What is Data Fusion?

Data Fusion is a fully managed, cloud-native, and flexible enterprise data integration platform offered by Google. It is designed for quickly developing and managing data pipelines.
With organizations dealing with massive amounts of varying data, Data Fusion helps bring it together, easing the application of data analytics. This platform can bring social, machine, or transactional data in different formats from applications, messaging systems, and databases, to mention a few. Also, it provides an intuitive visual interface, enabling you to visualize your data.
Additionally, Data Fusion offers advanced deployment capabilities. This enables you to execute data pipelines on popular managed cloud services such as Dataproc and Ephemeral. Even better, this enterprise integration platform is powered by an open-source CDAP, making the pipelines portable across GCP and hybrid/multi-cloud architectures. So, if you’re running on such cloud strategies, Data Fusion simplifies the deployment of your data pipelines across different cloud providers.

How Does Data Fusion Support Enterprise Data Integration?

Data integration is often a complex process. However, Data Fusion is optimized for integration, accelerating data transformation and analytics. Here are some of its integration capabilities:

• Connectors

Data Fusion supports over 200 data connectors and formats. This allows you to extract and merge data from different sources. Also, you can build data pipelines in a visual model-driven environment, helping improve productivity.

• Parsing and Enriching of Unstructured Data

Businesses often generate large volumes of unstructured data. This data is among the most challenging to integrate, analyze, and gain meaningful insights. However, Data Fusion offers capabilities to effectively parse and enrich unstructured data.

For instance, it uses Cloud artificial intelligence (AI) to convert audio to text. Also, it applies natural language processing (NLP) to extract features from documents and images and convert HL7 to FHIR. This helps ensure enterprise data integration processes comply with relevant regulatory standards.

• Data Wrangling Capabilities

Data Fusion offers advanced data wrangling capabilities. This enables you to seamlessly prepare and operationalize data. As a result, it improves business-IT collaboration, enhancing the overall outcome of your integration initiatives.

• Pre-Built APIs

APIs often act as the gateway to integrating data from different sources. The Data Fusion platform offers a library of built-in APIs, frameworks, and sensors. These features facilitate seamless enterprise data integration.

Also, it allows you to use the extensive REST API to develop, orchestrate, manage, and automate the lifecycle of your data pipelines. This streamlines enterprise data integration by consistently gathering, cleaning, and transforming data.

• Operational Analytics and Insights

As initially stated, enterprise data integration is a complex process. Many things can go wrong, resulting in significant losses. For instance, if data is not cleaned properly before being used for analytics, it can lead to misinformed decisions.

Data Fusion offers operational insights, enabling you to track data integration processes. Also, you can easily manage service-level agreements and optimize integration tasks based on these insights.

• Versatility

Data Fusion is a versatile data integration platform. It supports all data delivery modes, including real-time, streaming, and batch. This makes it a comprehensive platform for addressing streaming and batch-related use cases.

4 Benefits of Using Data Fusion in Enterprise Data Integration

Here are some reasons why you should consider Data Fusion in enterprise data integration processes:

1. Data Protection

Organizations often handle sensitive data. During integration, data can be exposed, leading to potential security breaches. However, Data Fusion offers various options for securing data, including the following:

• It allows you to store sensitive JDBC strings, URLs, and passwords in Cloud KMS and connect to external KMS systems.
• Data Fusion provides VPC Services Controls to protect data from exfiltration.
• This platform integrates with Cloud DLP, enabling you to encrypt, redact, and mask data in transit.
• It encrypts all data at rest either by default or through customer-managed encryption keys.
• Data Fusion offers a Private IP, facilitating secure access to on-premises data.

2. Data Consistency

Data consistency is a critical success factor in enterprise data integration. Data Fusion ensures data consistency in various ways, such as:

• Providing structured ways to specify transformations.
• Identifying changes in data formats and customizing error handling.
• Tracking data profiles to identify quality issues.

3. Modeling and Metadata

Data Fusion helps you gain insights into enterprise data integration processes with metadata. With Data Fusion, you can:

• Collect operational, business, and technical metadata for pipelines and datasets.
• Exchange metadata between integration and catalogs with end-user workbenches through REST APIs.
• Have a comprehensive data view, enabling you to understand profile data, relationships between datasets, and process flows.

4. It’s Open-Source

More organizations adopt hybrid/multi-cloud architectures to get the best out of each cloud platform. Data integration in such an environment is more challenging due to varying architectures. However, Data Fusion eases enterprise data integration in such settings.

It is a cloud-native and 100% open-source framework. Therefore, it allows you to build cloud-based and on-premises data analytics apps. You can execute and deploy integration pipelines across different environments without changing them to fit your business needs.

