Month: January 2022

How IoT is Disrupting Various Areas and Industries: A Quick Insider

Posted on by stridely

IoT – Internet of Things, is currently disrupting every sector. If we talk about the market size, IoT is expected to grow at a rate of 25.4% in the next 7 years (2021-2028). Yup, this is massive!

In 2022, you may expect the technology to drive significant revolutionary changes in how we do things and how we perform business operations. Industries, from Oil & Gas to metallurgy, all challenging sectors are benefitting from the improvement in related technological implementations, caused by IoT.

Business Solution: Unified IoT Platform

Growth of IoT: Major Areas of Disruption

IoT is evolving very rapidly. To under its current usage scope, we can begin our discussion by pondering over the areas that are fully transformed since IoT’s arrival. Here is our list:

  • Sensing (or Sensors)

IoT sensors can replace humans in the field, facing harsh conditions, just to get a few readings. Besides taking the reading, the delivery of captured data need not be noted down manually in computer systems today.

Be the humidity, temperature, pressure, velocity, proximity, acceleration, deviations, or fluid levels, IoT sensing endpoints can capture all details and send the data to monitoring systems in real-time. Not just that, these sensors can also figure out the composition of components in various mixtures. So, the healthcare, chemical, mechanical and other industries can also utilize sensors to operate more efficiently.

Major Highlight about IoT Sensor Technology Disruption

IoT laid the foundation of the Industry 4.0 revolution and smart (fully-automated) companies. When combined with smartphones, wearables, artificial intelligence, and machine learning, sensors can serve a huge number of purposes. The best part is, IoT sensors are pocket-friendly and can reduce the total cost of ownership for ventures.

Success Case: IoT Framework For Retail Industries: Entering Into The World Of Connectivity

We can expect that next-gen sensors will be more precise, fast, and varied.

  • Device Communication

IoT network comprises ‘Things’. These things are interconnected and perform various actions through communication via the internet. IoT communication-enabler components form the core of IoT infrastructure, connecting devices, clouds, sensors, and people using gateways, routers, and related platforms.

As per Gartner, the market of enterprise IoT connections and automation due to these connections – alone –  is expected to grow by 20%. The reasons behind this trend are speed, experience, and utility of wireless interconnection between IoT components alongside the benefits these aspects, all combined, result in.

Major Highlight about IoT Communication Disruption

Considering this demand chart, innovations related to IoT communication are also on the rise.  WiFi 6.0, Bluetooth 5.2, and other communication protocols are being updated to match the needs of IIoT (Industrial IoT sector).

Success Case: Asset Monitoring Web Portal With Azure And IoT

  • Security

The use of personal and professional devices and various other lockdown challenges surround us every day. There is a huge surge in the number of cyberattacks, threats, and compromises this year. The 2 reasons why conventional security-related technological solutions do not fit their current deployment scenario anymore are:

  1. Implementation of IoT
  2. Remote working culture that COVID (almost) forced upon us

Major Highlight about IoT Security Disruption

IoT promotes hyperconnectivity for users. With the always-connected approach and the variety of devices come cybersecurity challenges that are essential to be addressed. This fact has made enterprises upgrade their security strategies.

Also Read: Enable your Legacy device to Modern IoT Cloud through TCP Connection

Security automation, changes in security standards, AI-based security implementation, threat intelligence, and ML-enabled (machine learning) security tools are the trends that IoT’s industrial adoption has initiated.

  • Data-sharing and Analytics

IoT sensors and other devices can communicate in real-time and deliver data at a very fast pace. The amount of this data is too huge to be processed manually.

Also, as the data is arriving in real-time and is available for immediate decision-making, businesses look forward to automating the analysis process. This practice enables them to curate Big Data faster and gather insights that are trustable.

Major Highlight about IoT Analysis and searching Disruption

IoT sensors and communication mechanisms suit the best for training the AI models. Predictive analytics and analytics of live streams are the two disruptive trends based on this IoT function.

As the driving force of business intelligence, IoT is (indirectly) also capable of luring enterprises and other businesses to shift to the cloud and perform necessary analytics in real-time.

To ensure security in such a fast-paced environment, blockchain can ensure secure and encrypted communication. So, IoT is also promoting the use of blockchain technology to some extent.

Internet of Things + Artificial Intelligence

IoT provides reliable means for gathering the data and transmitting it faster. It connects networks in a truly hyperconnected manner. The technology can keep generating a huge heap of data with or without human interaction.

Download Guide: AI Builder

On the contrary, Artificial Intelligence requires a huge amount of data for model training and precise operations. This dataset can help the technology take better, and more human-like, decisions while improving the actions it triggers.

This makes IoT and AI a perfect match. The duo can change the facet of various industries and can transform the way of doing industrial operations.

A Few Transformations Driven by IoT

  • Healthcare equipment like health monitoring systems and wearable devices utilize IoT.
  • Weather monitoring systems and crop health monitoring sensors help the agriculture sector in boosting productivity and preventing/reducing losses.
  • GPS, fleet monitoring systems, and traffic monitoring sensors have transformed the way we travel or transit goods.
  • Sensor-enabled doors, lifts, train/bus gates, and escalators have made it simpler for us to navigate through places and within our homes/offices.
  • Heavy Field jobs, like finding oil reservoirs by digging, are transformed. Now, various sensors are used to confirm the presence of reserves in an area. With this, multiple laborious tasks are removed from the process.
  • IoT forms the fundamental component of smart cities, smart factories, smart homes, self-driven cars, and other intelligent solutions.

The Final Word

The Internet of Things is an important technology. It has changed the common method of performing various operations. The hyperconnected mechanism of IoT ensures real-time operations, faster processing, higher productivity, less human involvement in the process, and cost-effectiveness. However, it might demand more security and storage space alongside the migration of your business to the Cloud, to begin with.

