Role of Enterprise Managed Wi-Fi in the Era of IoT and Smart Devices
In the rapidly evolving landscape of the Internet of Things (IoT) and smart devices, reliable and efficient connectivity is paramount. Managed Wi-Fi services play a crucial role in enabling seamless communication and data exchange between IoT devices. The explosion of mobility & BYOD, enterprise virtualized applications moving to the cloud, increased use of multimedia-rich applications within the enterprise, and infrastructure modernization are a few of the core business drivers for increased adoption of enterprise managed Wi-Fi services.
With unprecedented advancements in IoT, data modeling, and AI/ML, there is a consistently growing focus on edge computing and its benefits. Enterprises are accelerating efforts to move to the cloud for on-demand computing, capacity, scale, better reach, scalability, and higher availability. Additionally, the managed Wifi services eliminate the traditional Wi-Fi challenges like lack of uniform access policy, no visibility into the wireless network, inadequate protection against wireless threats, complex or tedious onboarding process, and lack of visibility on user groups.
According to Marketsandmarkets, the global edge computing market size as per revenue surpassed $44.7 billion in 2022 and can rise to $101.3 billion by 2027 at a CAGR of 17.8% for the forecasted period (2022-2027).
This blog explores the significance of Enterprise Managed Wi-Fi services in supporting the proliferation of IoT and smart devices, the challenges they address, and the benefits they bring to businesses and consumers.
- Connectivity and device management
Managed Wi-Fi services offer a fully managed, secure wireless platform integrating Information Technology (IT), Operation Technology (OT), and people. It provides a robust infrastructure for connecting and managing a multitude of IoT devices. It offers a cloud-based centralized management platform with control and monitoring capabilities enabling enterprises to configure and manage their IoT devices efficiently. From provisioning and onboarding to security protocols and firmware updates, these services streamline the device lifecycle, reducing operational complexities and enhancing overall device management. - Security and data protection
Managed Wi-Fi services enable a security posture which is crucial in the IoT landscape. The managed Wi-Fi services offer robust security features to protect IoT devices and the data they generate. By processing sensitive data locally or within a private network using network segmentation, edge devices can minimize data exposure to potential cyber threats as theyβre isolated from other network resources. Managed Wi-Fi services also enable regular security updates and patches to address emerging threats, enhancing the overall security posture of IoT deployments. - Bandwidth management
With the growing adoption of connected devices, scalability becomes a critical factor as transmitting a large amount of data to the cloud for processing can strain network bandwidth and incur significant costs. Enterprise Managed Wi-Fi services are designed to handle large-scale deployments enabling enterprises to seamlessly scale their IoT networks. Enterprises can prioritize critical applications and optimize network resources using advanced bandwidth management techniques to ensure IoT devices receive the optimal bandwidth for their operations, preventing congestion, maintaining smooth communication between devices, and more efficient network utilization. - Reliability and performance
IoT applications and Smart devices often require real-time data exchange and low-latency connectivity. Managed Wi-Fi ensures high reliability and performance for IoT devices by optimizing network configurations and minimizing interference. They employ techniques like load balancing, channel selection, and Quality of Service (QoS) prioritization to maintain a stable and responsive Wi-Fi network. Edge computing reduces the latency required for sending data to a remote cloud server for processing. By processing data at the edge of the network, closer to the devices generating the data, response times can be significantly reduced. It is important for applications that require real-time or near-real-time processing, such as industrial automation and remote monitoring. - Analytics and insights
Enterprise Managed Wi-Fi enables real-time analytics into network performance and device behavior, giving enterprises decision-making capabilities at the network edge. They collect and analyze data on network traffic, device connectivity, and usage patterns, offering actionable intelligence to optimize network resources and improve overall IoT operations. These insights can help identify potential bottlenecks, optimize device placement, and enhance user experiences. Additionally, analytics-driven predictive maintenance can proactively detect and address anomalies, reducing downtime and increasing the lifespan of IoT devices. - Scalability and cost-efficiency
Edge computing allows for distributed computing resources, enabling scalability and cost-efficiency. Instead of relying solely on centralized cloud infrastructure, edge devices can share the computational load and distribute the processing tasks. It can result in reduced network congestion, lower costs associated with cloud resources, and improved scalability to accommodate the increasing number of IoT devices and data volumes.