Final Thoughts

Data Fusion is a revolutionary enterprise data integration platform. It allows you to quickly and efficiently integrate data from different sources, create pipelines, and apply transformations. So, if you’re struggling to meet your data integration goals, it’s time to switch to Data Fusion. By embracing Data Fusion, you’ll make your data teams more productive and happier.

Also Read: Right Blend of ERP, CRM, Cloud, and Analytics Drives Digital Transformation

The post Data Fusion: One-Stop-Shop For All Enterprise Data Integration appeared first on TechReviewsCorner.

Protect Network Access

Most teleworkers use WiFi, so there is a need to protect network access effectively. Unfortunately, this type of connection is not the most secure today for protecting personal data. To avoid any intrusion into your computer, it is essential to set up a secure password., which you can regularly change. Ideally, this password should be 12 characters long and include numbers, letters, and special characters. Specialized software such as LastPass, Dashlane, or Keeper now makes it possible to find, manage and save secure passwords. To best ensure cybersecurity, avoid connecting to the Internet via a public WiFi network, which is particularly exposed to attacks.
If the company does not offer one, using a VPN (Virtual Private Network) also proves to be an attractive solution to protect the exchange of information. This virtual private network makes it possible to hide the IP address and encrypt the data during authentication, for example. Filtering by MAC address (Media Access Control) offers the advantage of only allowing network access to a limited number of devices.

Update Your Computer

Viruses and other malicious software take advantage of the vulnerabilities of our computers to enter their systems. This is why updating your equipment as regularly as necessary through the computer’s operating system (OS) or specialized software is essential. Windows and Mac OS, of course, regularly offer these updates free of charge. Depending on the OS system preferences, they may be downloaded manually or automatically. Companies must make employees aware of this practice as much as possible.
Also, remember to acquire an effective antivirus, which you will also remember to update frequently. Some are free; others are paid. If the level of protection offered by these 2 solutions does not vary drastically, paid antiviruses always offer additional features, such as WiFi security alerts, ransomware removal (extortion software), hard disk cleaning, or protection against phishing (phishing of personal data). Among paid antiviruses, Norton, Kaspersky, and Bitdefender is the reference.
Particular attention will be paid to the data security of Windows computers. Due to its popularity, this operating system is much more subject to computer attacks than Mac OS.

Adopt Good Practices Daily

The GDPR recommends a few rules to ensure the computer security of your professional tools, whether remote or face-to-face.
Remember to lock your computer when you are away to limit the risk of someone accessing your data.
Avoid working in public places without screensavers, especially when handling sensitive data. Visual piracy is a very real phenomenon. According to a study, 87% of respondents had already noticed furtive glances at their screen from strangers in a public work situation1.
Back up your data daily via a USB drive, external hard drive, or secure cloud service. If you were to be the victim of a cyber-attack, this data would thus remain perfectly protected.
Separate the private and professional spheres, avoiding using the computer for personal purposes (shopping, Facebook, Twitter, other social networks, sports sites, etc.). Today there are nearly 2 billion websites, and not all offer the same security guarantees. The presence of a padlock or the mention of “https” at the beginning of the URL generally guarantees a high level of security.
Beware of suspicious emails; do not click links without checking where they redirect. Email providers rightly ask for your permission to download attachments. In some cases, they may contain malware harmful to your computer3, especially in .rar and .zip archives or Microsoft Office documents.
If you have any doubts about the security of your connection, do not hesitate to inform your supervisor or contact your company’s IT manager.

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When referring to data analysis, the term big data is frequently used. It refers to the collection, management and analysis of a large volume of data which, due to its size and complexity, exceeds the processing capabilities of traditional tools.

When mastered, DA offers a competitive advantage to organizations by allowing them to identify new opportunities and capitalize on their knowledge to make the best possible strategic decisions.

Data analytics solutions are evolving as the digital transformation of businesses progresses.

Despite their apparent complexity, any company can benefit from their advantages by following the correct methodology.

In this article, we share some tips that will allow you to benefit from the advantages of data analysis in the concrete case of business decision-making.

What Is Data Analytics?

Data analytics consists of analyzing data to detect trends and draw conclusions on available information.

This analysis is carried out using specialized software that transcribes the information analyzed on dashboards to optimize strategic decision-making.

The final objective sought by DA is to boost a company’s performance. According to Austin math tutoring experts, people most eligible for work in data analytics are those with degrees in computer science, economics, finance, statistics, and applied mathematics. Math knowledge is crucial for understanding algorithms, statistical methods, and data analysis techniques, which are foundational for extracting meaningful insights from complex data sets.

Decision-Making Based On Data Analysis

To facilitate decision-making processes based on data analysis, it is necessary to ensure that the information available is appropriately organized, accurate and easily interpretable.