Hire Stridely professionals for IoT solution development or digital transformation through migration to the Cloud. It will transform your ROI (Return on Investment) and TCO (total cost of ownership) statistics in a positive manner. We also have BI experts to help you out with full enterprise business process transformation

 

 

Effective and Viable Data Strategy – The Key to Business Success in Modern Times

Posted on by stridely

Establishing and running a business demands many things and a viable data strategy tops the chart. This is no longer a hidden fact that quality data and its effective utilization is what places a business way ahead in the competition. The fate of data is decided by implemented data strategy. The efficacious strategy is, lucrative are the outcomes.

Starting from improving the data quality to providing deeper insights to the organization, a smartly designed data strategy can do wonders. The post educates businesses and enterprises about the significance of data strategy, its key components, challenges, and viable way to fix them.

Also Read: SAP Master Data Governance – Streamlining Business Processes

Data Strategy – Meaning and Significance

By definition, a data strategy is a plan designed to manage the business data in a way that it brings out the maximum outcomes and support business growth. By making most of the offered data, data strategy empower businesses to be future-ready and churn out better ROI. Implementation of data strategy allows businesses to:

  • Define and explain the utility of data in a given scenario;
  • Decide how and where data should be used;
  • Depict the changes that organization must make in the operation to drive maximum value from the data activities;
  • Create a timeline for every data utilization activity;
  • Define the financial outcome for the data set and create plans to turn them into reality.

Why Data Strategy Is Important?

Data strategy can be called a pillar of success for the organization, but why? Scroll down to figure out this.

  • Allowing unleashing the full power of data

Today, data is the gold for businesses, provided it’s interrupted and consumed the right way. This can only be done with the help of a data strategy. A well-designed data strategy can answer questions like ‘What is big data, ‘Where should this data be used’, ‘what to expect from certain data-set, and ‘how employees can make most of the offered data’.

Download Guide: Open Data Initiative

Having these questions resolved allows organizations can easily explore the full power of data and utilize it for maximum fruition.

  • Zero data wastage

Data volume is increasing with each passing day and organizations are having a tough time managing this asset. The expanded data volume tends to do cause huge data wastage, which no organization can offer. With data strategy, one can juice the data up to a maximum extent and reduce the data wastage.

  • Better data management in the least possible efforts

Data management is a very tedious job. Despite that, one can’t turn a blind eye towards this action as data, with is not effectively managed, is not good for the organization’s well-being.

Data-related issues should be fixed in the infancy stage and organizations must define data access and usage criteria. Generating a company-wide data strategy addresses all these data issues effectively and allows each department to work towards the same cause.

  • Proficient use of resources

The absence of a data strategy will force different departments to use data as per their needs. This separate data handling is time-consuming. Data strategy offers a standard data utilization format across the organization. With this pre-defined data usage strategy, organizations are allowed to speed up the data utilization process while keeping resource wastage as little as possible.

Key Components of Viable Data Strategy

Now that you’re aware of the utility of data strategy and the wonders it can do to an organization, it’s time to get familiar with the elements shaping a high-end data strategy.

Component #1 – Data

Of course, data is the prime part of a data strategy. A strategy should feature the strategic value of data, validating its quality, integrating processes, and policies governing its key usage. Additionally, enterprise data catalog should be a part of data strategy as this component allows organizations to make data available for usage and explain to the team where data resides.

Component #2 – Data tools

Data analysis is not something that humans can handle alone. They need the help of high-end tools to automate the menial jobs and expect the best-possible accuracy. A doable data strategy should feature key data tools to use and, if possible, their utility process.

Data tools are of all kinds and types. Some are easy while few are complex. One must make a choice as per the need of the hour. Make sure that data visualization, dashboard, and reporting tools are included in the data strategy.

Component #3 – Analytics techniques

Just like data tools, there are ample analytics techniques offered. For instance, there are data visualization, text analytics, predictive analytics, and so on. When demanded oversight is offered, analytics techniques provide the best value of a data strategy. Based on the team’s understanding and capacity, organizations must define analytics techniques in the data strategy.

Component #4 – Collaboration

To make sure the data strategy is implemented effectively, collaboration should be of a higher grade. Starting from data preparation to data governance, collaboration is essential. The use of collaborative tools makes discussion and debating easy and allows organizations to figure out the utility of the strategy.

Component #5 – Documentation and auditing

Data strategy should be well documented and audited to figure out what’s approved, what’s appropriate, what’s the purpose, and what’s the governance policy, and answers to many other questions. A good documentation and auditing technique allows providing a good explanation of data strategy and fundamental data architecture.

Component #6 – People

As your team and included people are going to use the data strategy, it should revolve around the people. Also, make sure that the right people are a part of it. For instance, data scientists, in-house or outsourced, should handle the data strategy.

Also, enough IT and data management resources should be in place. The right kind of people will make better availability, instant disaster recovery, and better adherence with service-level agreements possible.

Challenges to Face

Despite acknowledging the power of data strategy, many organizations don’t bring it into action. The reason being is its tedious nature. It takes a lot of design and implementation of a data strategy. Have a look at them.

  • Businesses have a tough time figuring out the aim of data strategy. They know they have data and they know that they have certain issues to address. But, they don’t know how to make data work for those tasks. Defining the aim of a data strategy needs someone having deeper organizational and data-related understanding. Big enterprises can hire professionals for this job. The real hurdle is for start-ups and small businesses as the surged expenses involved in this task are beyond their capacity.
  • In a team, it’s obvious to have different skills level and this dissimilarity is a major hindrance for organizations.
  • Don’t consider your job done once you have a data strategy in place. One has to monitor its utility continuously. This adds an extra burden for organizations. Some even got tired of this ongoing task.

The Possible Solution

While one expects maximum outcome from data strategy, addressing these and many other hidden challenges is imperative. As not every organization can afford to have a dedicated team of Data developers or Data scientists, it’s wise to outsource data analysis services.

Success Case: Deploying Next-Gen Business Intelligence Solution For Telecommunications Industry

Many leading service providers, like Stridely Solutions, lend a helping hand to small businesses and start-ups in designing, implementing, and monitoring data strategies. Having such professional help ensure the best possible outcome from the at-work data strategy.