Wrapping up!
With the growing digital landscape and IoT integration across enterprises, the need to deliver secure, seamless customer and employee experiences become a top priority. Enterprise Managed Wi-Fi services provide a reliable and secure connectivity infrastructure to deliver seamless device management, ensure scalability, optimize network resources, quick & accurate decision making, enhanced production planning, logistics, complete mobility for your workforce, and lower IT support costs.
As the IoT landscape continues to expand, Managed Wi-Fi services will remain crucial in delivering seamless and efficient connectivity for a wide range of applications, enhancing productivity, efficiency, and user experiences.
How to choose the right data center service provider for your needs
During the COVID-19 pandemic, it became increasingly difficult for organizations to manage their in-house data centers due to challenges with scalability, break/fix support, and operations and maintenance staffing requirements. As a result, many organizations moved their in-house data center to a colocation provider and some of their applications to public clouds.
Modern-day data center powerhouses provide not only the necessary infrastructure and state-of-the-art technology but also advanced data analytics and automation capabilities. They offer streamlined operations, business continuity, reduced Capex/Opex, flexible engagement models, superior end-customer experience, support for business expansion, and accelerated digital transformation, among other outcomes.
Selecting the right data center: Key factors in play
Data center service providers typically offer an extensive array of services to accommodate diverse customer requirements. These include on-premise solutions, colocation options, wholesale and retail offerings, hyperscale capabilities, as well as specialized offerings like built-to-suit (BTS) data centers, green data centers, and comprehensive managed services. Businesses can find tailored solutions that align with their specific needs and preferences. It is important to choose the right data center service provider that can provide such integrated services, based on your business objectives and digital priorities.
[Interested to know more about Sifyβs world-class data center facilities? Learn more]
Here are some factors to consider when selecting a data center service provider:
- Scalability: Rack space is a critical and limited commodity for many service providers. Selecting world-class data center providers with the capacity to build campuses capable of accommodating 8,000+ racks and 50 MW IT capacity, for example, will enable businesses to plan their scale-up within their choice campus. They also stand to benefit from a robust support/service stack and comprehensive monitoring of the data center infrastructure.
- Security: Be sure to prioritize data centers with robust security systems. IT infrastructure protection, including data security through encryption, firewalls, intrusion detection, and prevention, needs to be implemented β at the very minimum. Your data center service provider should also have multilayer physical security from the perimeter wall up to the cage, including mantraps, turnstiles, and biometric access control, in addition to surveillance cameras and security personnel, to restrict unauthorized individuals from entering secure areas or accessing confidential information.
- Network connectivity: Choose a data center provider with excellent network connectivity, including multiple internet service providers (ISPs) offering IP transit nodes, high-speed connections, multi-cloud connectivity, data center interconnectivity, and connectivity to customer premises. Data centers should have at least 3-4 fiber entry paths to the building, ensuring seamless connectivity and resilience. Additionally, the presence of low-latency cloud on-ramp services, including cloud access nodes, facilitates fast and direct interconnection with public cloud applications. These aspects collectively contribute to creating a robust, efficient, high-performing, and well-connected data center environment.
- Certificates, SLAs, and compliance: When selecting a data center provider, the importance of having the necessary certificates and service level agreements (SLAs) cannot be overstated. Certifications from industry authorities are highly desirable as they validate the provider’s adherence to industry best practices, process reliability, and security standards. A tier-3 data center with ISO 27001, ISO 20000, PCI-DSS, SoC 1, SoC 2 and ISO 1400, and ISO 50000 certifications is ideal. With its robust compliance framework, 99.99% uptime, and clear SLAs outlining performance commitments, Sifyβs data centers deliver the highest levels of security, operational excellence, and environmental responsibility to customers.
