How can you prepare your organization for the future of connectivity?

Preparing an organization for the future of connectivity should involve strategic planning, technological adaptability, and a forward-thinking approach.

In my opinion, you must know what is the technologies that drives today and in the future, but you should adapt and adopt what you need and invest. Sometimes you have devices that a 100Mbits is enought to work fine and you can reserve faster connections to use in other devices.

Acho a tecnologia 4G incrível, especialmente para nós profissionais de TI que precisamos lidar com situações corriqueiras e agir rapidamente. Muitas vezes, fui salvo graças aos dados móveis do meu celular. Contudo, ao considerar a evolução para a 5G, estou ansioso para explorar ainda mais benefícios, como melhorias na velocidade e na eficiência, o que certamente aprimorará ainda mais a qualidade da atuação remota.

Not only 5G, as some companies are also working of connectivity through satellite all the time. So, todays fast paced era, it's better to prepare yourself and team or company to embrace any new communication technology launched and doesn't have too many bugs. If in technology, the need for fast communication is more than ever. In digital twin concept, the person can remotely via VR and do the job on site. But if the network speed is low, then it might hinder in progress or the command might not be executed as required. Need to select the best service provider as well, not only considering cheap packages but quality. Then cyber security need to be considered as well, otherwise someone can take wrong advantage of it.

Technical Support: Resolving Tech Issues Technical support assists users in resolving technology-related issues. Common issues include hardware malfunctions, software glitches, internet connectivity problems, and data loss. Troubleshooting involves gathering information, reproducing the issue, identifying solutions, implementing them, and verifying resolution. For unresolved issues, escalation may occur.

With IoT and cloud, no need to keep separate hardware for each site. It also gives the flexibility to deploy end devices in multiple locations world wide but control in one place from cloud. Another booming technology is wireless. Lot of devices and equipment are now going wireless to save the hassle of cabling, so such devices to be accepted. Edge computing also saves lot of hardware for each site. E.g., edge camera will do the processing and send the result to server directly, without need to install GPU.

An example: Picture a manufacturing firm optimizing operations through edge computing, reducing latency and enhancing efficiency. As we navigate the connectivity revolution, embracing edge computing, fortifying cybersecurity, and fostering collaboration with industry leaders become imperative. Let's cultivate a tech-savvy workforce and invest in adaptable infrastructures. Connectivity isn't just a tool; it's the cornerstone of organizational resilience. Let's proactively adapt and thrive in the interconnected era.

Edge computing involves processing data near the source of data generation (at the edge of the network) rather than relying solely on centralized cloud servers. To explain this more let's take a scenario of a smart security camera in an IoT system. Instead of sending all recorded footage to a cloud server for analysis, edge computing allows the camera to process and analyze data locally. Only relevant information or alerts are then sent to the central system, reducing latency and improving overall system efficiency. Together, IoT and edge computing contribute to creating more efficient, responsive, and scalable systems in various domains, such as healthcare, manufacturing, transportation, and smart cities.

AI tools are becoming common everyday, specailly after the introduction of chatGPT. So, these tools can bring information, idea or complete analysis within few seconds. But important is you should know how to use these tools properly if searching for something specific. There is also a need to define guidelines when using such tools, as not all tools are safe to use. These tools or programs can extract information from your system or can be a source of malware. It's better if the organization takes lead on such tools and define the guidelines and limitations for using it Similarly automation has replaced lot of laborious work previously done by manual labor. But as of today OT is not possible without IT. So also care required with set rules

AI has become a thing now where people look to it to answer questions they might have. Within minutes solutions that would ordinarily take a lot of time, are available. Of course, ethical use of the technology should be enforced, it should be leveraged with data privacy and compliance of regulations in mind. Automation is gradually becoming the order of the day, mundane and repetitive tasks are automated where little to no human input is required. These two technologies together could implement complex solution. I mean, AI learning software release strategies and implementing the CI/CD pipelines to automate infrastructure for software release. As always, security should be in implemented as early as possible when using these technologies.

I believe it's important to note that automation and AI are 2 different beasts. Regardless they can work together and when designed well perform well. That said, it is an investment that you need to determine if you should make. Personally, I believe that anything that requires repetition should be automated to save time and increase efficiency. AI on the other hand requires more thought. That said, I do leverage AI where I can as an assistant.