Ending Notes

Data, when used effectively, can change the fate of a struggling business. The practicable data usage can only be achieved from a diligently-designed data strategy. One must not shrug it aside just because it’s tedious and taxing. Taking the professional help of Stridely Solutions is the easiest way to have a worthwhile data strategy by your side while investing the least possible efforts.

 

Next-Generation SAP Managed Services: What All Your Enterprise Can Avail?

Posted on by stridely

SAP never disappoints its users and endows them with inventive and updated solutions. This is why it’s one of the most preferred and dependable ERP solutions in the market, holding a 24% share. The tools have become a crucial operational aspect for all sorts of businesses, regardless of the industry type and business size.

While using SAP resolves many operational hurdles, its effective implementation is what reaps all these benefits. SAP Managed services is a feasible way to make this happen.

Also Check: Run Enterprise Applications with SAP Solution Manager Solutions

By taking off the burden of upright and optimized implementation and management of SAP solutions from businesses’ shoulders, SAP Managed services warrants for better ROI and conversed focus on business-critical operations.

SAP Managed Services: A Sure-shot Way to Leverage the Most from your Existing SAP Implementation

Depending upon the needs, SAP implementation can be of various kinds and complexities. The SAP ecosystem is a bit complex as tons of applications and solutions are deployed on the cloud and need to be managed effectively.

S/4HANA migration comes with its own set of struggles. With SAP Managed services, businesses are allowed to enjoy only the perks of SAP and ditch the complexities involved in the implementation and management.

Success Case: SAP S/4 HANA Implementation On Cloud: Machinery Manufacturing Company 

This is enough reason for businesses to adopt SAP-managed services. In fact, many of them have already done this as market predictions indicated that the SAP managed service market is likely to hit the mark of $282 billion as we reach towards the end of 2023.

The operations that customary SAP manages services handle are:

  • Application support and testing
  • Resource optimization and upgrade
  • SAP solution advisory and consulting
  • Application stabilization
  • Remote monitoring of SAP solutions
  • Fully managed to host
  • Service delivery management
  • SAP solution maintenance

With cutting-edge and ultra-modern SAP managed services, one can experience certain exceptional facilities that were absent in the customary SAP managed services.

Here is a crisp overview of them:

  • Exceptional Transparency At Operational and Performance Front 

With next-gen SAP managed services, CIOs and the IT teams of an organization are likely to have ultimate peace of mind as they will be able to find out whether or not the deployed SAP solutions are in their pink health. The task can only be achieved by keeping an eye on the SAP systems’ performance and health over time, which was beyond the capabilities of traditional SAP-managed services.

Their operational areas were limited to deploying SAP solutions, providing updates, and customizing the features. The offered periodical performance reports, by old-fashioned SAP, managed services, weren’t enough to adhere to SLA compliance and knowing the overall SAP system’s health.

The ultra-modern SAP managed services are free to form this loophole and are able to provide continual and comprehensive SAP system health reports. The ongoing performance monitoring is a great way to spot any future complications in their infancy stage and create a viable remedial solution.

  • Automation of SAP Landscape In Performance-based Cloud and Hybrid Ecosystem 

SAP managed services of today’s era goes a step ahead when it comes to maintaining the SAP solutions deployed on cloud and hybrid ecosystem. Cloud and hybrid-based deployment have gained commendable popularity in recent times as it grants facilities like reduced operational cost, enhanced productivity, and leveraged resource accessibility.

SAP managed services offering SAP cloud migration and performance-driven cloud scaling endows enterprises to manage the hybrid landscape and switch between on-cloud and on-premise solutions easily while saving huge operational costs.

Success Case: SAP S/4 HANA Migration : Utilities Gain Flexibility And Optimization With Operational Excellence

Along with the landscape management, modern SAP managed services are able to grant in-depth visibility to the SAP system’s performance while the SAP landscape modifies automatically as per the enterprise’s needs.

This was not the case with earlier SAP managed services and end-users didn’t grant any visibility to the behind-the-curtain operations. This lack of visibility failed enterprises to spot the resource scaling requirements and continue with the lacked SAP capabilities. It was a sheer wastage of resources and caused the unknowing shutting down of crucial activities.

The facility of hybrid and cloud automation, offered by next-gen SAP managed services, empowered enterprises to scale the SAP solution in real-time and optimize the performance accordingly.

Read More: The Right Time to Migrate to SAP S/4 HANA

  • Real-time Forecasting and Predictive Analysis  

Enterprises, using cutting-edge SAP managed services, are bestowed with high-end forecasting and predictive analysis abilities. Using this ability, organizations of all sorts can do better budget planning and resource optimization.

Such improved SAP managed services delve deep into the past resource utilization and figure out the viability of a hired SAP solution in the real world. This detailed analysis will allow end-users to decide which solution is bringing the best outcome for enterprises.

Based upon the analysis details, enterprises can predict the future SAP solutions needs and make an informed decision. It’s a viable way to keep the operational costs under control as only useful resources are purchased this time.

Additionally, the analysis is useful to plan the work schedule of the hired resources and receive timely updates. This is the game-changer ability for organizations having multiple serves and they can schedule the server updates as per the needs of the hour or based upon the utility rate.

Using such detailed SAP managed services ensures that the money is invested visibility and only those SAP solutions that will bring the best ROI.

  • Continual Monitoring and Management of Business Processes 

Enterprises will get benefitted greatly from modern SAP managed services offering process monitoring and management. With such inventive SAP managed services, manufacturing industry-related enterprises are allowed to monitor the business processes in real-time and spot the hidden business process abnormalities.

This ability allows manufacturing enterprises can reduce the impact of business process damages without hampering the actual productivity. Here is a real-world example of this ability:

Suppose a manufacturing enterprise has a business process attached with the label printers and facing issues. Today’s advanced SAP managed service provider will act proactively and spot the issue in infancy stag, reset the printer, and will automatically fix the trouble. 

This high-end automation at business process anomaly detection wasn’t experienced before. Nonetheless, it’s here to assist enterprises today and allow them to expect improved cost optimization and enhanced business processes.