- Industry experience: Data centers that have subject matter experts across functions can prove instrumental in managing diverse workloads. Extensive cross-industry experience gives them the ability to address the unique requirements of various sectors, such as finance or healthcare. For example, as a leading data center service provider in India, Sify has extensive experience across diverse industry sectors. Sifyβs digital data center infrastructure services offer real-time visibility, measurability, predictability, and service support specifically required by different industries to offer customers high availability and seamless experiences.
- Green power: Many organizations today have committed to ESG goals, such as carbon neutrality, waste reduction, and power conservation. In this context, it becomes important to choose a data center provider that is invested in renewable energy, achieved by signing Power Purchase Agreements (PPA). Solar and wind power are increasingly viable options for clean energy. By choosing a data center service provider that adopts sustainable measures including renewable power, energy-efficient equipment, and practices, your business can achieve environmental goals while benefiting from competitive energy costs.
Adherence to safety practices, rules, and regulations are also key EHS considerations. Leading green data center service providers, like Sify, invest in transparent, environmentally conscious, and ethical business practices, adhering 100% to local and global regulations, and outperforming the competition when it comes to sustainability, corporate social responsibility, and people practices.
[Going green? Know how Sifyβs green data centers are pushing the envelope on sustainability. Learn more] - Data center footprint: Data centers strategically located in multiple regions ensure low latency and high-speed network connections, enabling efficient data transmission and improved user experience. A widespread presence allows data centers to establish diverse network routes and redundancy, minimizing the risk of network failures or disruptions.
- Partnership with hyperscalers: Hyperscale partnerships enable data centers to offer seamless integration with leading cloud platforms, offering flexible hybrid cloud solutions and enhanced performance. Ensure you choose a service provider that banks on the power of partnerships and leverages the sharing of expertise and resources to stay at the forefront of technological advancements.
- Automation and innovation: AI/ML-driven automation is increasingly important in developing innovations that optimize operations, reduce costs, enhance performance, improve reliability and sustainability, and elevate service quality. Integration of AI/ML in vendor performance evaluation and SLA management, including metrics like MTTR and MTBF, further strengthens operations. For instance, Sify’s AI/ML capabilities have contributed to significant improvements of over 20% in project delivery turnaround time, showcasing the tangible benefits of data analytics in the data center domain.
- Backup and DR: It is essential to consider the risk of natural disasters such as earthquakes, floods, hurricanes, or wildfires. Select a location with minimal risk to ensure the safety and longevity of your IT infrastructure. It is also crucial to select a data center service provider with adequate backup and disaster recovery (DR) capabilities. This ensures that in the event of an unforeseen incident, the data center can quickly recover operations with little or no data loss.
Wrapping up!
While these parameters will provide you with a solid basis for comparison, allow yourself to make the final decision based on your business’s specific objectives. Remember, there’s no one-size-fits-all approach when it comes to choosing a data center service provider.
As Indiaβs pioneering data center service provider for over 22 years, it has been Sifyβs continuous endeavor to innovate, invest in, and integrate new-age technologies. Learn more about how our state-of-the-art data centers have been delivering transformative business value to enterprises across the globe.
The Modern Marketer Needs a Data-First DAM Solution
Credits: Published by our strategic partner Tenovos.
In an era of increasing personalization, the key to successful marketing campaigns is effective storytelling that reaches the right audience with the right message at the right moment. If this chemistry between audience, content, and timing is the key to success, creative and marketing professionals have to rely on next-generation asset management technology that can guide them toward the right combinations by replacing guesswork with data, and surrounding content with context.
Traditionally, Digital Asset Management platforms (DAMs) have focused on assisting teams to manage their digital assets and move them from inside the organization to external partners and platforms. The premise is simple: a central repository where brands can store their assets alongside relevant metadata to make everything easy to find β photos and videos, logos and tear sheets, and any other brand collateral that needs to be used and reused.