AI tools are really helping simplify some task but before using AI tools you should really need to understand prompting because you can get the best results from AI if the right prompts are inputted,they have also been argument that AI is here to take developers jobs but without the write prompt inputted AI search will just be like an original search without getting the deep answer, organisation staff still needs to be trained how AI tools can make life easy.

AI and automation are the technical mechanisms that will help enable different areas of business. The 'oil/gas' that it runs on is data. The larger and more frequently current the data set the better. This means that AI and automation will thrive in environments rich in freely accessible sources of data. We saw this with the rise of ChatGPT and other LLMs in the conversational AI space. Mainly because human conversation (across social, phone, email, chat, etc.) is fluid and constant and provides a rich data set for AI. Other areas of business where data isn't as prevalent will find it harder to adopt AI. An example of this is in the legal industry where physical paper copies are still widely used and not stored in a online dataset.

I think hybrid solutions fit best for most of the cases. Lets consider a healthcare provider, navigating the balance between patient care and data protection. Their hybrid strategy involves leveraging the cloud for data analytics while safeguarding patient records on premise.

Examples of cloud and hybrid soulutions: Harmony with Regulations: - On-premises hosting takes the spotlight when regulatory or compliance demands call for a localized touch. Upholding these standards is the linchpin for a fortified operational structure. Innovating Amid Challenges: - Addressing the needs of nascent enterprise applications reliant on non-migrated workloads, or inherently resistant to migration, underscores the imperative of a steadfast on-premises strategy. This guarantees seamless integration and peak performance.

The days of physical infrastructure are waning. It's expensive to maintain and secure and is subject to catastrophic failure in the event of something as simple as power outages. Cloud solutions are flexible in pricing, supporting and scaling to fit the needs of your organization. With cloud services, you pay for what you use and the provider is responsible for the availability of your service. Physical infrastructure requires real estate and hands-on support personnel to manage it. But, if you have older systems that can't reside in the cloud, your hardware is still needed. Hybrid solutions give you flexibility for future growth while weaning off of the hardware.

Deploying your server in the cloud and other hardware can help reduce cost of purchase and maintenance,AWS,azure and Google offers such services

Examples of collaboration and communication great ways to prepare your organization. Agile Adaptation: - Collaboration coupled with effective communication creates an agile environment. Teams adapt swiftly to changes, leveraging shared knowledge to navigate complexities and capitalize on emerging opportunities. Breakdown of Silos: - Silos crumble when collaboration and communication thrive. Information flows seamlessly across departments, fostering cross-functional understanding and dismantling barriers that hinder organizational agility.

No matter how sophisticated our tools become, they are only as effective as how they are used to facilitate communication. Collaboration tools exploded during the pandemic. It took some time to learn how to best leverage them. Consider what tool is best for the communication need. Is instant messaging with your team as effective as a video call? Does your customer's meeting tool function with yours? If you have tools in place, devise best-practices for their use. Create job aids to help stakeholders determine how to reach their audience with the right tool, the right way and the right time.

For computing challenges one thing that has been useful is decomposing “connectivity” and interoperability into the 3 layers of (1) network, (2) data products, and (3) (super-) applications. Coming from the end result, the automation of a a use case, apps are required. They have to interact, “communicate” with each other. Then each app requires data - not raw data but refined data. For scalability it has been helpful to standardize refinement to create data products, such as digital twin templates in industry, for example. They also have to be interoperable or “communicate” with each other across verticals. And finally, it takes networks for data just like phone networks for voice to make data with the right information content available.

Cybersecurity and Data Privacy As connectivity becomes more pervasive, the importance of cybersecurity and data privacy cannot be overstated. With the increasing volume of data being transmitted and stored, organizations need robust security measures to protect sensitive information from cyber threats. Implementing encryption, multi-factor authentication, and regular security audits are crucial steps in fortifying your organization against potential breaches. Additionally, ensuring compliance with data privacy regulations is paramount to maintain trust with customers and avoid legal implications.

To prepare for the future of connectivity, focus on adaptable infrastructure and continuous learning. Invest in scalable tech like cloud services and IoT, ensuring flexibility for emerging technologies. Emphasize cybersecurity to protect data integrity as connectivity expands. Cultivate a culture of innovation and agility, encouraging employees to embrace change and upskill in areas like AI and data analytics. Foster partnerships for knowledge sharing and stay attuned to global connectivity trends, positioning your organization to leverage advancements for enhanced efficiency and collaboration.