테라다데이터 정보
테라데이터는 기업들이 지능을 자율적 행동으로 전환할 수 있도록 지원하며, AI 에이전트가 깊은 비즈니스 맥락과 신뢰할 수 있는 데이터에 기반을 두도록 합니다. AI 에이전트가 늘어나면서, 테라데이터는 기업들이 지금 필요로 하는 컨텍스트 엔진, 거버넌스 계층, 그리고 성능 기반이 되었습니다. Teradata 자율 AI 및 지식 플랫폼은 클라우드, 온프레미스, 하이브리드 환경에서 AI를 생산에 투입합니다.
Teradata Expands Vantage Support for Data Science
With expanded analytic functions as well as tools and language support, Teradata Vantage enables a diverse group of analytics personas to collaborate on data science workflows
SAN DIEGO – September 9, 2020 – Teradata (NYSE: TDC), the connected multi-cloud data platform for enterprise analytics company, today announced enhancements to its Vantage platform, making collaborative and frictionless data science a reality. By significantly increasing the collaboration between data scientists, business analysts, data engineers, business leads and others who may use different tools and languages, Vantage allows organizations to realize faster time to value and reduced costs with stronger data governance and security.
Key enhancements – free to all Teradata Vantage customers – include:
- Expanded native support for R and Python, with the ability to call more Vantage-native analytic functions, as well as the ability to execute a wide range of open-source analytic algorithms/packages;
- Automatic generation of SQL from R and Python code, making it easier and faster for data scientists and business analysts to work together seamlessly to quickly operationalize new insights; and
- Added support for JupyterHub for Python, R and SQL, in addition to the existing support for popular development environments such as JupyterLab and RStudio.
With this enhanced level of support for data science on Vantage, businesses can achieve end-to-end data science workflows on a single, scalable, reliable and secure platform, without the need to create data silos or sample data. This enables a wide range of personas to collaboratively run complex analytics in a self-service manner, on one platform and with the same data, ensuring efficient operationalization. This shared journey ensures consistent stakeholder buy-in, a fail-fast approach that delivers timely course corrections, and a consensus-based method for delivering long-term business outcomes.
“As businesses increasingly rely on virtual connectivity to keep operations running, collaboration has emerged as the key success factor for many functions, especially analytics,” said Sri Raghavan, Director of Data Science and Advanced Analytics Product Marketing at Teradata. “With greater functionality and expanded support for data science to help analytics users better communicate and collaborate, Vantage helps remove friction from the data science process so customers can derive mission-critical insights at record speed and scale. And given the broad deployment options for Vantage – public clouds, including AWS, Azure, and Google Cloud Platform later this year, as well as hybrid and multi-cloud – customers are given the flexibility to leverage the platform’s enhanced data science capabilities in the environment of their choice.”
In addition to increased collaboration, businesses will realize reduced costs in the form of minimizing or eliminating false starts, inappropriate analytic usage, lock-in to one form of implementation (e.g., on-premises versus cloud) and faster iterations towards achieving specific business goals. Vantage’s strong support for data governance and security also ensures the highest degree of freeform collaboration, without the downside risks of unauthorized access and performance bottlenecks.
A complete list of the new enhancements and support for data science on the Vantage platform includes:
- Expanded choice of analytic functions: Gives data scientists and business analysts a larger set of powerful analytic functions to leverage for increased collaboration:
- More Vantage functions available through R and Python: Facilitates an expanded set of native Vantage analytics algorithms (e.g., machine learning) called from R and Python, in addition to SQL.
- Access to more R and Python analytics functions: Expands a set of open source R and Python analytic algorithms (e.g., scikit-learn) which can be used with Vantage. Not only does Vantage integrate with open source language and tools, but it provides a wide breadth of native and open source algorithms to address virtually any business challenge.
- Availability of a new Analytics Library: Adds a new set of scalable advanced analytics built directly in Vantage, including a set of data preparation and modeling functions that helps data scientists spend less time with data preparation and more time delivering insights.
- Automatic SQL statement generation to facilitate communication between multiple user groups: Makes it easier for data scientists, business analysts and developers to work together through a single standard data management language (SQL) while using a language of their choice (e.g., R and Python), through:
- SQL generated from R and Python: Enables R and Python programmers to expose SQL statements used by Vantage with the show_query() function thus enabling non-Python/R savvy programmers to enhance, and also execute, complex analytic workflows.
- SQL generated from Vantage Analyst: Allows business users and business analysts to discover fundamental insights from Vantage Analyst’s graphical interface and also generate the underlying SQL script automatically without having to write a single line of code. The scripts can then be shared with developers for more advanced implementations.
- SQL generated from R and Python: Enables R and Python programmers to expose SQL statements used by Vantage with the show_query() function thus enabling non-Python/R savvy programmers to enhance, and also execute, complex analytic workflows.
- Collaborative Development Environment: While R, Python and SQL scripts can be executed by an analyst’s choice of Integrated Development Environment (e.g., RStudio, JupyterLab, Teradata Studio), Teradata’s support for JupyterHub - which allows R and SQL script execution in addition to Python - facilitates better code collaboration and best practice sharing.
Incorporating this functionality into Vantage allows current and future Teradata analytics partners to more seamlessly utilize the power of the Teradata platform within their own toolsets and languages.
These new capabilities further support Teradata’s advocated Analytics 1-2-3 strategy which holds that organizations can only successfully scale their Machine Learning (ML) and Artificial Intelligence (AI) initiatives by engaging in rapid experimentation and agile model building by using curated features with high predictive value. This ensures at scale operationalization and quicker model redeployment.
Teradata Vantage is the leading hybrid, multi-cloud data analytics software platform that enables ecosystem simplification by unifying analytics, data lakes and data warehouses. With Vantage delivered as-a-service, in the cloud, enterprise-scale companies can eliminate silos and cost-effectively query all their data, all the time, regardless of where the data resides – in the cloud, on multiple clouds, on-premises or any combination thereof – to get a complete, integrated view of their business. Vantage delivered as-a-service subscriptions include Vantage software, high-performance infrastructure, and environment management in one convenient bundle.
Availability
Expanded support for data science on Vantage is free to Teradata customers and automatically available now, except for the Analytics Library, which will be available in late Q4 2020.