An Overview of IoT Blockchain and AI in Digital Transformation

Internet of Things [IoT], Blockchain, and, Artificial Intelligence [AI] are the strong drivers of an organization that are stepping into the digital transformation era.

Here is a quick rundown of these innovative technologies’ influence in businesses to bring the required competitive advantage to stay in the global market space.

Today, organizations have realized the influence of digital transformation to stay in the business. Advancement of digital space is needed in every sector not as a competitive advantage, but as a basic necessity. In fact, they are pushed to re-engineer their existing processes by using the key technologies like Big data, Analytics, Artificial Intelligence [AI], Internet of Things [IoT], Blockchain, and, etc.

Let’s understand the three driving technologies like Blockchain, Internet of Things, and, Artificial Intelligence over here.

Blockchain Technology:

The Blockchain is one of the breakthrough technologies that has already infiltrated in the transactional environment and actively wiping off the middlemen’s role. It facilitates the transaction between the businesses or the people over the Internet.

The transactions may include digital assets, codes, cryptocurrencies [Bitcoin], and, etc.

Though it was initially associated with Bitcoin and adopted by the financial institution, today we find the technology in tradings, travel insurance, logistics, energy management, data analytics, and, etc.

To be simple in describing the technology, it is akin to a ledger. It is a chain of datasets grouped into containers called the blocks. These linked blocks are secured with cryptography technologies so that the authenticated users can alone edit [only the part owned by them] and are updated as the transactions occur.

“We really see this as transformative in the same way that the Internet changed communication,” says Marie Wieck, general manager for blockchain at IBM, which has more than 1,500 staff members working on the technology.

A recent World Economic Forum report predicts that by 2025, 10 percent of GDP will be stored on blockchains or blockchain-related technology.

In India, it is anticipated that the blockchain adoption streamlines the transaction process and transform India’s economy to all good. It is high time that we embrace the technology to derive the benefits.

Artificial Intelligence [AI]:

Artificial Intelligence systems mimic the human brain to a greater extent. It utilizes the patterns to logically perceive and analyze the situation rationally.

This cognitive technology is capable of processing the data in large volumes derived from sensors, social media, applications online, and, etc. It extracts the pieces of information, assembles them, incorporates machine learning in order to make a rational and valuable decision.

In simple words, the implementation of the technology could be compared to as having a personal assistant.

Gartner says that AI technologies will be “virtually everywhere” over the next 10 years, but it will be open to the masses rather than being purely commercial.

Artificial Intelligence is getting implemented in mobile space, food industry, beverage industry, logistics, and more. It readily uses the built-in intelligent systems as in ERP solutions, predictive analysis to manage the supply chain, and, etc.

It is anticipated that the Artificial Intelligence will be used in cyber attacks, cyber security, marketing, sales, banking, healthcare, eradicate biases in the corporates sector, enhance the user experience by creating a fluid experience for the end users, and so forth.

The expectations are more and seem to be realistic amidst the challenges and assumptions that it replaces the human capital. Indeed, it will not replace the human, though the certain industry may reduce the manual work. It is there to augment the human job processes in a better manner.

In India, the 2018 budget clearly indicates the Government’s investment and promotion for research in AI and Robotics as a part of smarter ‘Digital India’ empowerment.

The AI Task force focuses on AI-led developments in the verticals like Agriculture, Education, Manufacturing, Environment, Healthcare, Financial Services, National Security and Defense, and, etc.

Uses of AI could be realized only if the employees are aware of its ecosystem apart from its functions. Fostering the culture of innovation would help the organizations to identify the solutions and utilize them for better improvement.

Internet of Things [IoT]:

The Internet of Things [IoT] connects the devices like the smartphones, wearable devices, home appliances [washing machine, refrigerator], surveillance cameras, sensors, and, etc. These are able to communicate and transfer the data without human intervention over the network.

This technology indeed is disruptive helping the human beings to manage the appliances and derive insights for business interests from the system derived data regarding products, solutions, and, other business opportunities.

In simple words, IoT is nothing but the ‘things’ that are connected to the Internet.

CXOs today have realized the business value of IoT implementation, and are aggressively planning to deploy them successfully in the next 24 months.