The first essential step in structuring these processes is creating a standard procedure for integrating data from different sources, internal or external, into the organization.

At the end of this automation comes the supervision stage and analysis of the data presented.
This analysis is done through interactive dashboards designed to make data analysis visual and intuitive, allowing you to understand the information presented quickly.

This system extracts data in real-time, allowing for more accurate analysis.

The use of data to drive decision-making in business strategy is known as data-driven decision-making.

Let’s Take a Look At The Different Steps of This Method.

Definition of The Problem

Initially, it is necessary to know the initial status of the situation to be analyzed and to identify the possible problem to be solved. 

To do this, open questions can help identify the problem to be solved: What is the ideal analysis scenario? What is the current situation? 

Data Preparation

Once the problem has been identified, it is necessary to understand what data must be analyzed to improve the initial situation or to solve the problem.

In this case, the following questions may be relevant: What data should be collected to solve this problem? How can this data be obtained?

Data Processing

Once the data has been collected, the next step is to process and prepare it for further analysis. During this step, it is essential to consider which information is relevant and which should be deleted. This database cleaning is necessary to obtain the information that is really useful for the final objective. 

Data Analysis To Draw Lessons

Finally, we move on to the data analysis phase to study the problem and find possible solutions. In this phase, we must answer the following questions: what information does this data bring to the initial problem? How does this knowledge help us solve this problem? 

Implementation Of Analysis And Modeling

At the end of the steps described above, all the conditions are met to apply the analysis carried out to decision-making based on the results obtained.

Concretely, all the steps consist of defining an objective (what must be solved), designing the strategy (how to solve it), determining the strategies (actions to be taken) and choosing the key indicators that will be used to analyze the results.

Data Archiving

Finally, the last step consists of electronically archiving all the valuable information resulting from the processing and analyzing of the data.

This archiving makes it possible to access the information necessary during or at the end of this analysis to meet the conservation and data protection standards. 

Conclusion

The high level of competition in the market forces large companies to turn to data analytics to improve their decision-making.

Today, a large amount of information is archived, allowing the use of artificial intelligence to generate reports and dashboards that facilitate the search for solutions, with the ultimate goal of optimizing the profitability of the company. ‘company.

Using data analysis techniques, it is possible to interpret basic information to detect trends or uncover insights that will aid decision-making for business success.

The post How To Get The Benefits Of Analytics For Business Decision Making appeared first on TechReviewsCorner.

What Exactly Is The Customer Database?

By definition, the customer database consists, as its name suggests, of a set of organized and structured data relating to the company’s customers. Easily accessible, these can be modified and updated regularly.
The customer database, therefore, brings together all the information collected during the various transactions carried out between customers and the company, from cookies to customer contacts. Conventional knowledge combines socio-demographic data (age, date of birth, income level, etc.) and psycho-behavioral criteria (activities, media visited, centers of interest, etc.). In addition to all these criteria, there is data on the key contacts within the company who play an essential role in purchasing decisions and generating profits.

What Use?

Focusing primarily on customers, the customer database above all offers the company the possibility of targeting offers and personalizing them according to the profile of each customer. You quickly generate leads and build better customer relationships with the right basics. The customer database’s objective is to facilitate the connection with your customers and to help you subsequently adapt an offer according to their needs. In addition to increasing sales, this tool promises better customer satisfaction and increased loyalty to your brand and your business.

The customer database also helps the company understand each customer’s value and behavior, especially their purchasing behavior. The idea is to sift through all transaction data and purchase histories to determine if a customer is a frequent product purchaser or inquired about a particular offer or service.

A better understanding of customer behavior can also help increase company revenue and turnover. Indeed, by knowing precisely what your customers and targets are looking for, you can offer the right product at the right time and to the right customer through relevant business management. According to the 20/80 rule, 20% of customers represent 80% of business volume.

What Data Should Be Collected?

As mentioned above, data collection for the customer database must be organized and structured for optimal efficiency. The rule is that the information you collect should only be what you need in ​​customer relations and your marketing strategy. Avoid spreading yourself too thin at all costs and focus on the valuable data that makes sense for your business and achieving your objectives. Aside from the contact name and email address, the nature of the data to be collected varies depending on the company’s B2B or B2C status.

• If you are a B2C company, it is essential to collect the age and the gender of the customers, which determine the mode of consumption, the data which relate to their behavior of purchase, and the customer journey (for example, the number of orders and the average basket), without forgetting the centers of interest of the customers and the data relating to customer satisfaction.
• On the other hand, in B2B, you must focus on the legal and administrative data of the company, i.e., the company name as well as the SIRET, VAT and RCS numbers, the sector of activity, and the size of the company as well as the function of the contact within this company. Do not forget the phone number either, because, in B2B, the email address is not enough.