At its most basic level, a good DAM solution enables marketers to do their jobs more efficiently. More modern DAMs employ AI and machine learning to automatically add relevant tags to assets, so teams can spend less time on tedious tasks like tagging or finding assets and more time on the creative and analytical areas of their jobs. The most advanced DAM platforms, however, go beyond managing and moving assets, to actually measuring their performance in their context of use.
Building a DAM for the Modern Enterprise
Over the past 20 years, the pace of change in technology has exploded, while the DAM category has lagged behind in innovation. Brands have come to expect an exceptional, personalized user experience complete with smart insights from their marketing platforms, and DAM should be no exception. As marketing becomes increasingly fast-paced and data-driven, itβs time for a completely new and different DAM experience β one that can meet the demands of an increasingly tech-savvy industry and understands its pain points.
The first and most important question that a DAM provider should ask is, βhow does my solution help marketers do their jobs more effectively?β That is, after all, the central goal of a DAM system: to make it easier and more efficient for creators and marketers to collaborate to design and execute successful campaigns. In other words, if finding an asset within the DAM system and searching through emails to find it take approximately the same amount of time, the system is not making teams more efficient β itβs simply adding a layer of complexity to their martech stack.
Creating a Seamless User Experience
Not all DAM platforms are created equal. One common issue that many enterprises face is the inability to seamlessly integrate their DAM platform with the rest of their marketing ecosystem, which can essentially negate the efficiencies gained by using an asset management solution in the first place. Considering that the code base of many solutions currently on the market is over a decade old (older, in some cases), this is a problem that will only get worse over time as marketers look to incorporate new tools and technologies into their workflows. Consequently, itβs important to find and implement a solution that leverages the use of modern technologies β such as AI/ML, micro-services, graph databases, and serverless environments β that will be able to maintain its speed and flexibility in the years to come.
An organizationβs ability to collaborate seamlessly with team members across β and outside of β the organization is also a key indicator of the success of a DAM implementation. Marketing doesnβt happen in a single silo; from research to ideation, to creation to deployment, marketing is interconnected and interdisciplinary. A modern DAM platform should connect the enterprise in such a way that it simplifies the creative life cycle and enables marketers to reduce the friction and time required to launch each new campaign.
Data-Driven Marketers Need Data-Driven Technology
The reality is that many of the DAM solutions available on the market currently have not kept pace with the evolving needs of the increasingly data-driven marketing operation; theyβre often expensive, difficult to implement, and donβt deliver the user experience marketers and creative professionals have come to expect from their technology. Seen from this angle, itβs not surprising that many organizations are hesitant to invest heavily in a new system that is not capable of demonstrating a return on investment.
Brands need modern DAM platforms that not only enable them to meet the demands of marketing in the digital age, but also help them to demonstrate β and improve β their ROI. Marketers should expect their DAM platform to provide:
- A data-first approach to asset management that allows brands to measure and optimize their processes and their content to provide increasingly personalized experiences
- A seamless user experience that drives adoption and enables teams across the world to collaborate easily
- Performance and optimization capabilities underpinned by artificial intelligence and machine learning
- Continuous improvement and delivery to support the demands of a global omnichannel enterprise
At the end of the day, companies implement a DAM solution in order to optimize their processes and improve their ability to tell the compelling stories that are central to a successful marketing operation. This optimization should come not only in the form of improving the speed of creation, but also the strategy behind a given campaign. A system that has access to all of the contextual data that surrounds your every asset should be able to distill those data into insights that inform the creation of future content.
A modern, data-first DAM should act not only as a content database but also as a source of insight to enable marketers to make smarter creative decisions, which in turn allows them to tell stories that matter to their audience.
