The trend of work from home has gained momentum in the time of pandemic. A large number of employees are now working remotely due to COVID-19. The businesses that have remote employees require making important changes for the transition. Amongst other changes, the businesses are required to make some technological additions to help their employees in working efficiently from remote location.

Following is the list of important tools and programs the businesses need to assist the remote workers:

• Hardware: Hardware is the most basic requirement when facilitating remote working environment. It is an essential starting point for remote workspace, including a working desktop, laptop or computer. Once a computer system is setup, the next requirement is reliable WiFi and a smartphone. Depending upon the job requirements, some additional hardware may be required such as printer, scanner, a landline phone.

• Document Creation & Editing Tools: The remote employees may be required to create and edit documents, notes and presentations. Thus, businesses need document creation & editing tool packages. These tools are necessary for every approximately every office job. A common example of such tool package is Microsoft Office 365. The package includes Word, Excel, Outlook and PowerPoint. Other features that can be helpful for the remote workers include Microsoft Teams. This feature enables the remote workers to collaborate with their coworkers through messages, live editing, file sharing, chats, etc.

• Project Management Tools: Project management tools help in keeping track of the projects remotely. The tools aide the remote employees and teams to effectively organize work and manage projects & tasks. Different types of project management tools include desktop tools, web-based tools, mobile tools, personal tools, single user tools, collaborative tools and visual tools.

• Cloud Computing: Cloud computing helps in recreating the work environment in a virtual space, offering storage, application management, data analysis, security, support, etc. The solutions are scalable to allow businesses to add resources and services that can be easily accessible to remote employees.

• Video Conferencing & Chat Platforms: In order to manage the projects efficiently, it is important to maintain the communication between remote employees. Video conferencing and chat platforms allow remote employees to send direct messages to individuals and groups. These platforms also allow remote workers to send and share documents.

• Cybersecurity Tools: In a remote work environment, it is highly important to secure the business data being shared across the network. Cybersecurity tools help in ensuring the privacy of the business data and network. These tools also help in preventing the cyber criminals from accessing the private network.

For more information on technology requirements of businesses having remote workers, call Centex Technologies at (972) 375 - 9654.              

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Data intelligence is an important aspect of every organization. It lays the foundation for data analytics and decision making by the company executives. However, data collection and analysis are conducted by computers that store them in languages that are not comprehendible by humans. Thus, in order to facilitate decision making, it is imperative to make data analytics available in natural human languages.

Once the metadata is annotated in human languages, it provides information about events such as when, what, where, how and why they occurred. When the information is available in tangible form, it can be used to gain situational awareness and stimulate thinking by forming patterns or relationships between data. Formatting the data by forming visuals such as tables, charts, and graphs help in understanding the patterns and interdependency of various factors. This understanding defines the course of future actions to achieve desired organizational goals.

In order to understand how to make data analytics human for decision making, let us consider the following aspects:

Type Of Data:

Traditionally, metadata management focused on technical metadata including platform, structure and physical characteristics. However, as the business organizations are now relying extensively on data analytics, equal focus is being laid on collection and correlation of business metadata (business rules, associated applications, and business capabilities) and semantic metadata (business terminology and ontology).

Finding Data Patterns:

A large amount of data is collected on a daily basis. But in order to gain meaningful results, it is required to understand the relationships in the data. An example of data mapping for understanding interrelationships between entities, their properties and relationships is ‘Knowledge Graphs’ pioneered by Google. Although such graphs provide good information, they alone cannot be used for reliable decision making. Thus, more related data has to be collected from parallel platforms and databases to create a ‘Knowledge Platform’.

As the information is classified in classes and concepts across different datasets, it makes it easier to interlink and find related information. Businesses tend to make use of query languages to search for information across the contents of enormous datasets.

Narratives:

After understanding the patterns of data, the next step is to form a data narrative. It includes reasoning and learning in addition to data patterns. To create a narrative, it is important to understand three things:

• Types of questions that may be asked based on data patterns
• Answers to these questions
• Questions that will arise based on previous answers

Data patterns may indicate information such as the effect of a variable on business metrics. But data narrative includes answers to questions such as ‘If metric goes up with time, how will it affect the business?’, ‘Does the metrics accumulate over time or is it point-in-time?’ and ‘What does it mean for our sales?’.