In India, about three-fifths of the enterprises have already deployed IoT.

If we consider the evolution of the market, IoT is getting pushed and influenced by its security, edge computing, and, blockchain.

There is an urgent need for network security and security analytics in IoT as multiple devices are getting connected. Moreover, IT is spending on edge infrastructure owing to converged IoT systems reducing the time to data evaluation. And, blockchain could be leveraged to IoT for cost cuttings, secure transactions, and diminished settlement time.

The Final Note:

It is evident that data is driving the digital world today. And, the data is influenced by not one technology alone, but a myriad of innovative technologies.

It involves the IoT, Big Data, Machine Learning, Artificial Intelligence, or the mobile devices coupled together in order to deliver supportive actions based on logical predictions.

It is important for the forward-thinking companies to determine the investment cost and its returns, have an open mindset for absorbing technologies and understand the challenges when IoT, cognitive technologies, and/or the blockchain are implemented in a real scenario.

Read more info at — https://www.oodlestechnologies.com/blogs

Top Blockchain Based App Development in USA

Decentralization of applications has its perks and beyond any doubts, Blockchain technology has proved it really does. Owing to the increasing popularity of this state-of-the-art digital ledger technology, there has been a drastic inclination towards Blockchain Based App Development. Different companies and organizations are looking for ways to secure their business operations and what can be the better way to do that than implementing Blockchain.

The Blockchain is the key technology behind Bitcoin which powers the entire cryptocurrency landscape. Apart from that, the technology is also being used in a wide range of applications for security enhancements and transparency. Consequently, the Blockchain Based App Development is largely in demand these days.

Oodles Technologies is a leading Blockchain Development Company with ample experience in creating avant-garde Decentralized Blockchain Applications. We have a deft expertise in Blockchain Based App Development and over the years, we have attained excellence in this niche.

Features and Benefits of Blockchain Based App Development

• The distributed database helps for ready availability and functions better
• Develop peer-to-peer payment platforms with distributed database nature
• Develop safe and secure apps for the customers
• Helps to develop the new business process
• Develop a decentralized ecosystem for business

Technical Expertise:

Blockchain development platforms: Expertise in Ethereum, Multichain, HYperledger, IOTA, Quorum, and, etc.

Programming languages: C++, Python, GoLang, Java, Blockchain specific languages

Technologies: Android, iOS, Blockchain

Avail Powerful Applications with Blockchain Contact Us Today

Discover Oodles Blockchain Based App Development Services

• Smart Contracts Development
• Crypto Wallet dApps Development
• Cryptocurrency tracking Apps
• Ethereum App Development
• Bitcoin ATM Software Development
• Cryptocurrency Applications Development
• Blockchain Wallet Applications
• Bitcoin Exchange Platform Development

Why Choose Oodles Technologies for your Blockchain Based Apps

• Create avant-garde Decentralized Blockchain Applications
• Custom-tailored Blockchain Services
• Meet the client expectations and beyond
• Transparent services at best market prices without hidden costs
• Assistance throughout the process and post-launch support

Why Machine Learning Seems To Be All Around These Days

In our day to day life, we all must have experienced machine learning. When you type something and spell a word incorrectly on google search it still shows you the right results that’s where a machine learning application is implemented. Social media services like “people you may know”, “face recognition” are also a part of machine learning applications. We can say that it is everywhere nowadays. Probability is that you are using it in different ways without even releasing. Machine Learning is a buzzword in the world of technology and even if you are not familiar with all the technologies you would have heard about this term.

Let’s try to understand what is Machine Learning precisely ? And how it is revolutionizing the field of artificial intelligence.

Machine learning is a section of Artificial intelligence which is targeted on the concept where machines can learn and make decisions for themselves. Learning is an important part of human life. To implement AI into the systems that can show intelligence like humans then machines should be able to learn and adjust based on their last experience. It basically explains what machines can do with learning.

We come across many applications that are driven by Machine Learning in our daily life. Some examples of these are Facial, voice or object recognition, Anti-spam mails, forecasts of weather, predictions about traffic and search engine for improving search suggestions. We all know about spam mails. The email system uses spam filter to differentiate between emails that are worthwhile from spam emails of no use.