Want to know what types of data your DAM should be providing? Reach us at marketing@sifycorp.com
Written by Michael Waldron, CMO, Tenovos
RISE with SAP BTP
Introduction
SAP has unleashed its campaign of βRISE with SAPβ and it has been received very well by SAP customers and ERP prospects worldwide. RISE with SAP transitions ERP data (in the form of SAP ECC6.0 on-premise or SAP S/4 HANA on-premise) to the cloud (public or private) with less risk and without compromise. The bundle of ERP software, transformation services, business platform and analytics is quite an attractive offer to SAP customers having hosted SAP on-premise.
This article delves into the business platform and analytics which is clubbed under βBusiness Technology Platformβ (hereafter called as BTP).
SAP BTP is a cloud-based platform-as-a-service (PaaS) offering from SAP, which provides a set of tools and services for developing, integrating, and extending SAP applications and solutions. SAP BTP supports various cloud deployment models, including public, private, and hybrid clouds, and allows developers to build, deploy, and run their applications using SAPβs cloud infrastructure.
Four pillars of SAP BTP β It encompasses various capabilities that are categorized into following four pillars:-
1. Integration
This feature gives everything that is needed for agile business process innovation, extension, and integration in the cloud and in hybrid scenarios. You can easily integrate different systems, extend your current application, or create new solutions for your business needs with ideal user experience using theβ―SAP Fioriβ―interface. SAP Extension Suite provides various services that can be leveraged to build and extend SAP solutions. SAP Integration Suiteβ―(formally known asβ―SAP Cloud Platform Integration -CPI Suite) lets you seamlessly integrate SAP and non-SAP solutions, both on-premise and in the cloud. SAP Integration Suite covers not only A2A and b2B integration scenarios but B2G(Business to Government) integration scenarios as well.
Currently, SAP provides over 2000+ pre-packed integration scenarios for different business processors. These out-of-the-box integration scenarios are ready-to-use, require minimum development effort, and cover a range of business process integrations. (Check out β―https://api.sap.com/β― for details).
With the introduction of SAP Integration Suite, SAP PI/PO would be getting phased out in near future.
2. SAP Build
It enables everyone β no matter the skill level β to rapidly create and augment enterprise-grade apps, automate processes and tasks, and design business sites with drag-and-drop simplicity.
SAP Build brings together SAP Build Apps (formerly SAP AppGyver), SAP Build Process Automation (formerly SAP Process Automation), and SAP Build Work Zone (formerly SAP Work Zone) into a unified development experience with new innovations to rapidly build apps, automate processes and create business websites.
Low-code / No-code development β Low-code uses both a traditional programming language-based environment combined with no-code platforms and is used by developers with at least basic technical knowledge.
No-code is simpler, and it fully replaces the traditional programming language-based tooling with a suite of visual development tools (ex. drag-and-drop components) and can be used by technical and non-technical people alike.
3. Data and Analytics
The SAP Data sphere component enables accessing authoritative data, helps harmonizing heterogeneous data and thereby simplifies the data landscape.
The SAP Master Data Governance enables operating on high quality, consistent master data and established a comprehensive master data governance
SAP Analytical cloud β It is a single solution for business intelligence and enterprise planning, augmented with the power of artificial intelligence, machine learning technology, and predictive analytics. It helps everyone in your organization make better decisions and act with confidence.
SAP Analytics Cloud removes silos, empowers business analysts, and unifies a companyβs decision-making processes by combining business intelligence, augmented analytics, and enterprise planning into one product. It helps in achieving 360Β° insights with a single connected analytics platform.
4. Artificial Intelligence
It enables business applications and processes more intelligent with the power of AI on SAP Business Technology Platform. Its pre-trained AI models accelerate infusion of AI into Apps. It helps managing the AI model lifecycle into one central place and ensures AI deployment responsibly with transparency and compliance.
SAP solutions such asβ―SAP Intelligent Robotic Process Automationβ―(SAP Intelligent RPA) and machine learning let you automate the kind of complex, repetitive decisions that make up a significant portion of business processes.