  • Promptness at Operational Audits 

Auditing is a crucial part of every enterprise and can’t be ignored at any cost. Audit deals with various aspects; the key ones are ensuring implementation of market security’s best practice and their continual operability.

Traditional SAP managed services didn’t realize the worth of audits and failed to offer audit readiness to the enterprises. The best assistance offered, related to audits, with old-school SAP managed services is collecting the data for audits. That’s it. Nothing added efforts are made for completing the audits process.

Also Read: A full SAP Security Checklist for your Enterprise

With advanced SAP managed services, the audit can be handled at each stage. They go beyond collecting the data. They can monitor all the audit points and create detailed reports automatically.

Creating an audit report is a time-consuming task and when next-gen SAP managed services can take care of this task then enterprises enjoy ultimate peace of mind and are allowed to focus on key business processes.

Also, timely and data-driven audit reports ensure that enterprises are adhering to the best security and compliances practices.

Choose the Right SAP Managed Service Provider 

Seeing the sheer volume of benefits that SAP-managed servicer brings, it’s hard to maintain a safe distance for them. While you think of availing of SAP managed services, selecting the dependable managed service provider is a tough task as there are many key players in the market.

Only a forward-thinking MSP or managed service provider holds the ability to bring these perks to enterprises. Here is what one should keep in mind while selecting the SAP managed service provider:

  • Make sure that the selected SAP managed service provider offers all the SAP managed services. Doing so saves a huge deal of time, effort, and money invested in SAP solution management and one subscription can take care of all the needs. The key SAP services to watch out for are SAP Cloud Services, SAP Hosting Services, SAP Application Management Services, SAP Business Suites – SAP ECC, SAP HANA Operations Services, and SAP S/4 HANA migrations and implementation.
  • Opt for an SAP managed service provider who has in-house SAP experts with a proven record of accomplishment. The more experience managed service provider has in the industry and domain, the better service experience an enterprise is likely to encounter. With in-house experts, immediate assistance is a sure thing.
  • Quality assurance should be done based on the SAPCenter of Excellence (SAP CoE). There shouldn’t be any other criteria for determining the quality offered by MSP as it’s a globally recognized quality standard. SAP is a huge landscape and ensuring quality is a tedious task. If the picked SAP managed service provider is SAP CoE certified then no further research is needed.

The Final Say

SAP is a highly powerful ERP solution allowing enterprises to introduce the greatest productivity, optimized performance, and better cost utilization at every front. However, one can expect all these privileges only when SAP solutions are need-based, optimized, and managed continuously.

This is where SAP-managed services by Stridely Solutions come to the rescue. Present day’s expert SAP solution managers go a step beyond and grants facilities like performance monitoring, audit readiness, continual business process monitoring, and many others. Having such advanced SAP managed services allows enterprises to improve productivity and ROI of hired SAP solutions.

 

 

Planning Hybrid, Multicloud, and Edge Cloud Strategy With Azure: Why and How?

Posted on by stridely

The launch of cloud computing is one of the most historical events as it empowered enterprises to cut down the operational cost, efforts invested to set up the core infrastructure, and tediousness involved with system maintenance significantly.

It matured as a norm and compelled around 90% of businesses to adopt it. Seeing the surge in cloud computing adoption, market predictions say that the cloud computing market is going to touch the mark of $832.1 million by the time 2025 ends.

One key trait of cloud computing that enforced the enterprises to displace the legacy infrastructure model with this inventive approach is its ability to offer solutions as per the need of the hour. Diverse choices are offered to end-users. They can go with hybrid, multi-cloud, and edge cloud computing.

While adopting cloud computing is the goal, Microsoft Azure has emerged as a viable choice. As per the company’s data, around 206,009 companies are using this solution. It accounts for 27% of the total cloud computing market, which is a significant one.

Also Read: Microsoft Azure Logic Apps: Everything a Business Needs to Know

Since the commencement, Microsoft strived to deliver nothing but the best to its customers. Recently, Microsoft Ignite week happened and the industry’s veterans ponder over the utility of Microsoft Azure in planning and managing the multi-cloud, hybrid, and edge cloud strategy. We are presenting the excerpt of that in this blog.

Azure Arc – A Game-changer For Hybrid and Multi-Cloud Ecosystems

Depending upon the organizational needs, cloud solutions can be spread across thousands of servers and handle multiple applications. Maintaining security protocols and handling the distributed ecosystem of these solutions is the biggest challenge for the organization.

To address this issue in the best possible manner, Microsoft has launched Azure Arc. This newly launched solution is software enabling Azure users to safeguard the resources deployed over the multi-cloud and on-premises environment, using Azure Resource managers. Resources like Kubernetes clusters and physical/virtual servers can be easily managed by Azure Arc. Usage of Azure Arc permits end-users to manage all resources from a unified platform.

Also Read: MS Azure Cloud Automation — Things to Consider and Best Practices

It even makes enjoying the detailed security, governance, and management abilities of Azure to manage SQL server, Linux, Windows, and Kubernetes deployment, regardless of the deployment location. Edge, datacenters, and multi-cloud can be managed with equal ease and perfection while Azure Arc is at work.

Additionally, Azure Arc endows end-users to produce inventive and intelligent solutions in any cloud deployment environment using the first-hand Azure offered ML, data, and application services.

Microsoft also announced the launch of updated expertise of Azure Arc, especially for hybrid and multi-cloud solutions.

Azure Arc is now offered for VMware vSphere and Azure Stack HCI. Hence, organizations utilizing these two solutions are allowed to secure the present virtual machines and Kubernetes solutions with Azure Arc. Alongside, those who are planning to migrate from on-premise to Azure VMware are eligible for performing the VMs lifecycle management from the Azure portal.

Machine learning abilities of Azure Arc have gone through the commendable update and permit end-users to get ready deployed machine learning models from anywhere.

Azure Arc offers a directly linked mode that can be used to deploy, secure, and manage the databases.