Decision Making:

The data narrative forms the basis of decision making. The decision makers of an organization analyze the narrative, visualize the supporting data, and test the hypothesis to identify gaps. The final decision conveys the required actions for achieving business innovation and goals.

For more information on making data analytics human for decision making, call Centex Technologies at (972) 375 - 9654.

Bluetooth beacons are hardware devices that use low energy signals to transmit periodic information to electronic mobile devices in close proximity. The beacons transmit their id to the mobile devices, which return this identification number to the cloud server. The server responds by sending the information attached to the identification number. It could be a product detail, a webpage, a phone number, etc.

Business marketing professionals are using Bluetooth beacons in numerous ways to increase sales and revenue:

1. Tracking customer’s in-store movements: Bluetooth beacons can be used to track the movements of a customer in the store and send relevant offers. For example, if the beacon detects that a customer is in shoes section, it makes sense to send her a shoe discount coupon. This motivates the customer to make a purchase.

2. Help Customers In In-Store Navigation: It is common for customers to abandon the store if they can’t find what they are looking for. Bluetooth beacon technology can be used to tackle this problem efficiently. The technology can be used in conjunction with the store app to create an in-store mapping experience. Businesses can develop their apps to assist the customers in creating a shopping list as they enter the store. The app can then be used to show them the location of the selected products. The Bluetooth beacons detect the real-time location of the customers as they move and create a map to show them if they are moving in the right direction or not in relevance to the products.

3. Attract Customers To In-Store Events: Retail businesses commonly organize in-store events to attract customers during holiday seasons. The events may range from free makeup tutorials to gift wrapping presentations. Traditionally, the business marketing professionals used emails or telemarketing to inform their customers about the events. However, customers have a higher probability to walk in the store for attending an event, if they are already in the vicinity. Thus, you can use Bluetooth beacon technology to alert mobile device users in the proximity of your store about the ongoing events. This will help in increasing the footprint traffic, giving you a chance to generate leads.

4. Improve In-Store Conversion Rates: Using Bluetooth beacon technology, you can have an idea of the products that are being purchased by a customer via his online shopping list or in-store location. This information can be used to transmit notifications or reminders to purchase related products. For example, if a customer purchases cereal in a supermarket, a notification such as ‘Do you also need milk?’ can make sense to him. Such targeted messaging helps in increasing in-store conversion rate.

For more information about use of Bluetooth beacons in business marketing, call Centex Technologies at (972) 375 - 9654.

Customer service is an important aspect of any business organization. Businesses keep looking for new ideas to improve their customer service and offer better customer experience, which has led to the advancements in AI based customer service solutions. Although, businesses have been using AI in customer support for a while; the collaboration still holds many facets that are yet to be unfolded in the future.

Following are some of the applications of AI that can be explored for enhancing customer service by businesses:

• Brand Messenger: In recent years, there has been an increased user inclination towards messaging apps. The use of messaging has extended from personal communications to user engagement with brands. This has laid out a path for businesses to incorporate chatbots to interact with new and existing customers. As some major industries (like fashion, tourism, food chains, airline, e-commerce and hotels) have adopted this feature to increase user engagement; it would be exciting to know which industries will follow the suit in future.

• Quick Resolution: Wait time for resolving simple queries is an important determinant in customer satisfaction. Customers seek quick answers to general queries and tend to trust a brand that offers faster answers and streamlined action plans for their queries. Thus, businesses can exploit the capacity of AI to multi-task and handle multiple automated queries. This will help in limiting the response time and generating accurate resolutions.

• Customized User Experience: In addition to making self-service user interfaces more intuitive, AI can help in anticipating customer needs based on previous chat history, contexts and user preferences. AI integrated systems can capture a large amount of data for identifying customer issues, defining customer behavior, determining frequent decisions, prompting with proactive alert messages, suggesting personalized offers and discounts, etc. Such intelligent assistance and pre-emptive recommendations will help companies in offering a quality rich customer service.

• AI Controlled Multiple Support Channels: In addition to providing direct assistance to the customers, AI can be used to control multiple channels of customer support. For example, in case a telecommunications agent is unable to answer a query, AI can determine the issue and direct the customer towards dedicated support channel.