Service Catalog β SAP has come up with a rich repository of readily available 96 services encompassing one or more of the four pillars mentioned earlier. They help in integrating and extending your solutions, optimizing your business processes, and thereby creating an engaging digital experience using SAP Business Technology Platform services. Just to give an idea, some of the services are listed below:
- Automation pilot β Simplify the operational effort behind any cloud solution in the SAP BTP.
- Cloud foundry runtime β It lets you develop polyglot cloud-native applications and run them on the SAP BTP Cloud Foundry environment
- Cloud Integration for data services β To integrate data between on-premise and cloud on a scheduled/batch-mode basis.
- Continuous Integration and Delivery (CI/CD) β It lets you configure and run predefined continuous integration and delivery pipelines that automatically build, test, and deploy your code changes to speed up your development and delivery cycles.
- Identity provisioning β Lets you manage Identity Lifecycle processes for cloud and on-premise systems
- Kyma runtime β Develop and run containerized applications and extensions on Kubernetes. Kyma runtime is a fully managed Kubernetes runtime based on the open-source project βKymaβ. This cloud-native solution allows the developers to extend SAP solutions with serverless functions and combine them with containerized microservices. The offered functionality ensures smooth consumption of SAP and non-SAP applications, running workloads in a highly scalable environment, and building event- and API-based extensions.
- SAP AI core β It enables building a platform for your artificial intelligence solutions. It is designed to handle the execution and operations of your AI assets in a standardized, scalable, and hyper-scaler-agnostic way. It provides seamless integration with your SAP solutions. Any AI function can be easily realized using open-source frameworks. SAP AI Core supports full lifecycle management of AI scenarios.
SAP BTP Deployment β Salient points:
- Regions β You can deploy applications in different regions. Each region represents a geographical location (for example, Europe, US East) where applications, data, or services are hosted. A region is chosen at the subaccount level. For each subaccount, you select exactly one region. The selection of a region is dependent on many factors: for example, application performance (response time, latency) can be optimized by selecting a region close to the user. The global account itself is also running in a region.
- Environments β Environments constitute the actual Platform as a Service offering of SAP BTP that allows for the development and administration of business applications. Environments are anchored in SAP BTP on the subaccount level.
Each environment comes equipped with specific tools, technologies, and runtimes that you need to build applications. So a multi-environment subaccount is your single address to host a variety of applications and offer diverse development options. One advantage of using different environments in one subaccount is that you only need to manage users, authorizations, and entitlements once per subaccount, and thus, grant more flexibility to your developers.
- SAP BTP can have one or more global accounts. Global accounts are associated with license or contract which your company has with SAP BTP. Global account takes care of the license and contract and whatever the activities you perform or how you are billed is managed by global account.
- Global accounts are linked with entitlements which are passed down to subaccounts. Entitlements are the kind of resources provided to you based on the license that you purchased.
- Sub account is the place where you will be creating your PaaS environment(cloud foundry/Kyma).
- SAP BTP Cockpit β The SAP BTP cockpit is the central user interface for administering and managing your SAP BTP accounts as a platform user. To access the SAP BTP cockpit, you need to open a specific URL ‘https://cockpit.<region>.hana.ondemand.com’. You can replace the <region> with the one you are operating in (for example: eu10, us10, ap10) to have a lower response time and latency to the cockpit. After logging in with your user credentials, you might get prompted with a pop-up to choose the global account you want to access. Of course, you are able to switch between the global accounts as and when needed.
- Working with the SAP BTP cockpit is the easiest way to manage and administer your SAP BTP accounts.
Conclusion:
SAP has come up with a lot of helpful resources related to BTP including use cases, case-studies, readily available services, pre-packed integration scenarios, tutorials etc. BTP offers a rich load of tools/services which would enable your organizationβs business transformation and expedite your digitization journey. It needs to be fully leveraged when you opt for βRISE with SAPβ.