Organizations that were looking for a way to set up an inventive cloud-deployed desktop and application virtualization way out will be benefitted greatly from Azure Arc as it offers Azure virtual desktop. This service is offered on Azure Stack HCI and can fix the latency and regularity issues.

Also Read: How to Accelerate Time to Value for your Hybrid IT Strategy with Microsoft Azure?

Microsoft Defender is now more capable to protect and manage the multi-cloud as its Cloud Security Posture Management (CSPM) and Workload Protection abilities get a makeover and permit end-users to safeguard all their multi-cloud solutions from a centralized place.

Azure migration and modernization are also received the full support of Azure Arc and end-users are allowed to use all its features to make migration smooth and seamless.

All the above-mentioned Azure Arc updates were as per the need of the hours and get welcomed by the industry. This explains why many leading names such as Royal Bank of Canada and MAPFRE have shown their trust in Azure Arc and handed –over the task of managing multi-cloud and hybrid cloud solutions in its hands.

Royal Bank of Canada is currently benefitted from Azure Arc-enabled data services. Its mammoth data collection is managed easily by the solutions.

MAPFRE chose Azure Arc to protect and govern its thousands of Linux and Windows servers.

Azure – The Dependable Resource for Edge Computing

Out of all sorts of cloud computing types, edge computing is the freshest. Yet, it has managed to receive enough attention. The edge computing market was at the mark of $1.734 billion in 2017, and is likely to get close to $16.557 billion by 2025,

It’s a distributed computing approach that aims to bring data storage and computation closer to the location where these two resources are required at a particular time. While this type of computing reaps multiple benefits, it necessitates a wide range of intelligent cloud and distributed solutions as the application managed to edge computing must be competent to operate in a connected and disconnected state with equal perfection.

Read more: Achieve more with Serverless Applications: Build on Azure and Publish with PowerApps

Azure comprehended well the demands of cloud computing and has weaved its capacities in a way that they are apt for edge computing planning, deployment, and management. Have a look at them.

  • Azure is built in a way to offer consistency across the entire programming model, AI used, data services used, and DevOps solution so that the management of edge computing deployments is efficacious.
  • To ensure edge computing deployments are adequately protected and secure, Azure Security Center offers unified security management and threat protection solutions. The solutions feature protection against specific risks that are present only for edge computing deployments. Azure Sphere’s security is the ideal example.
  • Edge computing needs a unified identity control solution and Azure Active Directory offers exactly the same. With its help, unidentified access can be kept at bay from edge computing solutions.
  • Azure IoT Edge is now able to work offline. As quoted above edge computing applications should be able to operate regardless of the internet state. Azure IoT Edge has made this possible and allows IoT devices to operate seamlessly even if there is no internet connectivity.
  • Azure IoT Central is a specified edge computing solution enabling end-users to monitor, connect, and manage all the deployed IoT assets in one go. It also makes adding fresh value to the connected IoT devices.

Walmart, the leading retail giant, has already utilized the power for Azure IoT Edge for its e-commerce platform and has managed to augment its annual turnover by 79%. It happens when Walmart adopted Azure Cosmos DB.

The solution was used for handling online transactions during holiday seasons as this time there was a need for a cloud-native database with the least possible latency and ability to process billions of transection with 99.999% availability.

Azure Cosmos DB used multi-region writes to make availability expanded as much as possible. The latency was also negligible, sub-10-ms, which made the customer experience better than ever.

Seamless Business Transformation with Detailed Azure Data Features

Data, saved anywhere, need to be handled carefully. Azure offers end-to-end data competencies to expand the business transformation:

  • Azure Synapse Link comes with superb abilities for Dataverse that allow immediate insights to high-end Microsoft Dynamics 365 data and SQL Server 2022. To expand the capabilities of Azure Synapse, Azure Synapse Data Explorer is also included in it. With its assistance, end-users can gain easy access to the machine and user data and utility it for business process improvement.
  • The need of providing robust data governance is at its all-time high as cyber risks are increasing. Azure Preview is a genius way to develop a centralized data governance system for a multi-cloud and hybrid deployment. Owing to its general accessibility, more the 57 billion data assets have been already recognized with its help.

Also Read: Azure SignalR Service for ASP.NET 

Enhance Collaboration for Advance Cloud Management

While multiple cloud deployments are used, it’s imperative to have a continual yet seamless collaboration and communication network amongst the teams. The users of Azure subscriptions are allowed to distribute Power Apps as per the need of the team without asking for an extra pre-paid license. Both Power and Microsoft Team platforms can work in conjecture with Azure services and can enhance team collaboration.

Ending Notes

Cloud computing is the future is here to stay for longer. As more and more organizations are adopting this computing technology, Azure is altering its course of action to address the intensified needs with absolute accuracy. The launch of Azure Arc is proof of it. It offers unified solutions for planning, managing, and deploying multi-cloud, hybrid, and edge computing solutions. Azure IoT Edge is a viable way to leverage the utility of IoT devices and make them connected always.

Data stored over cloud or related to cloud deployments can be handled and monitored with the utmost perfection as Azure has solutions like Azure Synapse Link and Azure Preview. In short, if you’re in dearth need of a seamless solution to plan, deploy, and manage all your cloud-based assets then nothing can beat Azure. Investing money and efforts in this tool will reap lucrative perks. For seamless implementation, take Stridely’s Azure Cloud Services.

 

 

 

 

 

 

Multi-model Product Recommendation Search Engine Mixing – Visual & Textual Queries for Fashion or Interior Designing Products

Posted on by stridely

Fashion and interior designing are two industries where the visual appeal of the products used or put on the matter a lot. It won’t be erroneous to call fashion and interior designing all about a game of appearance and looks. To meet the client’s expectations and utility of a design, fashion and interior designers have to put tons of effort and deal with a fair share of struggles. At times, the vague or incomplete inputs increase the burden of interior and fashion designers.

The advent of AI and computer vision has made the job of fashion and interior designers a lot easier as these two technologies allow professionals to suggest customized yet appealing product recommendations.

