & expedient manner possible. Continuous improvements and enhancements to support new requirements. Building great products and providing unmatched engineering services would not be possible without the knowledge and extensive usage of the latest tools and technology. We help you to capitalize on opportunities, respond to competitive threats, and scale successful investments by reducing organizational friction from your company’s structures, processes, and culture. Knoldus helps clients identify and capture the most value and meaningful insights from data.