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This article was published as a part of the Data Science Blogathon

Introduction

Have you ever been in a scenario where you’ve created many models to solve a problem, all of which have about the same value for certain scoring matrices, and you’re not sure which one to use? When I was working on a similar issue, I came across one library that made the entire model selection procedure considerably quicker and faster.

Yes! I am talking about “YellowBrick”.

The outcomes of machine learning models may be visualized to assist make better decisions about which model to use. It also speeds up the procedure. In this article, I’ll explain how this machine learning library comes in helpful for the below few tasks and saves time.

Visualizing feature importance and selecting features

Interpret score of models

Visualize model Results to get a better understanding

Hyperparameter tuning

Model selections

Let’s learn how to use this library for visualizing these tasks for a Linear regression problem.

Installation

Yellobrick is based on scikit-learn and matplotlib. We must first install those libraries before proceeding with the Yellowbrick installation.

We may use the instructions below to install all three, or if you already have the first two, just execute the third one.

pip install scikit-learn

pip install matplotlib

pip install yellowbrick

Data Loading and Preprocessing

I’m going to utilize a dataset that predicts housing prices. The data collection includes both numerical and category variables.

I have performed all of the pre-processing steps after importing the dataset, including exploratory data analysis, adding new derived columns, and encoding categorical columns. I’m not going to go through all of these processes because we’re concentrating on the Yellowbrick for visualization.

You can always look at my git repository to grab the dataset we are using here and learn about the entire process, from data preprocessing through model building.

Visualizing

 Residuals

After creating a linear regression model, it’s usually a good idea to look at the residual plot to see if our model is good enough and it holds assumptions we made while building the model.

The ResidualsPlot Visualizer from Yellowbrick shows the difference between residuals (Observed value of target variable – predicted value ) on the Y (vertical) axis and the dependent variable on the X (horizontal) axis.



visualizer.fit(X_train, y_train)

# Generates predicted target values on test data visualizer.score(X_test, y_test) #show plot and save it at given path visualizer.show("Residual_lasso.jpg")

The fact that residuals are scattered randomly across the horizontal axis indicates that the linear model is adequate for the data. If there is a pattern in the residuals, we may conclude that the linear model is not the best option and that a non-linear model is required.

Distribution of Residuals 

On the right-hand side, we can see the error distribution, which is normally distributed with a mean of 0. This is true for linear models’ assumptions.

Now we will tune the hyperparameter and visualize the process using Yellowbrick.

Hyperparameter Tuning

We have alpha as a hyperparameter to tune in Lasso, which is a constant that multiplies the regression term. The model is less complicated (reduces overfitting) if the alpha value is big, but we can’t use a very big value of alpha because it will make our model underfit and extremely simple.

That’s why selecting the optimal value of alpha is important.

Let’s look at how different alpha values affect model selection during the regularization of linear models. If the plot is random then we can say that the regularization we are using is not suitable.

We can use the below code to visualize hyperparameter tuning for alpha:

from yellowbrick.regressor.alphas import alphas # quick method to immediately show plot alphas(LassoCV(random_state=0), X_train, y_train) Visualizing Prediction

Yellowbrick allows us to visualize a plot of actual target values vs predicted values generated by the model with relatively few lines of code and saves a significant amount of time. It also aids in detecting noise along with the target variable and determining the model’s variance.

We can use the below code to visualize prediction error using PredictionError from Yellowbrick.

from yellowbrick.regressor import PredictionError # Instantiate the linear model and visualizer Lm = Lasso() visualizer = PredictionError(Lm) # fit visualizer on training data visualizer.fit(X_train, y_train) #Evaluate on test data visualizer.score(X_test, y_test) #show the plot and save in given path visualizer.show("prediction_error.jpg")

Feature importance

Many model forms like the random forest, gradient boosting, etc. describe the underlying impact of features relative to each other. But Generalized linear models predict the target via a linear combination of input features.

For models that do not support a feature_importances attribute, Yellowbrick’s FeatureImportances Visualizer will also draw a bar plot for the coef_ attribute that linear models provide. When using such models, we can set relative= False to plot the magnitude of coefficients(coefficients may be negative).