Also Read: Style-aware Product Recommender Engine and How Can it Help Interior Designers?

Additionally, the use of multi-model search engines is on the rise. This inventive technology enables interior and fashion designers to bring visual and text-based customers queries at a centralized place and make an accurate and most-fitting product recommendation.

If that sounds unfamiliar to you and as a fashion or interior designer yon want to know more about this advanced technology then this blog is the best bet as it features key inputs about it.

The Existing Problem

The fashion and interior designing industry are already bequeathed with various tools that assist professionals to figure out visually appealing and suggest a similar product. However, they lack to match the style and context of the product with the proposed design plan. They only suggest products based on the object’s appearance.

The use of the latest textual representation tool, word2vec, is helpful only when contextual details are represented as the training corpus. It’s beneficial only to spot the products having the same or corresponding styles such as chair-table, pant-shirt, and shoe-socks.

This made textual search limited and restrictive, especially in the case of interior designing as it fails to describe the various styles in detail. It won’t be able to produce accurate product recommendations if one mentions Scandinavian style or rustic style.

Multi-model Search Engine – Making Product Recommendations Effortless

All the above pre-existing product-recommendation-related issues were resolved up to great extent by bringing the best of visual and textual search methods together. The end –result was an advanced multi-model search engine, Style Search Engine, which features an extensive list of products that are visually the same and have detailed textual inputs from the users.

Business Solution: Smart Product Recommendation System

This multi-model search engine’s operations are possible via YOLO 9000, a high-end art object algorithm, and a deep neural network. These two technologies are used by the visual search block of this engine. The updated textual block of this Style Search Engine endows end-users to make the search criteria more specific in terms of text explanation while augmenting the contextual significance of retrieved results.

Additionally, to promote the products suggestions utility, the search engine merges the visual and textual search results by utilizing the comparative score in the feature spaces.

With all these means, the engine manages to enhance the stylistic and aesthetic resemblance of the retrieved products. When analyzed thoroughly, it was figured out the use of this tool has managed to enhance the product recommendation performance by 11%.

How Multi-model Search Engine Works?

In this section, we will contribute comprehensive excerpts of the modus operandi of multi-model search engines. For input, the engine accepts queries in the form of images and text.

The image query here represents the image of an interior. For instance, the living room image or a bedroom image. As a text query, specific terms are mentioned. For instance, cozy, modern, aesthetic, or fluffy.

Once the inputs are received, an object-detection algorithm is brought into action to detect the objects featured in the uploaded image. The algorithm identifies the class of the object and defines it in detail like its chair, table, or sofa.

Upon identifying the exact object class, the interest region details are fetched in the form of picture patches and then this detail is forwarded to the visual search method. The same course of action is adopted to process the textual query.

The algorithm deduces the visual and textual matches and the blending algorithm of search engine categories them based upon the level of similarity shared with the described features and spaces.

 

Image Source

This image displays the general modus operandi of multi-model search engines.

The visual search engine feature of this engine doesn’t use the whole image of the interior space or fashion apparel. The object detection algorithm of this tool acts like a pre-processing step. With this approach, the engine retrieves results with more accuracy and precision as not the entire space or class is analyzed.

This approach is more advanced than the customary visual search engines that feature object categories having human labeling. The object detection method, YOLO 9000, is administered by DarkNet-19 mode, features 19 convolutional layers. Also, there are 5 max-pooling levels. With such advanced technology, the object detection method of the multi-model engine is able to identify the class of different furniture classes with bounding boxes.

The bounding boxes are further used to create Regions of Interest (ROIs), presented in the pictures. Visual search is executed on these extracted ROIs. For providing more optimized search results, the multi-model search engine uses the outputs from an entirely connected layer of neural networks and normalizes the outputs of extracted vectors.

When it comes to the textual search query, the multi-model search engine takes the help of text query search to make the search result more specific.

The textual search query feature of this search engine is so advanced that it figures out the accurate details even when interior items representing the abstract ideas can also be processed.

For instance, minimalism or Scandinavian style has no specific characteristics to define properly. Yet, the advanced textual search query mechanism of the multi-model search engine will bring accurate results.

The accurate space-embedding feature of the textual query is achieved using the state-of-the-art Continuous Bag-of-Words (CBOW) model from the word2vec model family. The multiple description details related to common household parts and fashion designs like rooms, kitchen, clothing style, and length are referred to clearly.

What makes the space-embedding technology of this multi-model search engine is its ability to operate without asking for any linguistic knowledge. Only the objects and information that appeared in the room at the time of query processing are captured.

Image Source

The above image represents the general object image processing and description the inventive multi-model search engine uses for data explanation.

Conditions to Fulfill For Sure While Using A Multi-model Search Engine

While using a multi-model search engine is a great way to improve the accuracy of product recommendations for fashion and interior designers, one must fulfill certain criteria to ensure its proper functioning. These conditions are:

  • The inputs provided should include images of individual objects and room scene images matched with the presented objects.
  • The details regarding the objects represented within a given design scenario should be clear and precise.
  • The textual description for every room image should be offered.

The absence of all the above criteria will lead to the improper functioning of search engines. Hence, make sure they all are fulfilled without fail.

Utility of Multi-model Search Engine for Fashion and Interior Designer

The above text has made it clear that the cutting-edge multi-model search engine is a sure shot way to get accurate and precise recommendation search results Fashion and interior designers can deploy this tool for performance improvement, better ROI, and optimized resource utilization.

Here are certain benefits that using a multi-model search engine sews instantly:

  • Fashion and interior designers are able to make accurate results even with few inputs. Not many details are required for the results retrieving process.
  • As everything is automated, tons of effort and a huge amount of processing time are saved. While product recommendations are happening, designers can concentrate on other crucial operations.
  • The high-end multi-model search engines are enabled with an innovative web-based application allowing end-users to use a pre-load image or upload an image of their choice. This makes product recommendations more accurate.
  • When a client is having a vague idea of end results, it’s a tough task for designers to bring the best match. The use of a multi-model search engine makes immediate and accurate product recommendations even with slight inputs.
  • The processing of virtual and textual queries makes results precise that allowing designers to provide customization at their best and offer solutions deliver just as projected by the customers.

