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A smart application is an software that uses data from user interactions (historical and real-time) for providing actionable insights for better user experience. The insights may be in the form of recommendations, estimates or suggestions to complete a task. A common example of smart applications is retail apps that provide product suggestions to the user based upon previous buying behavior and choices made by the user.

As a business owner, following are the reasons why you should consider to invest in smart applications:

• Operationalize Data: If you are investing your resources for collecting data related to your customers, it will hold no value if this data is not used. Smart applications operationalize the information collected by your data scientists. These applications utilize this information to provide insights to customers and systems for helping them take profitable actions. For example, a smart app utilizes data about the buying history of a user to provide a list of your products that may garner user interest and improve the chances of a sale. This leads to desired outcomes that support your business goals.
• Improve Operational Efficiency: Smart applications are also available for machines, not only human users. Machine-to-machine smart applications can be paired with event-driven architecture for automating the operational processes based on real-time insights. This helps in improving the operational efficiency of an organization.
• New Business Models: Smart applications can be used to analyze data for providing predictive insights for developing more productive business models. The model is based on extensive user data, market research, and thorough analysis. The smart app helps the organization in predicting the results of a business model before investing resources for its implementation.
• Dynamic & Evolving: As new data, insights, and user feedback are collected regularly; the data scientists and developers use this newly acquired information for continuously evolving the smart application. Thus, the smart application is able to provide relevant insights based on real-time data. Also, smart apps have a loosely coupled microservices-based architecture. This makes it easier to implement changes and support continuous evolution.

Undoubtedly, it has become important to adapt smart applications for your business. However, here are some points to be considered before making a decision:

• Do you have robust data practices? Smart applications are data-driven. Thus, an organization requires robust data practices for finding actionable information from a large amount of data.
• Do you imply an agile methodology? For running a smart application, it is important for both data scientists and developers to adopt an agile methodology. Thus, make sure that your data scientists must be able to analyze data and update the algorithms regularly. Also, your developers need to continuously update the smart app.

For more information about next generation smart applications, call Centex Technologies at (972) 375 - 9654.

As the IoT network continues to grow, the data has to travel long distances in order to be accessible to every device connected to the IoT network. As the data was formerly stored at a central location, it requires high bandwidth for pushing the data to and fro the nodal devices where it was actually needed. This also resulted in high latency rates. The need to reduce bandwidth requirements and latency rates gave rise to ‘Edge Computing’.

Definition: Edge computing is defined as a part of a distributed computing topology in which the information processing is located close to the edge – where devices or people connected to the network produce and consume the information.

Thus, it is a Microdata center network that processes or stores the vital data locally and pushes all data inward to a central location or cloud storage. Broadly speaking, edge computing is all computing that happens outside the cloud, at the edge of the network, where real-time processing is required. The basic difference between cloud computing and edge computing is that cloud computing feeds on big data while edge computing feeds on real-time data generated by sensors or users.

How Edge Computing Works?

In order to understand how edge computing works, let us consider a corporate scenario. Think about monitoring devices in a manufacturing company. While it is easier for a single device to capture data and send it to cloud storage, the problem arises in the case of multiple monitoring devices as they would produce a large amount of data.

Thus, the edge gateway collects data from the devices and processes it locally to separate the relevant information from junk data. Once the processing is complete, only the relevant information is sent to the cloud storage. Additionally, in case an application needs this information, the edge gateway sends it back in real-time reducing the latency period which would have occurred if the information request was to be processed at cloud location.

Privacy & Security Risks:

As the data is handled by different devices, it gives rise to security and privacy risks.

• Bots: A great degree of edge computing is done via Application Programming Interfaces (APIs). Failing to encrypt the data and authenticate third-party APIs result in a lack of control. This gives rise to a loophole that can be exploited by hackers to steal data or infect the connected devices with malicious code or bots.
• Distributed Denial of Service (DDoS): The hackers may lay silent for an extended period after infecting your system. This gives them time to spread the infection through a larger number of devices while staying unnoticed. Once their code is deep-rooted, they may initiate a DDoS attack which will spread at a greater speed owing to the low latency of edge computing paired with the upcoming 5G network.

It is imperative for organizations to pay attention to data security before implementing an edge computing model in their network. For more information about edge computing and ways to manage privacy issues related to it, call Centex Technologies at (972) 375 - 9654.