Let’s Visualize coef_ plot of features using the below code:

from yellowbrick.model_selection import FeatureImportances viz = FeatureImportances(lasso2,relative=False) #fit on train dataset viz.fit(X_train, y_train) #show plot and save at output path viz.show("feature_importance.jpg")

Larger coefficients are necessary “more informative” because they contribute a greater weight to the final prediction in most cases. This cool plot can help us compare models on the ranking of features.

Yellowbrick also has a lot of nice tools for viewing classification models and feature analysis findings. We’ll go through this in more detail in the upcoming post, but in the meanwhile, you can learn more about Yellowbrick from its documentation.

Conclusion

I attempted to demonstrate how we can utilize Yellowbrick to visualize hyperparameter tweaking, model selection, and feature selection to aid in the interpretation of our model’s findings.

Also, I had a lot of fun using Yellowbrick, and it also helped me save a lot of time and make better decisions. I hope it will be useful to you as well.

You can always have a look at all the code from this article here.

Happy Learning!

The media shown in this article are not owned by Analytics Vidhya and are used at the Author’s discretion.

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4 Virtualization Predictions For 2009

As 2008 draws to a close, virtualization remains one of the few bright spots in a year mired in financial debacles, a deepening recession and credit crisis that doesn’t seem to be going away any time soon. Virtualization has become a shelter of sorts in the rapidly brewing storm of economic uncertainty.

In 2008, virtualization seemed to have an unstoppable boom of its own. It has, for all intents and purposes, moved into “killer app” territory. This is unprecedented given that x86 virtualization is barely out of its infancy. In 2007, it went from being a technology vendors needed to explain to enterprises and sell them on, on to a technology everyone asked for. In 2008, however, virtualization became a technology whose capabilities were expected from the chip level on upward. It helped, of course, that Microsoft got behind virtualization with its release of Hyper-V in late June.

So what will 2009 bring? Will virtualization be able to maintain its location within the eye of the growing economic storm? Perhaps, but that doesn’t mean the winds of change won’t blow it around. That’s already begun.

Nowhere was VMware’s view of itself more clear than at this year’s VMworld in Las Vegas. From the vendor’s end-to-end roadmap of what it foresaw for data center to the way it facilitated the show, the message was clear: We are VMware and we are king.

However, as its message that “Virtually Anything Is Possible” was being broadcast through the Venetian Resort-Hotel-Casino and beyond, another message was being heard. The sound of Lehman Brothers crumbling. And then AIG spinning, followed by Merrill Lynch being bought in a fire sale.

And it’s not just market forces making life difficult for VMware. While the self-proclaimed monarch was busy planning its coronation, another self-proclaimed ruler was releasing the results of its vision, and that vision is free.

Hyper-V landed on the scene after a few months of delay. Hyper-V at this point is only a hypervisor, but it’s an integral part of Windows Server 2008, and it’s basically free.

And when Wall Street, Main Street and everything in between is melting down, free is good. Especially if the product is good-enough and it’s got Microsoft behind it.

Financial institutions are typically the early adopters for emerging technologies. They are willing to pay big bucks for products that deliver a return on investment of bigger bucks. With budgets frozen or contracting, and a free product on hand, it will be VMware, not virtualization, that will be in question.

Thus, in 2009, VMware will likely have to work even harder to maintain its lead. At present it has about a 40 percent share, the largest by far of any vendor. With the market still largely untapped, it’s sure to lose at least some ground to Microsoft.

Another sign of Microsoft’s expanding presence is from the ISVs that are developing products for Hyper-V as well as VMware ESX. In the past, ESX was the baseline. Now ISVs are either releasing products compatible with both, akin to Windows and Linux editions, or prioritizing Hyper-V right behind ESX.

VMware will also face increased competition at the other end of the spectrum. CA, Oracle and Symantec have a multitude of products, many of which compete directly with VMware’s offering. VMware’s end-to-end plan, puts it directly in the these players’ arena. There will be blood. There will be consolidation.

Doing anything on the basis of “as cheap as possible” always has ramifications, and virtualization is no exception.