Ending Notes

It takes a lot of hard work to bring the idea of customer related to a dream space or dress into life and interior designers and fashions designers need a helping hand that can ease down the entire process. The use of a multi-model search engine is a great way to eliminate the tediousness involved and make near-perfection recommendations.

The advanced technology is here to stay as it has recorded the instant 11% improvement in performance and project delivery. The integration of web-based applications makes image processing easy. Fashion and interior designers seeking a way to improve their product recommendation must give this tool a try to experience unmatched performance enhancement.

 

Machine learning for Precision Agriculture: How Smart Farming can Leverage from ML?

Posted on by stridely

In the coming years the Agriculture sector around the globe will see a huge transformation as ML, AI, and automation will unlock will bring game-changing opportunities on board. This article highlights how famers and technologists can harness the power of advance technology for propelling the industry forward.

Business Solution: Smart Product Recommendation System

The Background

By 2050, humans will be the most dominant species on earth with 10 billion in count – U.N report. The size of the planet will remain unchanged though which means the increase in population will put a huge pressure on the resources and landmass for food requirements. And to the top of that there are issues of deforestation, global warming, depleting water resources, and soil erosion making the problem even more serious.

Also Read: Effects of Monitor Vision Based Weed Detection on Farming

Fortunately, today the technological advancements are making things easier for individuals. Intelligent robots and smart machines are bringing transformation in the agricultural field. Powered by Deep Learning, Artificial Intelligence algorithms, Data Analytics, and Machine Learning systems these tools provide an ideal solution for various agricultural solutions. They are contributing towards human lives betterment.

How Machine learning is paving way to precision agriculture? 

With the increasing strain on food supplies globally, the need for optimum crop production has grown than ever. Modern technologyequipped with ML capabilities is making it possible to meet the challenges of the industry.

  • Automatic detection of ripened crops and drought patterns

AI and ML are transforming the farms into smart farmlands which are termed as Precision agriculture. The unique combination of technologies like Big Data, AI, IoT, Machine Learning, and Cloud and their applications allow individuals to automatically detect the drought patterns and trace the ripening patterns of crops. Besides, the emergence of smart tractors makes it easier for them to weed out the sick and diseased plants.
The technology is extensively used for safety, research analysis, terrain scanning, monitoring soil hydration, spatial analysis, and identifying yield issues in agriculture. The smart drones that are equipped with ML and AI capabilities pinout the diseased plants and help in precise spraying of the pesticides on farmlands.
Also Read: Natural Language Processing for Manufacturing Industry 

They also help in adding macro and micro nutrients and checking physical properties like chemical properties, moisture, pH balance of soil, and more. The combination of precision Agriculture and AI-powered application allows individuals to identify the match case and determine about the disease which has stopped growth of the plant and match it with the diseases listed in the imagery database.
On learning about the disease in real-time, farmers can build the corrective measures at the early stages and it could eliminate the possibilities of loss. There are endless possibilities with data analytics, AI, and ML in Precision Agriculture. The data is then collected, measured, and analyzed and sent to the farmers.

Real-time solutions for agricultural issues through Chatbots 

Chatbots are AI powered virtual assistants that conduct automated interactions with the users. They are created using machine learning techniques enabling users to understand the language of the users and build personalized interaction with them.
The chatbots are equipped majorly for media, agriculture, retail, and travel. The facility not only assists the farmers but also allows them to receive answers and solutions to their queries in the real-time.
Download Guide: BOT Framework
Today, we are heading towards AI-enabled precision agriculture where the farming processes are handled by technology. The farmers have long been fighting a battle with different sorts of internal and external factors like pest problems, unpredictable weather, water shortage, etc.
The trend can now be reversed by leveraging Big Data and AI Analytics. It helps in optimizing the entire farmland while ensuring that every section of it is used efficiently.
The smart technology also scans every plant for the growth and health tracking. Any pest issues are identified at an early stage and the same is notified to the individuals. It wasn’t possible with old agriculture methods.

ML powered technologies optimize the entire farming process 

The combination of Big Data Analytics, AI and ML, and smart edge devices such as drones, GPS, and sensors are used widely in smart greenhouses, fish farming, and livestock monitoring.
The adoption of advance Blockchain technology makes the change even more revolutionary in the field of agriculture. It ensures transparency, quick processing time, and upholds superior accountability. Plus, the advancement also contributes to supply chain optimization while adding value to the farming process.

Maximized yield of crops

Seed quality and variety of selections are important for optimal performance level of the plants. The ML enabled technologies helps the crops to grow quickly and in best health. Moreover, the quantity of the produce is also depends on hybrid seed selection. The seed should meet the needs of the farmers.

AI and ML enable farmers to understand how different types of seeds react in different weather conditions and soil types. This information allows farmers to take the right decision at the right time to eliminate the possibilities of crop damage due to diseases or any other reasons.
So, AI is not just changing how digital businesses workbut farming too.

The technology also enables farmers to meet the ever-changing market trends, consumer needs, and annual outcomes. It helps farmers in maximizing the return on their harvest. Resultantly, farmers can increase their farm output by 6 to 7 times per acre and make the most of their farmland.

The Future of Agriculture will be Technology-Empowered

The AI technology has turned out to be highly advanced that now tractor machinery has also become efficient enough of weeding out the spoiled or infected plants. Moreover, satellite imagery gives pictures of different drought patterns.

There are even AI and ML-powered apps which can be used by the farmers as the diagnostic tool. These apps are created to provide complete information about plants to the farmers. Additionally, it also helps in finding the corrective measures to combat the issue.
But continuous efforts are required by agriculture experts, tech companies, and thought leaders to innovate, harness, and improve the potential of the advancing technology. Besides, it is the duty of the governments to spread the role and importance of Precision Agriculture.
The farmers should be encouraged and educated to embrace new technologies like Machine learning and Artificial Intelligence as they have tremendous potential to increase the farm yield and productivity of the farmers.

