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Best Practices for Cyber Security

              Cybercrime is undoubtedly one of the fastest-growing crimes in the world and it continues in all industries. To stay
              protected from cyberattacks, one needs to be aware of the most up-to-date cyber security tips and best practices.
              Cyber security involves protecting computers, servers, mobile devices, electronic systems, networks, and data from
              harmful attacks. The best practices for cyber security are constantly evolving to keep up with the cyber threats.
              Reference Links:
              The following is the list of Do's and Don’ts to be followed for best practices of cyber security:

                                      Do’s                                               Don’ts
               ●   Use strong, unique passwords with a mix of      ●   Avoid sharing personal info like real name or
                  characters for each account.                        phone number.
               ●   Activate Two-Factor Authentication (2FA) for    ●   Don’t send pictures to strangers or post them on
                  added security.                                     social media.
               ●   Download software from trusted sources only and  ●   Don’t open emails or attachments from unknown
                  scan files before opening.                          sources.
               ●   Prioritise websites with "https://" for secure logins. ●   Ignore suspicious requests for personal info like
               ●   Keep your browser, OS, and antivirus updated.      bank account details.
               ●   Adjust social media privacy settings for limited   ●   Keep passwords and security questions private.
                  visibility to close contacts.                    ●   Don’t use copyright software without permission.
               ●   Always lock your screen when away.              ●   Avoid cyberbullying or use of offensive language
               ●   Connect only with trusted individuals online.      online.
               ●   Use secure Wi-Fi networks.                      ●   Don't respond to phone calls or emails, asking for
               ●   Report online bullying to a trusted adult          confidential data.
                  immediately.                                     ●  Don't  leave wireless or Bluetooth turned on when
               ●   Do use privacy settings on social media sites to   not in use.
                  restrict access to your personal information.


                       Acquiring, Processing, and Interpreting Data


              Working with data involves three key steps: acquiring, processing, and interpreting. First, gather data from
              sources like surveys and databases. Next, process it by cleaning and organising it for accuracy. Finally, analyse
              the data to find patterns and insights that help make informed decisions.


              Types of Data
              In statistics, various types of data are gathered, analysed, interpreted, and presented. These data consist of
              individual factual pieces recorded for analysis. Data analysis involves interpretation and presentation, producing
              statistics to get some meaningful insight from that data. Data classification and handling are crucial processes
              that use multiple tags and labels to define data, ensuring its integrity and confidentiality. Artificial Intelligence is
              crucial, with data serving as its foundation. We come across different types of data and information every day.
              Data can be broadly classified under Textual data and Numeric Data as explained.

              Textual Data (Qualitative Data)
              Textual data is the information that is written or expressed using words and language. It includes things like
              articles, books, emails, messages, and any other written content. Instead of numbers, it's made up of letters,
              words, and sentences that convey meaning and information. Qualitative data is also called categorical data.

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