For some time analysts have predicted a security breach would bring the public’s attitude toward virtualization back down to earth. Surprisingly, that has not yet happened. As the number of virtual deployments increases, however, so does the likelihood. Especially given the current economic climate, where many enterprises are thinking in terms of short-term savings and virtualizing without proper process.

It may be a perennial prediction at this point, but with as companies virtualize as quickly as they can to save money on equipment, mistakes will be made. These mistakes will range from virtual machine sprawl to wrongly provisioned hardware (most likely resulting in downtime) to gaping security holes.

Expect to read about some horror stories. To avoid becoming a case study for one, plan properly and don’t cut corners, especially when it comes to security.

Amazon’s cloud is just the beginning. IBM has a cloud initiative in the works, and expect to see many more in 2009. For some enterprises, building an internal cloud will be the way to go.

Cloud computing isn’t terribly new. The concept goes back several decades and has gone by a multitude of names, including utility computing and supercomputing. Its present incarnation has been gaining in popularity for about two years now.

Hosting providers, however, are well-situated to reposition themselves to offer clouds. Expect to see a lot of noise around that.

Not every application is suitable for the cloud, but not every app is suitable for virtualization. In general, mission-critical apps should not be put in a cloud, at least not initially — unless you’re willing to bet the business on them.

The excitement has long left the PC vs. Mac arena. In 2009, it will be all about Blackberry vs. iPhone. Successful data centers will take this into consideration, and when planning their virtual deployments, will look beyond traditional clients. Netbooks and smartphones will be increasingly sought after in the server room next year chiefly because of their price and flexibility.

Consumer devices are finding their way in through the back door, and enterprises that figure out a way to leverage them securely will have the upper hand in terms of both virtualization and general infrastructure management.

Amy Newman is the managing editor of ServerWatch. She has been covering virtualization since 2001.

This article was first published on chúng tôi

7 Predictions For Open Source In 2011

Predictions for the upcoming year are always plentiful in December, and this year is no exception. On PCWorld, for example, we’ve seen security predictions, enterprise resoure software (ERP) predictions, and general IT forecasts for 2011.

What I haven’t seen so far, however, are predictions for Linux and other open-source software. Lest that category of technology go “unpredicted,” allow me to venture these thoughts.

1. Android, Android, Android

This feels like a no-brainer at this point, but Android is clearly going to continue on its upward path throughout 2011. Holding nearly a quarter of the smartphone market in October, it’s widely expected to become the number-one mobile operating platform in the world in the next few years; I predict that will happen sooner rather than later, possibly even by the end of next year.

iPhones, meanwhile, will increasingly be a niche choice among a relatively small set of Apple fanatics, much the way Macs are, while Windows Phone 7 will be declared a flop.

2. Again, on Tablets

Android is going to give Apple a serious run for its money in the tablet arena as well, mirroring to a slightly less dramatic extent its rapid ascendancy on smartphones. I’ve lost count of just how many Android tablets are expected in the coming months, but there’s no way the solitary iPad can continue to dominate in the face of such diverse choice.

3. Ubuntu and Linux

Ubuntu is going to continue the strides it made this year and finally give Linux some of the brand recognition it needs on the desktop and maybe some mobile devices as well, making it a serious contender in the mainstream, even among non-technical consumers.

In particular, the combination of the new Unity interface and the Wayland graphics system promise to make upcoming Ubuntu versions what may be considered the first true “Linux for the masses.” Canonical’s research and development in such areas as context-aware computing, meanwhile, could push it ahead even further, and its debut on the tablet will give it a whole new arena to compete in.

In short, I predict big things for Ubuntu next year, even as Linux continues strong on servers and as Windows continues to fade in a cloud of malware.

4. Dual-Booting

Along with these relatively new contenders in the operating system arena and the increasingly blurred lines that separate form factors, I think we’re going to see an increasing number of devices sold with two operating systems. More often than not, at least one of those will be based on Linux.

One of the first things people did to Google’s Chrome-based CR-48, for example, was to install Ubuntu on it, and we’ve already seen tablets from the likes of Acer and Augen offering the dual-boot option too.

Choice is always a good thing, and I believe manufacturers will increasingly recognize that in their operating system decisions.

