Security Tips for Remote and Mobile Working

Security tips for remote working

Mobile security plays a big role in staying safe as many companies want to enable their employees to work securely on smartphones or tablets while they are on the road or away from the office – but they often fail due to IT security requirements. In order to achieve the highest possible security and data protection, companies must implement organizational and technical measures, to protect corporate data and systems.

 

Here below is a list of a few tips that can help employees to protect their organization’s security:

 

    • Free Public WiFi: Working on free WiFi can be attempting for employees who pay for their own data plans. They must be aware that these networks are not secure enough to use when logging into secure systems or transmitting sensitive information (customer data, credit card numbers, etc.). They must access companies’ data via their secure connection at home or enable their 4G for secure connectivity when they are on travel.

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    • VPN: companies that have employees using remote access applications, should use a VPN. With its help, employees can get a flexible connection on different online services and protect the traffic. VPNs allow the creation of a secure tunnel by means of data encryption during the connection. And as it grants access to all work applications and information employees haves feeling of working from the office.

 

    • Password management: When it comes to password management, employees use to take it very light. A good password management is the key to remote working security. Access to the applications containing crucial business and customer’s data must be protected with a strong password that contains at least eight characters, among which there must be capitals, low case letters, numbers, and special characters.

 

    • Two-Factor Authentication: Two-factor authentication is also considered for password protection. It adds an additional layer of security to the authentication process and makes it harder for attackers to gain access to employees’ devices or online accounts. It’s used to limit and control unwanted access to sensitive data.

 

    • Remote Access Applications: organizations must define which applications and data employees can use with their mobile devices, email programs including calendars and contacts, a browser, a document repository, and product and pricing databases.

 

    • Data Encryption: Protecting organizations’ and customers’ personal data is vitally important to the success of any organization. Encrypting that data with one of the best practices to be on the safe side. In the case of remote working, sending emails with sensitive data represents a huge risk. It could be intercepted or seen by a third party. If you encrypt the data attached to an email, it will prevent an unintended recipient from viewing the information. Also, be sure your device is set to have all stored data encrypted in the case of theft.

 

    • GDPR: As GDPR requires companies to have a 180-degree overview of the existing data, they must make data roadmaps with information such as, where the data is located, who is using the data – and is that data is being used in office equipment or remote devices.

 

    • Physical security: Employees must pay extra attention to their devices or files that contains companies’ important data once it’s out of the office perimeter and it’s not in use. Devices with important data in it, must not be left unsecured and unattended in any circumstance.

 

Remote employment is becoming more and more famous thanks to the advanced technologies and the flexibility it offers. Business must give extra attention to the security issues that can come along with the deployment of remote work. They must work on strategies that protect employees and business against cybercrime and offers a safe remote workplace.

2021: Intelligent Data Management Will Enable the Future of Your Business

2021 Intelligent Data Management Will Enable the Future of Your Business

The EU’s GDPR has a major impact on the data privacy ecosystem. The regulation is an essential step to strengthen individuals’ / Business fundamental rights in the digital era we are living in. After two years of the introduction of the GDPR, the following question still arises: What will 2021 bring in terms of data management and data protection? According to Gartner, by 2023, 65% of the world’s population will have its personal data covered under some kind of modern privacy regulations.

 

It’s predicted that the technology for the preparation, control and administration of data will become much more efficient so that data is available more quickly and reliably. With the focus on foundational components of data integration, data governance, and data preparation the effectiveness of big data projects can be improved. With the right technology, data management can also drive enormous business value and support digital transformation. It’ll certainly help organizations to better manage the availability, usability, integrity, and security of their enterprise data.

 

Data has evolved over the years and will continue to evolve. Today’s organizations are data-centric; they accumulate enormous amounts of information in many different formats. Those who are unprepared to deal with the amount of data will be left behind compared to those ready to welcome all business opportunities that big data has to offer. Here below are 5 main areas that play a huge role in the good preparation of data management.

 

  • Data orchestration

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A frequently used term in the sales and marketing domain for whom data has a high priority as their data is the foundation of just about everything, they do. Simply put, data orchestration is the automation of data-driven processes that includes data preparation, making decisions based on that data, and taking actions based on those decisions. Data and API integration and data movement need to grow together to support all kinds of DataOps (data operations) methods. It’s a process that often spans across many different systems, departments, and types of data. It also requires a combination of different technologies that ensure a central data flow. This is the only way to orchestrate data-related activities – across different locations, on-premise or in the cloud.

 

  • Data discovery

In this process, relevant data insights are uncovering and transferred to the business users who need them. A comprehensive directory for searching, making available, saving, and interpreting data and other objects is becoming more and more important. Advanced Analytics enables the automation of mundane data management tasks and frees up resources to actually generate added value from the data. With the right use of data discovery tools, even the non-IT staff can easily access complex data sets and draw out the information they need. This process of knowledge discovery can be performed by anyone, without the technical know-how that was required in the past.

 

  • Data preparation

Data preparation is one of the most difficult and time-consuming challenges facing business users of BI and data discovery tools, as well as advanced analytics platforms, Rita Sallam – Research Vice-President at Gartner.” However Artificial intelligence (AI) has solved this problem by creating the basis for advanced data transformation and by enabling automatic cleansing and consolidation of data. This enables users without any prior technical knowledge to use data.

 

  • Model management

Model Management technologies help organizations consistently and safely in developing, validating, delivering, and monitoring models that create a competitive advantage. The focus is to put the central control of all models in a single application instead of the separate management of individual models. In view of the fact that many analytical models never go into production or quickly become obsolete (model decay), it is important that companies can quickly and easily register new models, adapt, track, evaluate, publish, regulate and document them.  Previously, model management referred just to monitoring production models, but it’s beyond that. Models drive new breakthroughs and operational improvements for businesses. According to a McKinsey study, organizations that leveraged models extensively showed a 7.5% profit margin advantage over their peers, whereas those that did not use models had a 2.5% profit margin deficit compared to their peers.

 

  • Data governance

“A data governance plan, supported by effective technology, is a driving force to help document the basis for lawful processing.” Data protection laws require companies to have data governance programs that provide “data privacy by default” and define policies, roles, and responsibilities for the access, management, security, and use of personal data. If they do not proactively advance standards and programs, they not only run the risk of contradicting legal requirements but they could also lose the trust of their partners/customers. With the use of advanced analytics and artificial intelligence in decision-making, they are therefore even more challenged to bring transparency to the algorithms.

 

Sources:

 

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