What Should I Do?

Today, collecting different information intended to set up a quality customer database is done in several ways. Practically, the newsletter is a great way for your business to establish a connection with your customers and stay in their minds regularly. To be effective, it is still necessary to ensure that the newsletter brings quality content with a specific added value to your client and stands out from those sent by competing companies.

• More and more customers are enjoying contests. In addition to being entertaining, they still need to offer freebies that live up to your customer’s commitment to your business. Don’t hesitate to be generous by providing an additional gift to those who sponsor a loved one.
• With the survey and the satisfaction questionnaire, you directly ask for customer opinions on your offers and services, your prices, the quality of the reception, or the general atmosphere in your point of sale. In addition to these tools, there are the advantages of the various events, the order forms, or the card designed to build loyalty.

In any case, since you are asking for valuable customer data, always remember to formulate your request pleasantly.

A customer database is essential for developing a company and its customer portfolio. In addition to grouping customer-related information, it also makes it possible to target offers and increase turnover. For a better organization, using CRM and EDM software becomes essential to facilitate access to data, better know customers and their needs and find new customers through a prospecting plan. And an effective acquisition and retention procedure, but also to enable all employees to work and communicate more efficiently and improve the base’s performance.

The post What Is A Customer Database? appeared first on TechReviewsCorner.

What is RAM, and What Does it Do for Your Computer?

RAM, or random access memory, is a type of computer storage that stores data and programs temporarily while the computer is running. The data stored in RAM can be accessed quickly, making it an essential component for fast and efficient computing.

When you open a program on your computer, the data associated with that program is loaded into RAM so that the processor can quickly access it. The more RAM you have, the more programs you can have open at the same time without your computer slowing down.

Additionally, RAM stores data that the processor needs easy and quick access to, such as recently used files or frequently accessed websites. While RAM is a vital part of any computer, it is essential to note that the data stored in RAM is only temporary. When you turn your computer off, all of the data in RAM is deleted.

This might seem confusing, but it’s important to remember that RAM is not a permanent storage solution like a hard drive. If you’re looking to sell your old RAM, it’s essential to make sure that you understand what it is and what it does.

How Much is My RAM Worth?

The value of used RAM depends on a few factors, including the type of RAM, the brand name, and the condition of the modules. DDR3 and DDR4 memory modules are worth more than older types like DDR2 and DDR.
Some brands are also more popular than others, so that you may get a higher price for modules from well-known companies like Samsung or Corsair. And finally, damaged or defective modules will sell for less than those in perfect condition.
If you’re looking to sell your used RAM, it’s good to research the current market prices. A few online resources list average prices for different types of memory, so be sure to check them out before setting a price. Also, remember to consider shipping and handling fees when pricing your modules.

Why Should You Sell Your Old RAM?

Anyone who has ever owned a computer knows that it can start to run more slowly over time. One common reason is that the RAM, or random access memory, becomes full. This can happen if you install new programs or download many files.
When the RAM is full, the computer has to work harder to access the information it needs, slowing it down. If you have an older computer with only a few GB of RAM, upgrading to a newer model with more RAM can be expensive.
However, there is another option: selling your old RAM modules. Some companies specialise in buying and selling used computer parts, and they will usually pay a fair price for RAM modules. In addition, selling your old RAM is a great way to clear out some clutter and make extra money.

How to Sell Your Used RAM?

Now that you know what you need to know about selling your old RAM, it’s time to learn how to do it! The process of selling RAM is pretty simple, but there are a few things you should keep in mind. Here’s what all you need to know about selling used RAM memory.

Find a Buyer

The first step is to find a buyer. There are a few different ways to do this: you can post an ad on an online classifieds website like Craigslist or sell your modules to a memory dealer.

If you go the online route, include all necessary information about your modules, including the type, brand name, and condition. You may also want to take pictures of the modules so buyers can get a better idea of what they’re buying.

Also, it’s essential to know what kind of specs your potential buyers are looking for. Not all types of RAM are compatible with all sorts of computers, so you’ll need to make sure you’re selling the correct type.

DDR3 and DDR4 RAM are the most popular types right now, but older types like DDR2 and DDR may still be used. You can find out what kind of RAM your computer uses by looking at the label on your motherboard or checking your system information.

Negotiate a Price

Once you’ve found a buyer, it’s time to negotiate a price. This can be tricky since the value of RAM varies depending on the type and brand. It’s a good idea to start by asking for more than you’re willing to accept and then work your way down to a price you’re comfortable with.