Undoubtedly, these applications support the strengthening of collaboration between AI & Customer Support. However, as the AI systems rely on collecting extensive user data for working efficiently, this gives rise to privacy concerns. The data collecting system can be compromised resulting in a data breach. Thus, business organizations need to pay due attention to data security policies before implementing AI supported customer service systems.

For more information about use of AI in customer service, call Centex Technologies at (972) 375 - 9654.

Automation helps in enhancing the productivity of a company by streamlining the processes. Technological advancements have helped companies in automating routine tasks for better management of time and resources. Undoubtedly, automation seems like a lucrative option and a large number of companies are grasping the opportunity. However, it has some security risks that should be taken into consideration before incorporating automation into your operations.

• If your business process makes use of IoT enabled devices for data collection and process execution, a through security audit is recommended. It is also important to make sure there are no vulnerabilities in the internet or LAN connection that may install Trojans or malware in the system.
• When automating your company’s payment process, it may be a risk to provide access to multiple people. If multiple employees are authorized to set up and verify payments, the chances of insider threats may increase.
• Relying excessively on automated tools is another security risk for your business. Periodic manual checks to correlate automated process findings should be conducted.
• Like other software, ignoring regular updates of automation software may open a back door for cyber attackers.

Once you understand the risks associated with automation, here are some ways to help you balance automation with security:

• Set Security As A Priority: As the automation market is growing, the service providers have a zeal to launch the latest solutions at a higher pace than their competitors. This may lead to ignorance of security measures during the beta phase of development. Thus, make it a point to ask the automation provider about the built-in security measures. Also, you may consider a trial period to test if the products match your security standard.
• Think Before Scaling Up: Investing in automation for the sake of keeping up with the trend may lead to the obliviousness of security measures. Thus, before you invest in automation, you should consider the need and purpose. Also, pay attention to your system and infrastructure security before scaling up the automation operations.
• Regular Updates: Outdated software has vulnerabilities that can be exploited by hackers and may lead to cybersecurity breaches. So, it is important to be aware of software updates provided by your automation service provider.
• Automate Cybersecurity: Incorporating automation in your cybersecurity strategies can help in improving your security protocol by offering features such as better threat detection, data correlation, etc.
• Training: Before incorporating automation in your operations, train your employees to train them on ways to use the automation tools while considering security protocols.

We, at Centex Technologies, provide state-of-the-art IT security solutions for businesses. For more information on securely incorporating automation tools into your work processes, call us at (972) 375 - 9654.

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Companies accumulate large amount of data every year. The data may include important information like trade secrets, customer information, client database, product/service information, marketing strategies, etc. It is important for the companies to keep this data secured to prevent financial, trade and reputation loss. However, an increasing rate of data breach incidents indicate that most companies fail to secure their data.

Here are some common mistakes that the enterprises make leading to loss of data:

• Lack of Security Testing: New security features are launched at regular intervals. While it is recommended that businesses should update their security features with newer versions; the switch should be made after proper testing. The companies make the mistake of skipping the beta phase of testing (a testing phase where vulnerabilities of a new security feature are detected and rectified by the technical team of organization). Implementing any new security feature without thorough testing puts the business data at the risk because hackers get the chance to exploit the vulnerabilities and launch a data breach.

• Forgetting To Map Data: Data movement is an essential component for managing the operations of any business. As the use of online resources is increasing, data movement forms the basis of marketing/ sales strategies, collaborative meeting of on-shore & off-shore employees, process handling between different teams, etc. As the data is regularly moving, it becomes important to keep a track of it. Mapping data is the process of marking the origin, journey and destination of data flow. It also involves keeping a track of every person who interacts with the data, and the changes made to it. This helps the data monitoring team to detect data handling patterns and recognize unexpected interactions at an early stage. However, companies usually commit the mistake of neglecting this important process.

• Relying Solely On Anti-Virus: Although it is important to install anti-virus software into the computer systems of the organization to detect the malware; it should not be treated as the backbone of the cybersecurity strategies of the organization. Businesses make the mistake of relying solely on anti-virus software instead of installing other security measures that can detect and flag potentially malicious incoming data before it enters the network.

• Using Outdated Versions Of Security Networks: When considering security networks, companies have to pay attention to three aspects namely security software, security hardware and internal network of company’s systems. Companies often update one or two of these aspects which leaves them at the risk of improper integration of security networks. The outdated versions lead to vulnerabilities in the system which can be exploited by hackers.