You may also like: An Online Platform For Deploying Machine Learning Models

Machine Learning has become a significant part of artificial intelligence. Machine Learning and artificial intelligence are not same yet they are often combined into one term. ML is a branch of AI and without machine learning, artificial intelligence signifies nothing. AI is the term that enables machine to do task intelligently. On the other side, Machine learning indicates the automated process that machines make use of to recognize meaningful patterns in data.ML is the most dominant thing in today’s world and also in the future of technologies. The progress in ML is reshaping the future of industries. It is powering the AI development currently. Self driving cars are the most talked about topic today.

By machine learning, technologists have copied the way human mind works. It has developed complex frameworks called neural systems. Thus, neural systems make deep learning possible, a result that has delivered computers superseding human intelligence.Machine Learning algorithms deal with a large amount of information that give way to technology to make predictions. The best example of this is Amazon’s suggested product feature. It looks through your preferences and the buying habits of other people, and then suggests you other products that might appeal to you.

By using ML algorithms, we can build models that discover connections. Also, organizations can make better decisions deprived of human intervention. There are lots of ways where ML has been rendering its potential for empowering Artificial intelligence.

Read more info at — https://www.oodlestechnologies.com/blogs

5 Reasons to Move Your ERP To Cloud

“I don’t need a hard disk in my computer if I can get to the server faster, carrying around these non connected computers is byzantine by comparison.” — Steve Jobs

Many companies are still worried about whether they should move their ERP to the cloud or not. Well, having a virtual office can prove to be really beneficial for every type of organization, hence moving your ERP to cloud is always a great idea.

Businesses require flexibility, scalability, and most importantly security and all of these are provided by the cloud at an affordable price. IT departments are always on the lookout for time and money saving software, therefore it can be a smart move if companies switch to cloud.

According to a survey conducted by the market research department :

32% of the companies want to reduce the maintenance cost.
28% of the companies want more flexibility in accessing the information.
25% of the companies want to streamline their work process.
22% of the companies want more affordable alternatives.

But if you are still not convinced and confused about whether moving from ERP to cloud is an immediate need or not, then have a look at few of the compelling reasons:

Enhanced Security
Every organization, especially small and medium, requires additional security and the cloud systems are perfect for providing the safe and secure environment. The cloud system offers secure gateways for data management so the data does not get leaked to a wrong person.

These cloud-based ERPs are the pre-built templates that fulfill the international as well as domestic standards. The improved security and reduced cost might force you to shift from ERP to cloud-based ERPs now.

Reduced Cost
Traditional ERP system required a huge investment as routers, switches, computers along with few unexpected costs were very expensive. Well, all these costs can be completely eliminated with the cloud-based ERP system. The cloud system follows the rule of, “pay as you go” which means it can put an end to all the initial capital costs.

Not only the hardware costs, cloud ERP can eradicate the server maintenance cost which decreases the workload of the IT department. This means the cloud-based ERP can save a lot of working hours of your company.

Remote access
The Cloud-based ERP platforms can be accessed from any remote location with an ease which means it can be accessed securely from any browser. This is great if an employee is out of office and still needs to access some data, cloud ERP just makes it easy. It makes the employees work easy and comfortable whereas the traditional ERP is time-consuming and less productive. Also, cloud-based ERP can eliminate the corruption and security breaches.

Also Read: Deep Insights Into Cloud-Based ERP Applications

Faster Innovation:
The cloud-based ERP systems are much more flexible than the traditional ERP. Not only that, but cloud ERP encourages the innovation as well. It further helps in making a faster clone of the development and production process. This makes it easy for doing research and innovations without disturbing the company’s operation.

Data Recovery: 
In tradition ERP system, there is always a risk of losing data completely. The Cloud ERP removes this problem as ERP clouds have redundancy which means the data is placed in two places so if it is lost from one position then we have data at another place. The data in the cloud ERP can be survived in any situation.

CONCLUSION:
Cloud-based ERP system helps companies to gain access to robust collaboration tools which helps them to identify any problem instantly and accurately. The Cloud-based ERP solutions can help your business to evolve completely and at an affordable price. In a nutshell, a cloud-based ERP can generate better returns, reduce cost, increase flexibility and security. These are the few reasons which endorse the benefits of moving your traditional ERP to the cloud-based ERP system.