Finally, it’s time to ship your modules! Be sure to package them securely and include tracking information so you can follow the package’s progress.

Why are ITAD Vendors the Best Choice to Sell Your Old RAM?

When you’re looking to sell your old RAM, there are a few things you need to take into account. One of the most important is finding a reputable and trustworthy buyer. This is where ITAD vendors come in.

An ITAD vendor is a company that specialises in buying and selling used computer parts, including RAM modules. They have a reputation for being honest and reliable, and they will usually pay a fair price for RAM modules in good condition.

In addition, ITAD vendors offer a secure online marketplace where buyers and sellers can meet and negotiate prices. This makes it easy for buyers to find the right modules and for sellers to get the best price for their products.

If you’re looking to sell your old RAM, ITAD vendors are the best choice for a buyer. They’re honest, reliable, and have a secure online marketplace where buyers and sellers can meet. In addition, they usually pay a fair price for RAM modules in good condition.

Important Tips to Consider When Selling Your Old RAM

• When pricing your modules, take into account shipping and handling fees.
• Ensure you know what type of RAM your computer uses before selling it.
• Research current market prices for RAM modules to get an idea of what you can expect to get for them.
• Pack your modules securely and include tracking information when shipping them.
• Take pictures of the modules before shipping them to give buyers a better idea of what they’re buying.
• When selling online, include all necessary information about your modules.

The Final Word

So, if you are looking to sell your used RAM, be sure to keep all of these things in mind. By following our tips and being aware of the current market value for RAM modules, you can ensure that you get the most money for your old hardware.

The post All You Need to Know about Selling Used RAM Memory appeared first on TechReviewsCorner.

1. Move to “Sustaining Support” that doesn’t cover critical updates, fixes, and security updates.
2. Embrace market driven support offered through Oracle’s Advanced Customer Service to cover years 2022 and 2023.
3. Upgrade to Oracle EBS 12.2 to get premier support till 2032.
4. Upgrade to Oracle Cloud

Upgrade to Oracle Cloud is the best option for innovative enterprises as Oracle will not only take care of the maintenance and system upgrades but also rolls out continuous updates and functionality that will help them efficiently and effectively manage their business. Although migration to Oracle Cloud offers numerous benefits like scalability, business continuity, security, & low total cost of ownership, however, it is considered as the devil is in the details. Oracle has been saying that most on-premises Oracle E-Business Suite deployments can be migrated to Oracle Cloud without needing significant change in configuration, integration, or business processes. However, to ensure that application breakdown will never occur post migration, you data is secure, and your apps serve your purpose, you need to include pre-migration, in-migration, and post-migration testing scenarios.

Given below are the important types of testing that need to be executed while migrating Oracle EBS to Oracle Cloud.

Regression Testing: This is the most critical testing type in which production-like environment on the cloud is used to test applications. Regression testing validates whether your Oracle Cloud Apps are at par in performance to on-premise. Since complete regression testing involves lot of timing, especially when executed manually, it is recommended that enterprises should Oracle test automation framework that accurately offers the exact scope of regression testing during EBS to Oracle Cloud migration. This will help you achieve adequate coverage based upon your mission critical business processes.

Load Testing: It is a type of performance testing performed under a specific expected load. This type of testing is executed to determine how application will behave when accessed by multiple users simultaneously.This type of testing ensures that applications are functioning smoothly and stable when test under load. In case of EBS to Oracle Cloud migration, apps are subjected to load testing to monitor their performance. This type of testing is critical to determine performance especially when the apps are under the most stress, i.e. during a month-end financial close for ERP applications. Major benefits of load testing are

• Reduced risk of downtime
• Service availability assurance post-migration
• Overall peace of mind towards business continuity

Compatibility Testing: Any enterprise application is of no use if it doesn’t interact seamlessly with other third-party applications in the sandbox. Compatibility testing ensures that your EBS apps are seamlessly interacting or send and receive data with other critical systems in your environment.In case of EBS, you need to check compatibility across

• custom or third-party enterprise apps
• Browser
• Network
• Devices
• Java, Oracle Application Server, RAC

Functional Validation Testing:Once you complete your Oracle Cloud migration, you need to execute functional validation testing. With this, you can confirm the production readiness of your Oracle EBS apps.Comprehensively, functional validation testing comprises unit testing, sanity and smoke testing, integration, regression, and usability testing. Your testing should ensure that

• Your applications are performing as intended
• Your critical integrations are working.
• Your customizations are performing as intended.
• UI is user friendly

Final Thoughts

The importance of testing cannot be undermined during EBS to Oracle Cloud migration. If you need to avoid bumpy migration journey, then you need to bring in test focused Oracle Cloud migration strategy. A robust testing strategy will not only avoid application failure post migration but also helps in keeping a check on migration timelines and budget.