5. More Open Drivers

This year saw the announcement of Broadcom’s new open source wireless driver, and it also saw the debut of an open source driver for AMD’s Ontario Fusion chip. As Linux becomes increasingly mainstream, this is a trend that will continue. No manufacturer wants to exclude an increasingly significant market.

6. ARM

With mobile devices expected to outpace PCs in the next 18 months, the low-power, open source-friendly ARM architecture will continue to shine. Microsoft and Intel may both now be trying to catch up in this arena, but such efforts promise to be too little, too late.

I predict that ARM chips will become commonplace in PCs and even servers as well, particularly given the growing popularity of Ubuntu and other Linux distributions, which don’t require the expensive horsepower that Windows does.

7. Oracle and OpenOffice.org

Oracle had a very bad year in 2010 when it comes to open source, making it clear that it has no desire to play any role that doesn’t involve significant profit. In addition to suing Google over Java, the company has pulled the plug on OpenSolaris, caused the launch of numerous forks, precipitated the Apache Software Foundation’s resignation from the Java SE/EE Executive Committee, and targeted the Hudson project with more ownership claims.

OpenOffice.org, of course, is one of the projects that has now been forked, and I’m betting that the result–LibreOffice–is going to take over in the open source productivity software world. Many Linux distributions have already pledged to include it instead of OpenOffice, and the Document Foundation has exciting plans.

Oracle, meanwhile, will stick to lawsuits and price increases.

Will my predictions hold true? Time will tell. Meanwhile, what do you expect to see happen in the world of open source next year?

Follow Katherine Noyes on Twitter: @Noyesk.

What Is Next For Xrp? Predictions & Alternatives

The crypto market has been struggling heavily this year but with Q3 ending, we are able to see a slight growth for some of them. One of them is XRP.

With the mild corrections in the last few days, XRP is still showing signs of growth in the last month. What can we expect in the next 90 days? It’s left to see. With that being said, let’s just mention a few of the hot coins you should invest in. For example, there’s a disruptor within the crypto trade platforms market –  D2T, so check it out.  Then we’ve got a P2E hot stuff, RIA. Also, if you’re into green investments, you should definitely try  IMPT. We’ve even got one that has successfully completed its presale phase and it is heading towards its ICO, and it is called – TAMA! 

So, what’s up with XRP? 

Market collapse has affected everything and everybody – that doesn’t exclude Ripple (XRP). Coming back strongly from the fall, XRP had a strong last month, climbing up to $0.5.

On the other hand, we’ve witnessed a slight adjustment in the last few days with XRP plummeting to $0.44. Is this downtrend here to stay or is it just temporarily?

Ripple(XRP) Price Prediction For Q4 2023

Let’s pretend the third quarter is a turning point for the XRP price and that it continues to rise. After a choppy year, it may finish at its all-time high of $0.6. However, if more delays or motions are found in the litigation, the price might end the day’s trading at $0.38. Price would settle at about $0.45 if normal buying and selling forces were in play.

XRP alternatives

With these ‘slippery’ predictions, it’s important to be smart and careful. Now, more than ever it is important to choose your battles but more importantly  – diversify.  So, what coins besides the stable coins should you focus on? Let us suggest a few. They’re hot, they’re hype and they’ve had a fast start in the last quarter.

DASH 2 TRADE (D2T)

Dash 2 Trade is a world class crypto analytics and social trading platform that makes it easier for investors to make informed decisions. 

Dash 2 Trade is launching the taxless D2T token to support an informed trading analytics platform providing crypto traders with in-depth market insights to help create market-beating strategies. The Dash 2 Trade platform allows users to access signals, metrics and social trading tools for every type of trader. With the actionable insights powered by the D2T ecosystem, a trader can identify and analyze underlying factors that influence the price of cryptocurrencies.

The Dash 2 Trade analytics dashboard operates on top of the Ethereum blockchain. The native digital asset of the project is the D2T token, which complies with the ERC-20 standard. D2T is a utility token that offers its holders a full range of benefits, such as access to the Dash 2 Trade terminal and all of the features previously discussed. The total supply of D2T is 1 billion tokens.

They’ve raised $1,000,000 in First 3 Days of Presal, so hurry up and invest early!