The role of data analytics and AI/ML in optimizing data center performance and efficiency
Data centers have emerged as a crucial component of the IT infrastructure of businesses. They handle vast amounts of data generated by various sources, and over the years have transformed into massive and complex entities. Of late, data analytics has emerged as a necessary ally for data center service providers, powered by the growing need to improve parameters like operational efficiency, performance, and sustainability. In this blog, we will discuss the different ways in which data analytics and AI/ML can help enhance data center management and empower data center service providers to deliver better service assurance to end-customers.
How data analytics and AI/ML can help service providers in data center optimization
Today, data center service providers are leveraging data analytics in various ways to optimize data center operations, reduce costs, enhance performance, reliability and sustainability, and improve service quality for customers. They employ a variety of methods to collect data from colocation, on-premise and edge data centers, which include physical RFID/EFC sensors, server, network and storage monitoring tools, security information and event management (SIEM) systems, configuration management databases (CMDBs), API integration, and customer usage data. The data collected is then fed into a centralized monitoring and analytics platform, which uses visualization tools, dashboards, and alert systems to analyze the data and generate insights.
Furthermore, by integrating IoT and AI/ML into data center operations, service providers are gaining deeper insights, automating various processes, and making faster business decisions. One of the most critical requirements today is for analytical tools that can help with predictive assessment and accurate decision-making for desired outcomes. This is achieved by diving deep into factors such as equipment performance, load demand curve, overall system performance, as well as intelligent risk assessment and business continuity planning. Selection of the right tools, firmware, and application layer plays a major role in making such an AI/ML platform successful.
The relationship between analytics and automation from the perspective of data centers is rather symbiotic. Data centers are already automating routine tasks such as data cleaning, data transformation, and data integration, helping data center service providers free up resources for more strategic analytics work, such as predictive modeling, forecasting, and scenario planning. In turn, data analytics provides valuable insights that enable data centers to implement intelligent automation and optimization techniques. This may include workload balancing, dynamic resource allocation, and automated incident response.
Here are some of the key areas where data analytics and automation have a significant impact:
- Enhancing operational reliability: Data analytics, AI/ML and automation can enable data centers to ensure optimal performance. This involves using predictive maintenance, studying equipment lifecycles for maintenance, and incident history analysis to learn from past experiences. In addition, AI/ML-driven vendor performance evaluation and SLA management incorporating MTTR and MTBF further strengthen operations. Leveraging these metrics within the ITIL framework helps data centers gain valuable operational insights and maintain the highest levels of uptime.
- Performance efficiency: Data centers consume a substantial amount of energy to power and maintain desirable operating conditions. To optimize services, track hotspots, prevent hardware failure, and improve overall performance, modern data centers analyze data points such as power usage, temperature, humidity, and airflow related to servers, storage devices, networking equipment, and cooling systems. Prescriptive analytics can take this a step further by providing recommendations to optimize utilization and performance.
- Predictive maintenance: Predictive analytics is a powerful technology that uses data to forecast future performance, identify and analyze risks and mitigate potential issues. By analyzing sensor data and historical trends, data center service providers can anticipate potential hardware failures and perform maintenance before they escalate, with advanced predictive analytics enabling them to improve equipment uptime by up to 20%.
- Capacity planning: Businesses today must be flexible enough to accommodate capacity changes within a matter of hours. Data center service providers also need to understand current usage metrics to plan for future equipment purchases and cater to on-demand requirements. Data analytics helps in optimizing the allocation of resources like storage, compute, and networking while meeting fluctuations in customer needs and improving agility.
- Security and network optimization: Data centers can use analytics to monitor security events and detect vulnerabilities early to enhance their security posture. By analyzing network traffic patterns, data analytics tools help identify unusual activities that may indicate a security threat. They can also monitor network performance, identify bottlenecks, and optimize data routing.