Also Read: What Type Of Mobile Application To Develop And Why?

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Backdoor – Right or Wrong?

The backdoor can be translated as “backdoor” – and that shows what law enforcement agencies are after when they demand backdoors: programs should be given alternative access methods, and conventional security mechanisms, such as end-to-end encryption, should be circumvented. Authorities such as the BKA repeatedly emphasize how vital access to encrypted communication is in the fight against criminal offenses in general and child pornography and terrorism in particular.

The terms “backdoor” and “trojan” are often used in the same breath, but they differ in their function. A Trojan is a program often disguised as a helpful tool but performs other functions. Cybercriminals often use Trojans to install a backdoor in the first place. Therefore, the Trojan is the tool for attackers who want to gain unauthorized access. The backdoor itself enables alternative access to the system.

End-To-End Encryption – Arguments From Data Protectionists

Data protectionists reply to those demanding backdoors that weakening the end-to-end encryption through a backdoor would no longer protect users but endanger them. If messages are not encrypted, they are transmitted in plain text and can be read by anyone – not just investigators. This means that criminals or foreign intelligence services could also exploit backdoors.

Advocates of encryption see both human rights and democratic values ​​at risk. A surveillance state could emerge from the softening of end-to-end encryption, for which access to public communications could become a matter of course. One thing is clear for data protection officers: It is entirely pointless to create weaknesses in the currently secure transmission that both authorities and criminals could exploit.

Lots of Ideas For Decryption

Accepting the arguments of data protection advocates and privacy experts, authorities want to bypass end-to-end encryption without breaking the security that encryption brings. To do this, you rely on various ideas. Some times the data and PC is attacked by different types of viruses, to avoid this we can use various tools. Free Trojan removal tool is one of them which will be on alert all the time and will advice you if one of them is trying to access your system.

The Apple group has been arguing with the FBI for years: the law enforcement agency wants to access encrypted communication to put a stop to criminals. However, Apple claims that backdoors have no place in end-to-end encryption. You can read the full story behind the dispute between Apple and the FBI in this post.

PhotoDNA With Inconsistent Encryption

The remarkable thing about end-to-end encryption is that only the sender and the recipient can read the content of the communication. This is also referred to as end-to-end encryption. In the case of non-encrypted contact, on the other hand, there are various options for decrypting – one of them is PhotoDNA, developed by Microsoft in 2009. This is already being used by Facebook, Twitter, Google, and Microsoft.

With this tool, photos or videos are converted into a unique hash value, i.e., into a checksum. This checksum is compared in the database in which known media with criminal offenses such as child pornography are stored. The messages are checked manually or forwarded directly to the responsible authority when the system responds.

As mentioned, the PhotoDNA method only works if the encryption is not consistent. With end-to-end encryption, only cryptic data salad runs through the servers. Experts are now thinking that the checksum and comparison process could affect the sender’s end device before end-to-end encryption, but this is not particularly practical. A hybrid variant would also be conceivable: the hashes could be created entirely or partially on the sender’s smartphone. The checksum is then compared on high-performance servers or in the cloud. A comparison on several servers from different operators would also be conceivable – there would then be no central points of attack.

Upload Filter Against End-To-End Encryption

Another way to circumvent the end-to-end encryption is so-called upload filters – they work similarly to the PhotoDNA method from Microsoft. Both variants aim to recognize content using comparison databases automatically. Upload filters work as follows: content should be analyzed by the messenger either before end-to-end encryption or after decryption by the recipient on the respective end device. The resulting fingerprint is to be compared with the database. This comparison can take place locally on the device or provider servers or servers of third parties.

If there are matches between the fingerprint and the database, the actual end-to-end encrypted communication should be forwarded either to the provider or directly to the government agency. This means that content no longer stays with both ends – the sender and the recipient. Depending on the result of the automated analysis, they also end up with third parties. The bottom line is that one can also speak of a backdoor here.

The End of End-to-End Encryption?

In addition, there is the imponderability of automation using artificial intelligence (AI): Experts expect high false-positive or false-negative rates when recognizing the content. An example of matching using the PhotoDNA method clarifies: what if the criminals change just one pixel in an image? The hash value varies immediately so that recognition by the database fails. The papers repeatedly suggest detection of suspicious content by AI,

In the encrypted room, not only child pornographic and thus, of course, highly illegal and despicable content is exchanged. There are also journalists in this room who report from countries that are not democratic – and they can only do this because of the end-to-end encryption. It also contains countless private communications from ordinary people. That would mean: Critics in dictatorships would no longer have a chance to communicate, activists would no longer be able to network, sensitive data could no longer be exchanged securely. End-to-end encryption would be nothing less than the nail in the coffin for accessible communication.