IMPT.io (IMPT)

IMPT.io connects users with hundreds of impactful environmental projects around the world with the purpose to reduce carbon emissions and help our planet. chúng tôi also engages thousands of the largest retail brands that allocate a specific percentage of sale margin for environmental projects. 

This token relies on blockchain technology — the immutable ledger that facilitates the process of recording transactions and tracking assets in a business network. It is an efficient solution that can solve the current carbon offset challenges.

Through a fully blockchain-based system, IMPT is adding significant transparency and security to the carbon offsets market, which until this time has been fraught with fraud and uncertainty. And with so many countries around the world working to Net Zero emissions, the value of carbon credits is only going to rise substantially over the next few years.

We haven’t seen anything like this and we strongly recommend considering this crypto as an investment opportunity.

CALVARIA (RIA)

Calvaria is a project centered around speeding up the mass adoption of crypto through a play-to-earn battle card game. The project’s mission is to create the first effective ambassador between the “real world” and crypto, achieved by creating a fun and accessible game, available on both mobile app stores and PC’s.

The game is designed in such a way that each player can truly own the in-game resources. They can earn these either through playing or investing in the game’s ecosystem. All of this is made possible by blockchain technology, which gives players true digital ownership.

The total maximum fixed supply of the $RIA token is 1,000,000,000 units. Below is a summary of the proposed distribution.

Tamadoge  (TAMA)

Tamadoge has made its first appearance on a top-tier crypto exchange OKX. The date has been set for the 27th of September, and it was the first listing for the newest meme coin on the markets. The official TamaDoge presale was a huge success, as the platform sold all 1 billion tokens months ahead of schedule.

If you missed the TAMA token presale, you can still get your hands on these tokens by exchanging them for another cryptocurrency. The tokens have already gained over 500%, but since this is the first official listing, their current price is the lowest it will be moving forward. So visit OKX and be one of the first users to exchange your tokens for TAMA on their CEX exchange. If you can’t complete the transaction, you can use OKX’s DEX listing as an alternative.

Should you choose alternative coins or stick to stable coins such as XRP?

Even though some analytics forecast a huge jump for XRP and others predict a fall, it’s still early to know and given its volatility, you should consider researching some new, interesting projects. 

New coins such as TAMA, RIA, and D2T offer interesting use cases while using ETH blockchain tech that make them more transparent and reliable. 

We’ve shared all the information with you so it’s left to you to do a more thorough research and make your own investment decision.

FINAL WORDS

Hope you’ve enjoyed our article. Remember, diversification is the key so you should consider investing in different interesting coins that you believe in.

Using Color Schemes For Power Bi Data Visualization

Creating a high-quality color palette for your Power BI data visualization is essential to make your reports look compelling and professional. You may watch the full video of this tutorial at the bottom of this blog.

I’m constantly seeing some reports that use a generic color palette from Power BI, which affects the visualization and representation of their insights.

I personally can’t stand these colors as they just don’t do your work any favor when engaging your consumers into your insights.

So, if you want to create great reports, you need to spend a bit more time finding a good and coherent theme that you can implement in your models.

Let’s try to use this report as an example. I’ll be showing you some of the colors that I am using in a particular report, and how I use them in combination with one another.

I used the same theme throughout my entire report. I tried to match good colors that will work together.

This report was utilized during the Enterprise DNA learning summit last May, 2023. We went through six different workshop sessions over three days, and a lot of analytical insights were discussed around how you can create really compelling Power BI reports. A big part of that was related to visualization.

Now, some of you might think that it’s quite hard to find good color combinations. During this tutorial, I’ll discuss how you can create really great and compelling color themes in your reports. I’ll run through my process and show how I create color palettes from scratch.

First of all, I’ll be showing you this Enterprise DNA Power BI Showcase page. This is where you can get some inspiration for colors.

You can also use the live demos for each report and dashboard. If you want to download all of these, you just have to upgrade to a Enterprise DNA membership. This is certainly something to consider if you really want to master Power BI visualizations and analytical techniques.

In creating color palettes, I mostly use two key websites. The first one is called Color Palette FX.

This website automatically generates palettes of color based on an image that you already have. For instance, if you have a company website, logo, or any other company-related image, we can just place it into this image box.