- Customer insights: Data centers collect usage data, such as the number of users, peak usage times, and resource consumption, to better understand customer needs and optimize services accordingly. Analytics helps providers gain insights into customer behavior and needs, enabling them to build targeted solutions that offer better performance and value. For example, through customer-facing report generation, organizations and end-customers can gain valuable insights and optimize their operations. Additionally, analytics accelerates the go-to-market process by providing real-time data visibility, empowering businesses to make informed decisions quickly and stay ahead of the competition.
- Environment sustainability & energy efficiency: Data centers have traditionally consumed significant power, with standalone facilities consuming between 10-25 MW per building capacity. However, modern data center IT parks now boast capacities ranging from 200-400+ MW. This exponential growth has led to adverse environmental impacts, such as increased carbon footprint, depletion of natural resources, and soil erosion. Using AI/ML, performance indicators like CUE (Carbon Utilization Effectiveness), WUE (Water Utilization Effectiveness), and PUE (Power Utilization Effectiveness) are analyzed to assess efficiency and design green strategies, such as adopting renewable energy, implementing zero water discharge plants, achieving carbon neutrality, and using refrigerants with low GHG coefficients. For example, AI/ML modeling can help data centers achieve 8-10% saving on PUE below design PUE – helping to balance environmental impact with an efficiency better than what was originally planned.
- Asset and vendor performance management: The foundation of the AI/ML platform lies in the CMDB, which comprises crucial data, including asset information, parent-child relationships, equipment performance records, maintenance history, lifecycle analysis, performance curves, and end-of-life tracking. These assets are often maintained by OEMs or vendors to ensure reliability and uptime. AI/ML aids in developing availability models that factor in SLA and KPI management. It can provide unmatched visibility into equipment corrections, necessary improvements, and vendor performance. It can also help enhance project models for expansion build-outs and greenfield designs, accurately estimating the cost of POD (point of delivery) design, project construction, and delivery.
- Ordering billing and invoicing: AI/ML plays a vital role in enhancing the efficiency and effectiveness of order, billing, and invoicing processes. Its impact spans various stages, starting from responding to RFPs to reserving space and power, managing capacity, providing early access to ready-for-service solutions, facilitating customer onboarding, and overseeing the entire customer lifecycle. This includes routine processes such as invoicing, revenue collection, order renewal, customer Right of First Refusal (ROFR) management, and exploring expansion options both within and outside the current facility.
Selecting the right data analytics solution
The implementation of data analytics and automation through AI/ML requires careful consideration as several parameters, such as data quality and level of expertise play a crucial role in delivering efficient end-results. To succeed, businesses need to choose user-friendly and intelligent solutions that can integrate well with existing solutions, handle large volumes of data, and evolve as needed.
At Sify – Indiaβs pioneering data center service provider for over 22 years, we continuously innovate, invest in, and integrate new-age technologies like AI/ML in operations to deliver significant and desired outcomes to customers. We are infusing automation led by AI/ML in our state-of-the-art intelligent data centers across India to deliver superior customer experiences, increased efficiency, and informed decision-making, resulting in more self-sustaining and competitive ecosystems. For example, leveraging our AI/ML capabilities has been proven to lead to over 20% improvement in project delivery turnaround time. Our digital data center infrastructure services offer real-time visibility, measurability, predictability, and service support to ensure that our customers experience zero downtime and reduced Capex/Opex.
How do Sifyβs AI-enabled data centers impact your business?
- Person-hour savings: Automation of customer billing data and escalations resulting in up to 300 person-hour savings in a month.
- Reduction in failures: Predictive approach for maintenance and daily checks yielding up to 20% reduced MTBF, 10% improved MTTR, and 10% reduction in unplanned/possible downtime.
- Cost savings: Improved power/rack space efficiency and savings on penalties to deliver up to 8% reduction in customer penalties by maintaining SLAs and 10% reduction in operating cost.
- Compliance adherence: Meeting global standards and ensuring operational excellence and business continuity.
To know more about our world-class data centers and how they help enterprises expect positive business outcomes, visit here.
