General Data Protection Regulation

Introduction to GDPR: The Who, What, When, Why, and Where of GDPR

Why IT professional should learn about GDPR – it is law in all countries that are members of European Union (EU) and the countries working with European Union or having clientele in European Union countries.

Why GDPR Exist – the core reason to protect the people fundamental rights i.e. Right of Privacy.

Why do we need GDPR – EU Data protection passed in 1995 and as technology evolves there is so many changes in data.

Whom it apply – GDPR applies to organizations that do anything with data about people.

OR

It apply all the organization in EU and all those organization who works with EU i.e. offering goods and services in EU or monitoring behavior.

OR

Simply to say GDPR applies to all organization inside EU or Outside EU who works with people of EU.

GDPR have 06 principles

Data uses is fair and expected
Just have data that’s Necessary
All data must be accurate
Delete when finished
Keep data secure
BE accountable.
What is the risk of non-compliance to GDPR?
1. Reputation – if organization is not complaint with GDPR it means people might not trust that company.

2. Fine and penalties if not following GDPR – fine could be Euro 20 million or 4% global turnover of organization

3. Liability risk – people / customer who are using organization services they can sue the organization if there data is misused or leaked.

In each country has a local Data protection authority. In India there is no such authority but Data protection covers under the IT ACT (70). It is punishable offence and person can get jail term for 3 year or fine of Rs. 5,00,000/-

Let’s understand GDPR in detail -

GDPR Article 1 – “This regulation lays down rules relating to the protection of living humans with regard to processing anything with personal Data… ”

Living humans – means we “people” belongs to any geography.
Processing of personal data – means doing anything or something with data i.e. Collecting, analytics, using, recording, structuring, consultation, retrieval, transmission or be anything.
Personal data – any information relating to and identified or identifiable living human i.e. Social Security number, PAN number, driving licenses.
Three key terms in GDPR
Data subjects – it’s the data of the people whom they work for and who are working for them means customers or employees
Data controller – means where the data controls i.e. information once you login, your work and act you perform
Data processors – where data process, like organization are using cloud services to process the data, it could be AWS or any cloud. Both Data controllers and Data Processors process (do anything with) personal Data. Companies or government can be data controllers or processors.
GDPR regulations -
GDPR splits in to 02 parts

Recitals – 173 recitals in count
Articles – 99 articles in count
GDPR principles in details
1). Fair and expected – let’s discuss in detail, the all processing of data is lawful, fair and transparent. Transparent means – when you are collecting data you should tell people what are you going to do with data, and why.

2). Fair – balancing the fundamental rights and freedoms of person whose data it is, with the rights of holding his/her data for further processing means, A financial website can’t share people personal data with other companies without consent of people.

3) Lawful – there are six reasons of processing the data -

Consent from data subject
Contract from data subject
Legal obligation – companies are bound to share data with government authorities.
Vital interests.
Public interest / official authority – processing of your personal data like Siebel for your financial status.
Legitimate interests.
Key Data Protection Concepts and Principles: All Processing Must Be Lawful
Besides above 6 principle there is special category data which can’t be allowed for processing or need special approval from Government authorities.

The categories are

Allowing Discrimination – race, religion, political party or trade union membership.
Genetic / biometric Data,
Health,
Sexual life/orientation
But still if organization or person wants to process the Special category data in that case they need another good reason and these are 6.
Explicit consent from data subject
Employment – context about employment under special category
Vital interests – healthcare
Substantial public interest
What an organization does
public health processing special category data
(Disclaimer – if you are looking for some government specify information on GDPR in that case you should check with a Lawyer who can consult about GDPR)

Data Recovery Service in Manchester

Data recovery:

The data that is stored in the storage device can be lost at any time. This is the main problem that businesses and users go through from time to time. Digital data is important in today’s time. This could lead to many problems, such as legal and financial. The data stored digitally can be recovered at any time. This process of recovering the data lost is called data recovery. The data is inaccessible because of some physical or logical damage.

During the process of data recovery, the files that have been lost are scanned and retrieved. The data can be recovered from different storage sources such as the laptop’s internal drive for storage, solid-state drive, external hard disk drive, USB flash drive, memory cards, etc.

Physical and Logical failures:

Logical failures: In a logical failure, the data is lost accidentally because of formatting the drive, deleting the data, volume deletion, the drive could get corrupted, reinstalling the O.S., boot failure, etc.