Then, it would automatically come up with a palette of colors based exactly on the image that you have uploaded. 

Let’s check out this image here.

The image above is the one that I used for the sample report that I previously showed. It doesn’t look exactly the same because I only chose the particular colors I wanted to use. But you can still see that there were some colors from the image which I utilized in this report.

If you want to download this resource, all you have to do is to register for the learning summit. During the summit, you will not just learn about creating compelling good reports and models in Power BI, but you’ll also be able to download this resource, and see how I’ve developed the visualization. 

Then find the file that we want to upload.

Another thing that you’ll get if you come to the learning summit is a text file. This file contains settings on how your themes need to be set up. This format is what you’ll be using so you can completely implement the color palette in your Power BI reports.

Then, you should paste it into this format from the text file.

After that, you need to turn it into a json file. You can do this by saving it with a .json file extension. Then, you may import the file after saving it. And that’s the core of what I do for color themes. I always like to start with a random image of my choice, and then use a website to generate colors from the image.

If I’m not yet satisfied with the generated palette from the previous website, I also go to this really great website called Coolors. This is also free to use. It can generate a palette of similar colors that work together.

For example, if we want to use this particular color, we just need to copy the Hex color code value.

Then, let’s paste it into this part of the Coolors website.

 And then let’s try to use this light greenish color.

Paste it again here, and make sure to lock both colors.

Finally, just press the space bar. As you’ve probably noticed, these three colors are now creating the other parts of our palette and generating different colors that we can utilize in our report.

You can now get it into your model to have this coherent color scheme that we can utilize and implement in our reports.

That’s how you implement great colors within Power BI. Primarily, I gain inspiration from an image. Then I upload that image in a web-based tool to generate the color palette for me. From generating all of these unique codes for my color palette, I then create my palette template and integrate this into Power BI.

Another important design tip: utilize good color combinations and do not overdo it.

I highly recommend working through the video to understand both my work and thought processes on how to generate great color palettes in Power BI for your own work.

For many more design and report creation tips, check out the Dashboarding & Data Visualization Intensive course module at Enterprise DNA Online.

Also, don’t forget to check out the Enterprise DNA Showcase page for more inspiration on how to set up reports in Power BI.

Enjoy working through this detailed video.

Sam

Five Data Privacy Predictions To Look Out For In 2023

Data privacy is a part of the data protection that deals with the proper handling of data

The year 2023 marks a significant concern over data management. Businesses faced severe technological challenges with growing innovations which altogether triggered the concept of data privacy. Companies had to shift to emerging technologies, and at the same time, keep a tab on International data privacy outlook will intensify The famous  Ultimately, more counties are expected to either join hands with international data privacy committees or for new laws within the country to keep a check on privacy issues. This will ease tension and move past security doubts.   The importance of transparency will increase In the age of data economy, true company value lies in the collected data assets that are worthy of protecting and keeping. However, people expect these private players to keep in mind that data is just borrowed and never be owned. Privacy laws enable individuals to exercise their rights in certain circumstances by providing the provision to take back ownership of data. Henceforth, in order to hold up data and trust, organizations need to ensure data transparency by openly communicating on what data they collect, and the purpose and uses behind it. Governments aren’t the only ones that will expect more tech companies’ privacy standards. Since people had a bitter year in experiencing multiple mobile applications being banned by the government over security reasons, commoners will also demand privacy and transparency. According to a   Security automation will take center stage The increasing furor over data security could be soothed using automation technology. The pandemic related complications have gapped the normal security checks. The only solution that organisations have in hand now is data security automation. Security automation is the machine-based execution of security actions with the power to programmatically detect, investigate and remediate cyberthreats without human intervention. The system will identify incoming threats, triaging and prioritizing alerts as they emerge. Cybersecurity will have to become more flexible as many businesses are changing the way they operate. Automating security processing using AI tools will help companies to achieve the flexibility level. Even though when security AI is at the beginning stage, it is predicted to take off on a large scale in 2023.   Security data analytics will be highly adopted Already, big data analysis is considered a data asset in many organisations. In 2023, it will become a standard practice with more companies using them to improve their data privacy measures. Data analytics could highlight operational improvements, showing companies how to better their data security performance. Major companies like Third-party assessments will become critical Consumers will be more specific of companies giving their   In a nutshell

