#USA #AI #Dallas #SAS #Data Management

Introduction

As organizations strive to implement Artificial Intelligence (AI) effectively, they face obstacles stemming from decentralized data structures and outdated manual processes. SAS has recognized these challenges and introduced enhancements to its cloud-native portfolio, SAS Data Management, built on the SAS Viya platform. This significant upgrade aims to facilitate how companies prepare, govern, and activate data to harness the full potential of analytics and AI.

The Challenge of Data Management in the AI Era

In the race towards deploying AI, many enterprises are confronted with fragmented data ecosystems, which hinder operational efficiency and decision-making. A recent study indicated that almost half of the organizations viewed non-optimized cloud data environments as a major impediment to AI advancement. SAS asserts that the issue is exacerbated by inadequate governance frameworks, which fail to scale with the increasing demands of AI.

Gartner predicts that approximately 60% of AI projects are destined to fail due to deficiencies in AI-ready data, revealing a dire need for organizations to revamp their data management systems. This underscores the pressing requirement for a modern data platform that seamlessly integrates governance and operational efficiencies into a single, coherent architecture.

Strategic Enhancements from SAS

SAS's fresh update to its Data Management capabilities integrates governance as a core component rather than a supplementary afterthought. By embedding features such as data lineage, transparency, and performance monitoring directly into data workflows, SAS is enabling organizations to engage confidently in large-scale AI initiatives while maintaining trust in their data processes.

New Features Explained

1. AI-Ready Data Management: The latest version enhances the preparation and activation of data specifically for AI applications, ensuring that businesses can efficiently leverage their data assets.
2. Governance by Design: Governance features are integrated throughout the data lifecycle, providing organizations with a structure that promotes compliance and risk management without compromising agility.
3. Agentic AI Integration: SAS has introduced tools that facilitate greater automation for decision-making processes, allowing organizations to leverage AI technologies with more autonomy and less human intervention.
4. Cloud-Native Analytics: SpeedyStore, a revolutionary cloud-native analytical data platform, allows organizations to run analytics directly adjacent to their data. This minimizes data movement, enhancing performance and fostering lineage preservation for better trust in analytics results.

Bringing Analytics Closer to Data

The decentralized approach to analytics has often resulted in delays and inefficiencies due to the need for data to move across different platforms. SAS's approach not only alleviates these issues but also promotes a more coherent system where analytics can occur directly within the data environment. This shifts the paradigm, ensuring that analytics tasks are executed in situ, thus reducing latency and enhancing operational efficiency.

Inside SAS Viya

The SAS Viya platform further facilitates integration with existing cloud data environments, such as large-scale data warehouses or lakehouses, making it adaptable for organizations that require flexibility and scalability. By utilizing modern embedded analytics engines, SAS empowers companies to conduct swift local analyses across varied formats.

AI-Co-Pilots and Enhanced Data Autonomy

As organizations increasingly adopt AI-powered solutions, the governance of data remains paramount. SAS introduces functionality that embeds AI-driven assistance directly into the foundational data lifecycle. This includes revolutionary features like the SAS Viya Copilot for Data Discovery, which simplifies the exploration of available data through natural language processing, drastically reducing the time needed for discovery.

Another game-changer, SAS Viya Copilot for Code Assistance, incorporates AI-support directly within SAS Studio, elevating developer productivity while ensuring adherence to governance frameworks. Furthermore, SAS Data Maker provides capabilities to generate synthetic data, preserving privacy while enabling teams to perform necessary tasks without exposing sensitive information.

Conclusion

At the SAS Innovate event, marking the company's 50th anniversary, these advancements in data management take center stage as organizations look for efficient pathways to integrate AI into their operations. With tailored solutions that embed governance within data workflows, SAS sets a precedent for the future of AI-driven enterprises. By tackling the fundamental challenges of data management head-on, SAS is not just enhancing its offerings, but also empowering organizations to leverage AI responsibly and effectively.

Organizations keen to explore SAS’s comprehensive data management offerings can find further insights on their official site.