Endnote

Agriculture sector has been facing a lot of difficulties such as change in temperature, absence of proper irrigation facilities, food scarcity, groundwater density, substantially, wastage, etc. Cognitive solutions such as Machine Learning can change the fate of farming. However, there is a lot to be done on research and development of agriculture on a large scale but still you can find various applications and advance tech tools in the market that can enhance the overall system.
ML enabled precision farming also enables farmers to handle the realistic issues faced by them due to autonomous solutions and decision making. ML has a huge scope in agriculture. Hence, the applications should be reliable and robust. A highly efficient ML tools can handle the changes that take place in external conditions. It also facilitates them with real-time decision making and helps in ensuring appropriate platform or framework for contextual data collection.
The high cost of cognitive solutions is another thing of concern in farming. Hence, the technology is being used to find the right solutions and ensuring that the technological tools reach the masses easily.
Want Artificial Intelligence and Machine Learning Powered smart solutions for farming or other purposes? Talk to experts at Stridely Solutionsand get started towards a better future.

 

 

The Write Interface enabled ADSO Ability for SAP BW/4HANA

Posted on by stridely

Users of the SAP BW/4HANA system are endowed with a powerful capability, ADSO or Advanced DataStore Object, to leverage the data modeling. The post throws light on its key abilities and ways to bring them into action.

A Quick Overview of SAP BW/4HANA ADSO

SAP BW/4HANA is one of the most famed centralized platforms used to make most of reporting, planning, and analysis solutions of SAP. ADSO stands for Advanced Data Store Object and is a data modeling approach. SAP BW/4HANA features ADSO having updated table structure and function.

Also Read: Your Modern Data warehouse for Elevated Needs

ADSOs are equipped to alter their crucial functions without missing stored data. Additionally, it allows one table content modifications in case data types are modified or altered. Regardless of the process, ADSO feature three tables for sure.

The image displays the ADSO tables featuring ‘SAP Blog’ as the technical name.

The Updated ADSO of SAP BW/4HANA

In Q1 of 2019, SAP released BW/4HANA v2.0. The version features many updates, including the write interface for the DataStore Object. This updated interface permits end-user to easily add the data to ADOS inbound table. While this integration happens, there is no need to use any of the customary BW/4HANA objects such as Source System, Data Transfer Processes, or Transfer.

This freedom empowers clients to directly integrate data into SAP BW/4HANA from pivotal SAP tools like: Data Services and Data Intelligence. Not just these, sending/syncing data to Cloud Platform or NetWeaver Process Integration Suite is also possible with it.

The updated interface is offered for the below-mentioned resources.

  • SAP Data Services on-premise. In this case, it requires the support of 4.2 SP11 Patch 4.
  • SAP Cloud Platform Integration (CPI)
  • SAP NetWeaver Process Integration (PI)
  • SAP Data Hub
  • SAP CPI-Data Services

Write-interface enabled ADSOs are compatible with all the leading ADSO. However, planning and inventory-enabled ADSO are not compatible with this latest interface. While this interface is active, clients are allowed to use RFC or HTTP data for data pushing to the ADSO inbound tables. RFC is used for on-premise SAP solutions while HTTP is useful for cloud-based SAP solutions.

The data-pushing task occurs via two methods:

  • Sending data without waiting for a request: In this method, a new request is open for every internal call made.
  • Sending data only when a request is received: This method involves pushing data in a sequence. The key data pushing sequence used are transfer data, open request, and close request.

The best thing about this updated interface is that it’s not designed solely for SAP solutions. Various third-party tools can be befitted big time with this latest interface. Let’s explain the modus operandi of write interface enabled ADSO with an example with the help of SEEBURGER Business Integration Suite (BIS).

This BIS is a very commonly used strategic platform to meet the integration requirements of the IT ecosystem. Here are the steps to follow to bring write interface enabled ADSO.

Step 1: Generate a new ADSO in the Modeling Tools in BW/4HANA as a Standard (or Staging) DataStore Object.’

Step 2: Upon successful activation of ADSO, the next step is to generate the template URIs using the functionality in Properties.

Step 3: Data transportation requires a CSRF token at this step. In its absence, you will see error 403.  It is the HTTP Forbidden error. The display text for this error might be ‘CSRF token validation failed’ or something similar.

Step 4: For sending the data back to the in-bound table, use the Send-Data-URL command alongside the JSON-formatted data to be sent in your HTTP POST request and CSRF token is required. Also, one must perform basic authentication as well. For data transferred from different IP, it is crucial to have cookies in your HTTP Header – the ones from the Open-Request response mentioned.

Step 5: Once the data transfer is done correctly, clients will be able to see a fresh TSN request in the Cockpit app of SAP BW/4HANA. For this, you must navigate to Manage DataStore.

Correct following of these steps ensure upright usage of TSN request in SAP BW/4HANA and you need not handle the request TSN from outside.

Few Technical Details to Keep In Mind

While using write-interface enabled ADSO, paying attention to certain technical aspects is crucial.

For JSPN schema retrieval, you must use HTTP GET request wherein you sent plain data on Get-Structure-URL to fetch desired records. In this request, you may send record count and seed details too.

See an example request below:

GET …/zadso/sampleData?records=4&seed=5

For inaccurate sent data, the client must use CLOSE-Request-URL while confirming error=true and label it as an error. When this happens, this inconsistent data is removed (dropped) from the ADSO activation queues and the request will be closed.

It’s possible to activate the data in the aimed ADSO automatically with the help of Process Chain in ‘Streaming’ mode. This mode is activated when an inbound queue Request is closed.

The Final Say 

With the addition of write interface-enabled ADSO, SAP BW/H4HNA has empowered a lot as clients are endowed with the facility to choose from the data sources offered. The source system types like Web Service, External System, and Data Services can avail this facility. The additional interface, the integration service delivery in any kind of customer ecosystem is swift and effortless. It has made objective achievement possible under every condition.