Physical failures: The data that is lost due to connectivity issues, the physical space for storage, damage of any component, failure of any electronic equipment comes under physical damage.

How Data is Lost?

The data can’t be lost if you delete it from the location of storage. After deletion, they are moved to recycle bin available in windows or the trash of Mac OS. The deleted files can be restored from the recycle bin and trash. They are moved back to their original location. Even after the deletion of data from trash or recycle bins, they aren’t deleted. You can easily recover them using some recovery software as they still exist on the drive. The logically lost data can also be recovered in the same manner.

How is Data Recovery Possible?

During the formatting, to increase the computing speed, the OS deleted all the file references. Meaning, the files’ reference is cleared during the formatting, but the files still exist on the drive. The files are not lost completely. If any files are overwritten, then it is complicated to retrieve the original file. Overwriting deletes the files, but it requires many resources of computing and time, so the operating system prefers not to overwrite. Due to this, it is inaccessible and can be retrieved by the software of data recovery.

Limitations of Data Recovery:

It is usually easy to recover data, but sometimes it can be hard during some situations, which are as follows:

It is difficult to recover the data if it is overwritten during formatting.
If the data has been corrupted badly.
If the lost data is present in a defective sector.
Conclusion:
The valuable lost data can be restored immediately. Many unexpected scenarios like deleting the files unintentionally, attack of viruses on the system, crashing of the software, physical damage, etc., can be the reason to lose the files. To overcome this, take the data backup from time to time. If you do not find yourself capable, you can always turn to Data Clinic. If any digital data is to be retrieved, then Data Clinic is the specialist that must be visited in London.

Artificial Intelligence: The New Player in Technology

Artificial intelligence means stimulating human intelligence in machines by programming them to think and act like humans. It also refers to machines that can perform actions like a human brain like problem-solving. It should be able to rationalize and perform actions to achieve a specific goal. It includes machine learning, whereby computer programs automatically learn and adapt to changing data without human intervention. Deep learning enables these machines to automatically learn by absorbing data like images, text, and videos.

Types of Artificial Intelligence

Artificial intelligence is divided into weak and strong intelligence. Systems with weak intelligence are capable of performing only one task at a time. Personal assistants like Alexa and Siri fall under this category.

Systems with strong are complex, complicated, and can carry out tasks like humans. They are programmed in a manner to handle situations without any human interference.

Artificial Intelligence Applications

Artificial intelligence has applications across sectors and industries. Tests are conducted with AI in the healthcare sector, where they are tasked with dosing patients with drugs and conducting surgeries in the operation theatre. Self-driving cars are becoming a massive hit in recent times. Driven by AI, these cars have to decide on their actions as the results depend on their actions. The computer systems of these self-driving cars have to consider the external data and act accordingly to avoid a collision.

Another industry where artificial intelligence is present is the banking and financial industry. It is used to help the banks’ fraud detection departments by flagging suspicious activities like unusual debit card transactions and large deposits. It makes it easier to estimate the demand and supply of securities, which helps make trading easy.

Speech recognition is the capability to process human speech into a written format using Natural Learning Process. It is incorporated as the voice input feature in numerous mobile devices. Online chatbots are replacing human correspondents in the customer care industry by letting users choose the problem they are facing for the chatbot to understand, then it provides answers based on its understanding of the user’s problems. Computer vision is an AI technology where computers can derive information from images, text among others, and act based on this information. With convolutional neural networks it is used in photo tagging, radiology imaging, and many other industries.

AI algorithms can discover data trends that can be used in cross-selling strategies using past consumer behavior data patterns. Add-ons at the end of the checkout process also rely on AI algorithms.

Why study Artificial Intelligence?

Studying AI prepares one to become a software engineer interested in the research of neural networks, quantum artificial intelligence, and human-machine interfaces. People can also work as software engineers for companies by creating recommendation lists for shopping and processing vast data sets. An education in AI opens up the opportunity to become a hardware engineer who develops robots for home assistance or electronic parking assistants. AI as a field did not exist ten years ago and is continuously growing even today. AI is admitted to have the capability to solve many of the world’s current and upcoming problems. It is a constantly evolving field with job prospects available, now possibly becoming commonplace in the future.

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