The post End-To-End Encryption – Forced To Decrypt appeared first on TechReviewsCorner.

We will focus on the business world, on the importance of creating and investing in occupational health and safety systems. In this sense, organizations can find in the analysis of HR data. H H. an opportunity to know the variables that impact the accident rate, evaluate the effectiveness of preventive measures or obtain a level of risk to anticipate in decision-making.

Objectives of Occupational Health And Safety Management

The Occupational Health and Safety Management System encompasses a discipline that seeks to prevent injuries and illnesses caused by working conditions and the protection and promotion of employees’ health.

This implies, among other actions, identifying dangers and risks and implementing preventive measures to reduce the accident rate. Furthermore, it is conceived as a continuous improvement system to anticipate, recognize, evaluate and control all risks that may affect safety and health at work. Thus, being a management system, its principles are focused on: plan, act, verify, adjust.

To respond to all of this, we have in data analysis a powerful tool that can help us make more objective decisions based on data that allow us to improve the management of safety and health at work.

First Steps of Data Analytics In Health And Safety

As in any data analysis project, and especially in the field of HR. . HH, it is imperative to involve from the beginning all stakeholders or stakeholders: responsible for the prevention, production areas, processes, human resources, IT area, legal, data protection, etc.

The starting point will be one or more questions related to the business, giving us relevant information about the process we want to improve. In this case, for example:

• What activities are most likely to be an incident or accident?

• What factors have a more significant impact on the risk of a specific activity?

• Is there a relationship between the days of the week and the accident rate?

• Does training in health and safety or implementing some corrective measures influence reducing the accident rate?

• Are there subcontractors with higher workplace accident rates?

We also need to know the data on incidents and accidents and with what period: activity, date, and place of the incident or accident, its severity, location of the injuries, corrective actions, inspections, etc. And it is also interesting to cross them with the information from the HR systems. HH., Related to the professionals involved: experience, prevention training, seniority, subcontractor company or not, etc.

From the initial questions, we will pre-select the initiatives that allow us to address a strategic issue for the organization and that are feasible due to having sufficient data. We will prioritize having the first results in 2-3 months (the so-called minimum viable product) and sponsoring the project. This will allow us to communicate the results of this pilot project and for the data culture to permeate the organization.

Also Read: RPA – Threat or Opportunity For The Business World?

How Do We Analyze Occupational Health and Safety Data?

Once the question or questions on which we are going to focus and the existing data have been identified, we will define the most appropriate methodology: classical methodology, with a clear objective, planning, and defined deliverables; or agile methods, with a high-level objective and scope and sprints of a determined duration, defining after each sprint the narrower scope of the next.

At this time, we can also set up the project team, usually multidisciplinary, incorporating the appropriate profiles: business analyst, project manager, data engineer, data scientist, psychometrician, scrum master, agile coach, computational linguist, developer of software, etc. All those involved must participate in the project initiation meeting, in which they align expectations and finish defining the requirements.

In the initial phase, the data extraction, treatment, and cleaning (ETL) will be carried out, at which time the data history with which we are going to work is defined. It is also interesting to assess the relevance of incorporating external data, such as the weather or the calendar of holidays, or the age of the work machines, for example.

The analysis phase can begin once the analytical table has been made with the clean data, according to the project objective and the available data. According to these, the type of analytics to be addressed will also be chosen:

• The descriptive-analytical or inferential statistics will allow us to identify linear relationships between variables relevant and accidents and know, in quantitative terms, how they are impacting incidents and accidents in the organization. Likewise, we can study the effectiveness of preventive measures in terms of their impact on the probability of incidents and accidents.
• A predictive model will be helpful if the goal is to anticipate. It is possible, for example, to obtain a level of risk related to the probability of an incident occurring in a specific activity, taking into account the historical data and the variables that have the most significant weight in that prediction.

It is essential to take steps little by little: start from descriptive analysis to understand what is happening and move towards predictive analytics in HR that allows us to anticipate decision-making based on data and positively impact people’s safety and health. In the latter case, it would also be possible to simulate scenarios or test the impact of certain decisions in simulators or dashboards custom-built for the organization.

Whatever the objective and the analysis methodology, on this path to incorporate the culture of data in health and safety, we will find value, providing more excellent knowledge about the factors that impact incidents and accidents. And that affects the health of working people. This will allow us to prevent them, thus increasing productivity and efficiency and a more significant commitment from the people of the organization and other stakeholders.

The post Data Analysis In Occupational Health And Safety Management appeared first on TechReviewsCorner.

However, there are some things that you can do yourself to help improve your cybersecurity and make your current defenses perform better.