Read more info at — https://www.oodlestechnologies.com/blogs

Reshape Your Services With The Cloud Development Technology

Reshape Your Services With The Cloud Development Technology

The lightning transformation of cloud development technology is allowing enterprises to deploy services more securely, measure them, and modify them at a much faster pace. At the same time, if they are not coping up with the evolution, it can swiftly lead to ending up with a dainty cloud implementation. However, as the stupendous advantages of cloud development become highly recognized, most organizations are striving to amalgamate the way they develop for the enterprise and the cloud. Also, it is a little difficult for the organizations to keep up with the development of new cloud development tools and practices as they are being updated almost as frequently as possible. Keeping that in mind, here are few revolutionizing cloud technology developments that the enterprises can never afford to ignore.

Microservices’ Shift To Kubernetes

Microservices are becoming highly penetrative; everyone is either deploying in accordance with that or at least planning to do so. And as more organizations undertake a pure Kubernetes approach to cloud development, it is, therefore, becoming the major “Operating System” of the microservices.

Also Read How To Improve Cloud ERP With AI And Machine Learning

Kubernetes not only initiates containers and allows basic connectivity for enabling microservices to function together but it is also non-opinionated and permits businesses to implement various tools to sweep out the chunks that it can’t really handle. In addition to this, local storage is not the desirable stateful storage area, instead, enterprises should include microservices with high-performance network storage.

Service Mesh Integration

The most recent advancement of cloud microservices development inculcates using tools known as service meshes. Basically, it is a proxy between microservices that assists with networking glitches and also provides several features that reflect what is happening in your services or applications.

Putting service mesh to use is almost similar to messaging platform integration tool since some features could permit simple integration of latest service-level enhancements, thereby, stimulating organizations to build services that are more reliable and fault tolerant.

DevOps’ evolution to GitOps

Since microservices are capable of populating tens of hundreds of containers, “infrastructure as code” or “GitOps” is becoming more visible as the standard approach for recognizing where microservices are standing, hence, ensuring enterprises to function more effectively.

Although GitOps is an evolution of DevOps, however, it does not really change the basic idea of DevOps and thus can be continued to be used as earlier.

Serverless Functions

The most essential aspect of serverless computing is that organizations are only invoiced for the duration these functions are executed and since there is no such vital requirement of particular nodes, serverless computing can lead to cutting down the cost by over 95%.

Also, the serverless functions including the targeted applications can give out marvelous results and should never be overlooked when you are trying to save some costs.

Also Read Cloud Computing And Its Testing Tools

Therefore, I believe that imposing greater automated testing is essential to ensure that the organizations will be well positioned in the near future with the help of cloud development technologies. What are your thoughts about it? Let us know by writing down in the comment section below or contact us if you are looking for leveraging cloud technology development in your business.

Read more info at — https://www.oodlestechnologies.com/blogs/Reshape-Your-Services-With-The-Cloud-Development-Technology

Advantages of Machine Learning in DevOps

DevOps and Machine Learning are the technologies that are creating a combined impact on the software industry today.

As the DevOps engineers are expected to understand the working nature of the codes, infrastructure, cloud, and, other things, incorporation of machine learning into their work culture seems to be more promising.

Technologies today are pushing the boundaries that mankind would have ever dreamt of. Though there is no real substitute for intelligence and hard work, we witness a positive impact in businesses today with robotics, machine learning, artificial intelligence; evolving software development cultural practices and trends like DevOps, blockchain development, and so forth.

DevOps [truncated term for Development and Operations] is a bold new strategy getting implemented by the IT industries who are in search of the outcome-based model. All of them carry the main objective that is, create, test, release, and support the software at a reliable, scalable, and faster rate, that are closely aligned with the business objectives.

On the other hand, Machine Learning, an algorithm category, facilitates the data-driven automation for applications and predict the outcomes more accurately. It is able to receive the data input, analyze the statistics, predict the output, update the data, and, so forth. It is pushing the businesses to explore and implement data analysis model.

However, the DevOps advantage, when combined with harnessing, monitoring, and, analysis of the data it creates, is forecasted to help the team to optimize the operations in a better manner.

