Embracing Green - Sustainable IT is the Power to Know
Figure 1: Sheep grazing in a solar panel park at a software company focused on sustainability.
In today's eco-conscious business landscape, sustainability is vital for corporate responsibility and quality. Information technology, integral to operations, has expanded its environmental footprint through increased computing demands, electronic waste, energy consumption, and resulting carbon emissions. Sustainable companies manage IT assets to extend their lifespan, reduce material impacts, and optimize energy use. Procuring energy-efficient, eco-certified IT assets is essential.
Achieving sustainability involves operational excellence and effective IT Operations Management to ensure reliability and performance. Beyond IT, companies should reduce energy consumption in offices and data centers, promote recycling, minimize waste, and encourage sustainable employee practices. For software companies, this means optimizing configurations, efficient coding, and lean operations to meet SLA goals while scaling down when feasible.
Embracing Green with Low Code: Streamlining Data Management and Analytics
A picture says more than a thousand words. Low-code platforms are akin to looking at a picture rather than looking at massive amounts of code and worded explanations of the code. They provide a visual, intuitive interface where users can efficiently manage and analyze data. With user-friendly interfaces and drag-and-drop tools, these platforms streamline workflows, making tasks quicker to comprehend and execute. This visual approach not only enhances productivity but also reduces the complexity typically associated with traditional coding methods, thereby promoting sustainability through lower energy consumption. Operating in cloud environments, these low-code platforms optimize resource usage and provide:
- Rapid Deployment: Pre-built components enable quick implementation of solutions, cutting down on development time.
- Reduced Resource Needs: Streamlined processes demand lower energy consumption for data and analytics processing.
Figure 2: Rendition of a low-code visual pipeline for easy readability and understanding.
Embracing Green with Cost-efficient Storage and Computing
Optimizing storage and computing not only reduces costs but also enhances sustainability. With various cloud options available, practicality plays a crucial role in decision-making. Consider these options tailored to business needs:
- Data Warehouses and Data Lakehouses:
- Strengths: Ideal for data management and governance, ensuring organized data.
- Limitations: Less suitable for exploration due to costs associated with querying and resource consumption.
- Balancing Exploration and Cost:
- Optimize storage for AI-driven insights by extracting data into formats well-suited for efficient exploration and resource utilization. This approach allows businesses to delve into data without financial concerns, fostering both exploration and cost-effectiveness, without the meter ticking.
- Cost-efficient computing:
- Take advantage of the elasticity of cloud services that enables organizations to reduce their environmental impact by using only those resources that they need. In this context, AI applications with clever workload management capabilities can offer greater control over compute resources, beyond what is provided by generic cloud services.
Embracing Green with SAS for Data Exploration and AI Modeling
SAS Viya revolutionizes data exploration and AI modeling with its powerful in-memory analytics engine, setting a new standard for efficiency and performance. By seamlessly integrating optimized visualization and demonstrating significant speed advantages over competitors, SAS Viya not only enhances analytical workflows but also supports sustainable computing practices, making it a preferred choice for organizations focused on innovation and environmental responsibility.
According to a study by the Futurum Group, SAS Viya demonstrates significant performance advantages:
- On average, SAS Viya is reported to be 30 times faster than its competitors across all tested scenarios.
- In specific cases, such as running on Azure, SAS Viya showed performance gains of up to 326 times compared to a specific competitor ("Competitor-A").
- SAS Viya achieved these performance metrics while also reducing costs significantly, reportedly 86% lower compared to competitors overall.
Figure 3: SAS Viya performance impact from Futurum Group study.
Here are some key points that highlight SAS Viya efficiency and capabilities for greater sustainability:
SAS In-Memory Analytics Engine:
- Direct Data Ingestion: It can directly ingest data from various sources including data warehouses and data lakehouses. This eliminates the need for repetitive data fetching, which traditionally slows down analytics processes.
- In-Memory Data Storage: Data resides and persists in memory, enabling lightning-fast access. This in-memory processing accelerates both data exploration and AI modeling tasks, indicating its versatility across different analytical workflows.
- Offloading Data: By offloading data from big data lakes and lakehouses into SAS Viya's in-memory cache, organizations can optimize querying and modeling tasks. This optimization leads to improved query speeds and overall efficiency in data processing.
Optimized Visualization:
- SAS Viya integrates an analytics engine that optimizes data visualization directly in memory. This integration enhances the exploration of insights derived from the data.
- The emphasis on optimized visualization ensures that users can efficiently interact with and interpret data, whether for exploration or model training purposes.
In summary, SAS Viya stands out for its combination of in-memory processing, efficient data handling, optimized visualization, and substantial performance advantages over competitors, all while promoting greater sustainability and allowing organizations to enjoy the fruits of successful innovation.
Figure 4: Saving on cost by being clever with storage - move data where it can be most efficiently explored.
Embracing Green with SAS for Efficient Computing
AI applications with efficient Workload Management capabilities provide superior control over compute resources compared to generic cloud services like Kubernetes. This includes detailed scalability support with awareness of job dependencies and priorities managed within the application, abstracted from Kubernetes.
Furthermore, adopting applications that support In-Database processing enhances sustainability efforts by reducing or eliminating the need for additional compute resources. This approach optimizes resource usage by leveraging database-proximate resources, minimizing data egress costs, improving network efficiency, and enhancing the end-user experience—an advantageous strategy across all aspects.
SAS as a Company Embraces Green Powered by Data and Analytics
Being open about sustainability is key, and from the IoT data collected through its smart campus project to powering office buildings with clean energy from its solar farms, a company such as SAS uses its own visualization solution to collect, manage, calculate, and report its environmental performance. Anyone can view SAS’ sustainability metrics from the dashboard here: SAS Institute Sustainability Dashboard
Figure 5: SAS goal to improve office CO2 emissions at SAS headquarters.
Companies like SAS go above and beyond in their pursuit of sustainability by providing solar power to run their data centers at their headquarters in Cary, NC. Moreover, they employ a herd of sheep to maintain the grass under and around the solar panels, ensuring the area is safely passable and easily accessible for regular maintenance. You can read more about this in the following blog on corporate sustainability: SAS, Solar Farms and Sheep: Working Together for the Good of the Planet
Figure 6: Sheep grazing in a solar panel park at SAS campus headquarters in Cary, North Carolina.
Finally, by using SAS software, organizations can emulate SAS's approach to becoming more sustainable. With SAS's comprehensive solutions for data collection, analysis, and reporting, organizations gain the tools needed to make informed decisions and create positive environmental change.