It is advisable for the businesses to focus on proper cybersecurity strategies to prevent data breach instances.

For more information about ways to secure data, call Centex Technologies at (972) 375 - 9654.

Artificial Intelligence (AI), Machine Learning and Deep Learning are commonly used interchangeably. However, in technological context; Machine Learning and Deep Learning are subsets of AI. In order to understand the difference between these terms, it is important to know the actual meaning of individual term.

Artificial Intelligence (AI): Artificial Intelligence is a term that defines the simulation of human intelligence processes by computer systems. The processes include learning, reasoning and self-correction. AI is broadly classified as weak (narrow) AI and strong AI. Weak AI systems are designed to do a particular task. The most common example of weak AI is the virtual personal assistants. On the contrary, strong AI systems are equipped with generalized human cognitive abilities. These systems are able to find a solution to any problem independent of human intervention.

Machine Learning (ML): ML is an application or subset of Artificial Intelligence. Under this application of AI, a machine is programmed to access and manipulate data. The machine can analyze the data to identify patterns and learn from these patterns. This allows the machine or computer system to modify decisions as per any change in data without explicit programming. Machine Learning is driven by algorithms and stat models. The common usage of Machine Learning can be found in apps such as email filtering, optimization, internet fraud detection, etc. Machine Learning methods are widely grouped as supervised and unsupervised ML.

• Unsupervised ML: These methods group interpret data based only on input data. Clustering methods are an example of unsupervised ML.
• Supervised ML: Supervised ML methods use both input and output data to develop a predictive model. Classification and Regression methods are listed as supervised ML.

Deep Learning (DL): It is a broader subset of AI. Deep Learning involves collection of large unstructured data and combing through it to generate classified structured information. The basic difference between Machine Learning and Deep Learning is that ML is task oriented learning, whereas DL is more general. It is used to derive meaning or identify patterns in unstructured data. This, in turn, helps in spotting large scale trends or irregularities. Some common applications of Deep Learning include self-driving cars, fraud news detection, natural language processing, visual recognition, etc.

For more information about Artificial Intelligence, Machine Learning and Deep Learning, call Centex Technologies at (972) 375-9654.

As technology is evolving rapidly, it has enabled a faster change and greater progress in the IT industry. The disruptive technological trends like interconnected humans, robots, devices, content and services driven by them have become an integral part of modern IT applications.

Some of the major technology disruptors revolutionizing the IT industry are:

• Robotic Process Automation (RPA): It is an emerging form of automation technology that uses software with artificial intelligence and machine learning capabilities. RPA is used to perform high-volume repetitive tasks that awere earlier done by humans. The RPA robots utilize the user interface to capture data and manipulate applications like humans do.

• Internet of Things (IoT): IoT enables devices, home appliances, cars, etc. to be virtually connected and exchange data over the internet. The connected devices share data that they collect and take instructions from multiple sources which may or may not be in close proximity. Proper use of IoT technology can enable optimized traffic system, efficient waste management, energy use, etc.

• Cloud Computing: The major part of the IT industry relies on cloud computing, making it one of the most trending technologies. The range of cloud solutions & delivery models is widening and it now requires the cloud services to be more adaptable in different areas of activity. Majority of IT service providers are acquiring hybrid cloud solutions to speed up the service delivery.

• Blockchain: Blockchain technology has potential applications in almost every field. We have already witnessed use of blockchain applications in healthcare, IT, real estate, law enforcement, cryptocurrency, banking, etc.

• Artificial Intelligence (AI): AI are computer programs that perform highly intelligent tasks, such as recognition of images, speech, patterns and complex decision making. Machine learning is a new branch of AI that is creating and enabling smart business operations with greater accuracy.

• Data Security: Cybersecurity is increasingly evolving due to technological advancements. As the threats are constantly arising and the hackers are finding better ways to illegally access information, technologies are required to enhance data security by incorporating hardware authentication, cloud technology and deep learning. This makes data security an emerging technology as it will constantly evolve to defend against intruders.

Implementation of modern technology in business operations, marketing, customer care, etc. can increase productivity of an organization. For more information about various trending technologies and how they can be applied within your organization, call Centex Technologies at (972) 375 - 9654.