The potential of Machine Learning to make the DevOps smarter is the talk of the techno-town today and is becoming the key area to explore in the future.

In brief, the DevOps methodologies and machine learning are parallelly evolving and is logically considered for a successful outcome in combination.

Here is a brief note about how both these giant technologies could be implemented in combination for deriving better benefits in business.

How Machine Learning Benefits DevOps Methodology?

Till date, most of the teams depend on threshold monitoring approach wherein conventional habit and wisdom are the factors to rely on. This has resulted in a high signal-to-noise ratio and alert fatigue.

But, when you consider machine learning, it is of mathematical, statistical, and logical. That is, it is more grounded as it uses the models namely linear and logistic regression, deep learning, classification, and, etc., to scan the data sets, trends, correlations, and make the logical predictions.

You may also like: An Online Platform For Deploying Machine Learning Models

Optimizing DevOps with Machine Learning:

• Machine Learning Application may analyze all the large data in store and help for predictive analysis.
• The possibilities of looking at data in many forms and combinations are easier like velocity, bugs, metrics, continuous integration system, and, etc.
• It delivers the data as per the needs like daily, weekly, monthly, or so; and trends like seasons, festivals, geography, and, etc., for gaining a complete insight.
• The collection of data and its analysis helps to rule out the root causes, investigate the failure, and other issues easily.
• It determines the efficiency of the orchestration and helps to analyze the tools and processes for more efficient and directed planning.
• It helps to optimize a specific metric like maximizing the uptime, reduce the deployment time, maintain the standard performance, and, etc.

Advantages of Machine Learning in DevOps Methodology:

There are varied illustrations, where machine learning could be effectively implemented to DevOps. A few of them are mentioned below.

1.Machine learning implication on DevOps tools like Jira, Jenkins, Puppet, and, etc., identifies the software wastes like inefficient resources, partial work, task switch, process slow down, and other shortfalls that are faced during application delivery.

2. It helps to review the QA results, detect the errors, ensure proper testing, and thus raise the quality standard of the deliverables.

3. It helps to ensure the security of the applications by detecting the backdoors in coding, deployment of unauthorized code, theft against intellectual property rights, and etc., based on user behaviors and exercising patterns.

4. It analyzes and detects the abnormal pattern in usage, group the alerts based on transaction ID, servers, subnet, and, etc., enabling filtration. This, in turn, manages the alerts by reducing the alert storms and fatigue.

5. The machine learning tools can detect the anomalies in the process, operations, alerts, and suggests best-fixing measures. It automatically detects and also triages the known issues in a more intelligent manner.

6. It analyzes user metrics and its impact on the business at an early stage itself. For instance,

Cart abandonment, click through rates, user registrations, and, etc. This serves as an early warning for the businesses to take effective measures wherever needed.

Challenges of Machine Learning in DevOps:

It is understood that the machine learning tool implementation is still limited owing to several challenges. A few of them are highlighted below.

• We find technical challenges among the DevOps practitioners as there is the need for better understanding about these technologies like machine learning, Artificial intelligence, and/or the predictive analysis. Example: Logarithms, statistics, linear algebra, programming, trigonometry, and, etc.
• Further, implementation of machine learning itself is a challenge at the organizational level. Integration of it with DevOps is not yet understood completely and the management is not unanimous to support the decision.
• The Hiring of a new team, encouraging the existing team to meet the DevOps and Machine learning challenges by upgrading themselves is still in the process.

What Next?

The effectiveness of machine learning is dependent on DevOps processes. By understanding the benefits a machine-learning DevOps infrastructure could provide to the business processes, and its implementation is anticipated to bring success in project management.

If the integrations are correlated and evaluated efficiently, the technology is going to create wonders in business processes positively.

It is expected that the proliferation of the frameworks would make the algorithms easier than the present scenario. As more professionals are expanding their skills in machine learning, we may expect more use cases in the near future.

Machine learning is able to map the best possible patterns for enhanced performance and infrastructure.

Thus, the implementation of machine learning in DevOps is highly recommended today.

Read more info at — https://www.oodlestechnologies.com/blog/tagged/MachineLearning