The year 2023 marks a significant concern over data management. Businesses faced severe technological challenges with growing innovations which altogether triggered the concept of data privacy. Companies had to shift to emerging technologies, and at the same time, keep a tab on data privacy in the organization Data privacy is a part of the data protection area that deals with the proper handling of data. This includes how data should be collected, stored and shared with any third-parties, as well as compliance with the applicable privacy laws. Data privacy is not blocking data and disposing it without use, it is more about properly utilising data while protecting the privacy preferences of individuals. When companies started functioning online, people showed more concern over data privacy . The issue of privacy breach has made a significant spotlight in the news. This could lead people to adopt a safer form of data privacy policies in 2023. As the ideas and trends in data security evolve, some changes will be accelerated while others might get replaced. Working systems have to embrace the changes to run the chúng tôi famous video sharing app Tik Tok made most of the tech headlines for many days in 2023 so far. The reason behind this is the lenient data privacy norms and alleged intrusion of the Chinese government in the system. After all the issue, people are well aware of the importance of data privacy. They are valuing their personal data and denying any reason that comes behind a company’s carelessness towards data privacy. The events in 2023 might put an end to the prolonged international regulations to safeguard laymen’s private data. China has already announced new security standards and asked other countries to follow. The EU General Data Protection Regulation (GDPR) is set to become the most influential data protection legislation worldwide. Some other countries have similar data privacy laws like GDPR which protects the people’s data constitutionally.Ultimately, more counties are expected to either join hands with international data privacy committees or for new laws within the country to keep a check on privacy issues. This will ease tension and move past security chúng tôi the age of data economy, true company value lies in the collected data assets that are worthy of protecting and keeping. However, people expect these private players to keep in mind that data is just borrowed and never be owned. Privacy laws enable individuals to exercise their rights in certain circumstances by providing the provision to take back ownership of data. Henceforth, in order to hold up data and trust, organizations need to ensure data transparency by openly communicating on what data they collect, and the purpose and uses behind it. Governments aren’t the only ones that will expect more tech companies’ privacy standards. Since people had a bitter year in experiencing multiple mobile applications being banned by the government over security reasons, commoners will also demand privacy and transparency. According to a PwC Poll , 84% of consumers said they would switch services if they think a company’s data system is fragile. In 2012, companies that are transparent about how they use data will likely be more chúng tôi increasing furor over data security could be soothed using automation technology. The pandemic related complications have gapped the normal security checks. The only solution that organisations have in hand now is data security automation. Security automation is the machine-based execution of security actions with the power to programmatically detect, investigate and remediate cyberthreats without human intervention. The system will identify incoming threats, triaging and prioritizing alerts as they emerge. Cybersecurity will have to become more flexible as many businesses are changing the way they operate. Automating security processing using AI tools will help companies to achieve the flexibility level. Even though when security AI is at the beginning stage, it is predicted to take off on a large scale in 2023.Already, big data analysis is considered a data asset in many organisations. In 2023, it will become a standard practice with more companies using them to improve their data privacy measures. Data analytics could highlight operational improvements, showing companies how to better their data security performance. Major companies like Nintendo and Marriott’s experience in data breaches this year have propelled business institutions to not follow their footsteps. Ultimately, keeping all these in mind, data analytics will be a crucial step companies take in 2023.Consumers will be more specific of companies giving their data to third-party access . Businesses will be pushed to consider their third-party partners and perform more risk assessments. A survey conducted by Soha Systems on third-party risk management found that 63% of all data breaches were attributed to third-party vendors. The study also found that only 2% of respondents consider third-party access amongst their top IT priorities. Enormous third-party data breaches like General Electronics, T-mobile, Entercom, etc. have revealed the importance of not having a loose end to an alien in the system. Customers will expect businesses to hold their partners to higher standards to avoid these risks.Notable scandals in the modern tech era have put people on their heels demanding for a prominent data privacy framework . Implementing data privacy measures might initially have hurdles, disruption and confusion. But eventually, companies will find it useful and stick to the bottom line. This will take both people and companies to a data secure 2023.

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