Knowing what methods and devices that cybercriminals use to infiltrate devices and software can make your life easier when it comes to avoiding an attack and protecting yourself. Not opening suspicious links or sending money to people you don’t know when asked to can be relatively easy ways to avoid malware, such as Trojans or viruses, getting into your computer systems. As well as that, here are a few more tips you should follow to protect yourself and your data when online.

You should start to take more responsibility for how you use the internet

You need to be careful of what you download and always make sure that your network is secure. Ensuring you have a secure network stops Advanced Persistent Threats (also known as APTs) from occurring and getting a hold of any data that might be entering or leaving your device.

It’s one of the many reasons why you should never do a money transaction over the internet when using public Wi-Fi, as they are unprotected networks and can be infiltrated by hackers easily. 

You should also change your passwords regularly

This is to stop hackers from gaining access to any accounts you might have that will allow them to get to your sensitive data. Just because your personal cybersecurity is strong, it doesn’t mean to say that the company with whom you’re trusting your data does.

Another thing you can do is invest in multiple security services to keep you safe

Investing in services such as authentication services like nfc systems or in network security services to put up a stronger defense against APTs (which we mentioned before) can help protect your information really well. They put up a more robust layer to boost your security so you are better protected against identity fraud.

Using services such as operational security (or otherwise known as OPSEC) will give additional security to your systems as it will analyze the data entering and leaving your device and processes it to see if it will be useful to a hacker if grouped and analyzed properly to reveal more data about you. 

Final thoughts

While these are not all of the ways you can protect yourself against cybercrime, these methods can be quite easily implemented but can significantly improve your level of protection, and as such should be the first things you consider.

Also Read: The Art Of Cyber Risk Prediction And How To Stay One Step Ahead Of Cyber Attacks

The post Tips On How To Protect Yourself Against Cybercrime appeared first on TechReviewsCorner.

Spread of the AI-supported data fabric

The pandemic made it clearer than ever that the provision of information for business needs to be accelerated significantly. However, this can often no longer be achieved with conventional data integration methods. The integration of new data sources into heterogeneous infrastructures is becoming increasingly complex and it simply takes too long before new queries can be made available to data consumers. Against this background, more and more companies are turning away from traditional data architectures and relying on more agile forms of data integration, such as those of the logical data fabric. This concept stands for seamless data integration in heterogeneous environments as well as the fast provision of information for the business.

This trend will consolidate in 2021 and more and more organizations will pursue a holistic data strategy. The concept of the data fabric, in particular, will play an important role here. These agile architectures enable reliable real-time data flow without physical replication of the data. In addition, the implementation of AI technologies in the data fabric will continue to establish itself in order to ensure more automation, especially in the areas of data discovery, performance optimization, and workload management.

Cloud integration instead of cloud migration

Most companies are now in the cloud migration phase: more than 60 percent of organizations use the cloud and 25 percent are even pursuing a cloud-first approach, according to a current study. In the context of the Covid-19 pandemic, this trend has intensified and many companies have recognized the advantages of cloud computing. So far, the focus has been on the migration of data to the cloud. Although this approach promises success, it can lead to so-called “technical debts” – that is, negative consequences due to insufficient technical implementation of software – because the new systems are often only very loosely docked to the existing IT infrastructure.

In 2021 the focus will shift from pure migration to full integration of the cloud into the data strategy. Gone are the days of trying to physically consolidate all data in one place: Given the sheer volume and heterogeneity of the data, this seems out of date. Rather, modern architectures such as the logical data warehouse or the logical data fabric promise seamless integration of all company data without physical replication. Complex access authorizations can be managed centrally and securely and the data can be made available to the business in real-time for analysis.

Monetization of data

The best possible use of data for advanced analytics to derive strategic recommendations for action is already a high priority for most organizations. For this purpose, investments are made in the modernization of data architectures in order to supply the data consumers from the business with the required data sets.

In 2020, the pandemic made us realize the importance of having quick access to accurate and complete data in order to make the right decisions. Many large companies therefore already have valuable data services in place. In 2021 we will observe that more and more companies are providing their data services and, on the other hand, including 3rd party data services in their own analytics.

For example, geolocation data can already be obtained from telecommunications companies, financial companies offer information on the valuation of financial assets, and companies in the real estate sector sell statistics on the housing market. This trend of monetizing data will spread to other industries and sectors in 2021. From a technological point of view, the need for data-as-a-service tools, such as GraphQL, data virtualization, or API management tools, will therefore increase.

Also Read: These Technologies And Digital Trends Will Influence The Market

The post Data Strategy Trends For 2021 Everyone Need To Know appeared first on TechReviewsCorner.