#Big Data Technologies

[feathersofwares]

Big Data Technologies

Big Data Technologies are the tools and technologies used to extract and analyze information from large, complex sets of data.

It is used in applications like Business Intelligence, Predictive Analytics, Data Mining, and Machine Learning and AI. Feather Softwares helps businesses attract attention from their ideal audience online. We design user-friendly websites that create a positive impression on customers, improving brand reputation. We also optimize the websites for search results, ensuring customers interested in the business’s offerings discover them easily. Feather Softwares offers internships for students who want to start a career in Web Development, Digital Marketing, and Software Programming.

For Business Enquiries- https://formfacade.com/sm/xvjfh3dkM For Course Enquiries - https://formfacade.com/sm/RD0FNS_ut

[techtoio]

The Impact of Big Data Analytics on Business Decisions

Introduction

Big data analytics has transformed the way of doing business, deciding, and strategizing for future actions. One can harness vast reams of data to extract insights that were otherwise unimaginable for increasing the efficiency, customer satisfaction, and overall profitability of a venture. We steer into an in-depth view of how big data analytics is equipping business decisions, its benefits, and some future trends shaping up in this dynamic field in this article. Read to continue

[jointhefediverse]

💫 Join the Fediverse! 💫

Greetings, fellow bloggers! We welcome you to join us in discovering, honoring, and promoting the potential future of social networking—commonly referred to as the "Fediverse."

The Fediverse, or Federation Universe, refers to a collective of online platforms that utilize the web protocol known as ActivityPub, which has set a standard of excellence in regards to both protecting and respecting users' online privacies.

There's a good chance in the past few years that you've caught wind of the fedi family's critically acclaimed Mastodon; however, there are many other unique platforms worth your consideration...

✨ Where To Begin?

Conveniently enough, from the minds of brilliant independent developers, there already likely exists a Fediverse equivalent to your favorite socials. Whether it's an opinion from the critics, or from the community alike—the following popular websites are commonly associated with one another:

Friendica 🐰 = Facebook Mastodon 🐘 = Twitter Pixelfed 🐼 = Instagram PeerTube 🐙 = YouTube Lemmy 🐭 = Reddit

It's worth mentioning, too, a few other sites and forks thereof that are worthy counterparts, which be: Pleroma 🦊 & Misskey 🐱, microblogs also similar to Twitter/Mastodon. Funkwhale 🐋 is a self-hosting audio streamer, which pays homage to the once-popular GrooveShark. For power users, Hubzilla 🐨 makes a great choice (alongside Friendica) when choosing macroblogging alternatives.

✨ To Be Clear...

To address the technicalities: aside from the "definitive" Fediverse clients, we will also be incorporating any platforms that utilize ActivityPub-adjacent protocols as well. These include, but are not limited to: diaspora*; AT Protocol (Bluesky 🦋); Nostr; OStatus; Matrix; Zot; etc. We will NOT be incorporating any decentralized sites that are either questionably or proven to be unethical. (AKA: Gab has been exiled.)

✨ Why Your Privacy Matters

You may ask yourself, as we once did, "Why does protecting my online privacy truly matter?" While it may seem innocent enough on the surface, would it change your mind that it's been officially shared by former corporate media employees that data is more valuable than money to these companies? Outside of the ethical concerns surrounding these concepts, there are many other reasons why protecting your data is critical, be it: security breaches which jeopardize your financial info and risk identity theft; continuing to feed algorithms which use psychological manipulation in attempts to sell you products; the risk of spyware hacking your webcams and microphones when you least expect it; amongst countless other possibilities that can and do happen to individuals on a constant basis. We wish it could all just be written off as a conspiracy... but, with a little research, you'll swiftly realize the validity of these claims are not to be ignored any longer. The solution? Taking the decentralized route.

✨ Our Mission For This Blog

Our mission for establishing this blog includes 3 core elements:

To serve as a hub which anybody can access in order to assist themselves in either: becoming a part of the Fediverse, gaining the resources/knowledge to convince others to do the very same, and providing updates on anything Fedi-related.

We are determined to do anything within our power to prevent what the future of the Internet could become if active social users continue tossing away their data, all while technologies are advancing at faster rates with each passing year. Basically we'd prefer not to live in a cyber-Dystopia at all costs.

Tumblr (Automattic) has expressed interest in switching their servers over to ActivityPub after Musk's acquisition of then-Twitter, and are officially in the transitional process of making this happen for all of us. We're hoping our collective efforts may at some point be recognized by @staff, which in turn will encourage their efforts and stand by their decision.

With that being stated, we hope you decide to follow us here, and decide to make the shift—as it is merely the beginning. We encourage you to send us any questions you may have, any personal suggestions, or corrections on any misinformation you may come across.

From the Tender Hearts of, ✨💞 @disease & @faggotfungus 💞✨

[boymanmaletheshequel]

As we enter back into an era where technology is used primarily as a weapon against you by the United States and Russian governments, (welcome back 1980s! 😍) let’s go over some tips to consider if you are a queer, bipoc, or otherwise an “enemy from within” as trump so lovingly and hypocritically put it, to protecting your identity and privacy through the internet so that you can continue to resist this cultural shift safely and resiliently!

• stop posting identifying information on social media like your full name, place of residence, and pictures of yourself or other at risk people, and go back and delete posts in which you might’ve already.

• disable location tracking services and camera and mic access to apps, services, or websites that you know to be compromised by the influence of shady overseers, such as X, Instagram, Facebook, Google, and TikTok. I know it’s convenient to use these but it’s a MAJOR security hazard.

• Turn your phone COMPLETELY off when discussing sensitive subjects with friends or when you are making plans of resistance and gathering your communities, or when you are discussing personal feelings on such subjects with family, friends, or a doctor/therapist. Basically all mobile phones now have live mics that are constantly listening to you.

• Create a new email under a fake name if you haven’t already to use as your primary email address, in order to further protect your true identity.

• use an alternative browser like DuckDuckGo or brave in place of google, preferably with a VPN on top of it to even further secure your browsing history and to bypass potential IP blocks of websites from the government.

• if you want to watch YouTube and don’t want a recording of your watch history, log out of your account and watch that way, preferably you would just delete your account entirely but I understand why some might not want to.

• pirate content from streaming services via piracy websites, again so that your watch history can’t be used to make assumptions about you if that data were ever sold to the government.

These are obviously just some of the ways to bypass data collection and ti protect your real identity online, but there are many others I’m sure I’m not aware of. Please add to this if you can, and stay safe out there, because anything you say can and will be used against you in the future of this country. But: We have survived this kind of shit before, we can again, if we are careful. Loose lips sink ships, and that goes for the internet as well.

[kn-1013]

i know i've been on my anti-modern AU propaganda lately and it's just because i've been delving deeper into the sally face ao3 tags and i just keep finding them over and over. it's frustrating because there are a lot of really interesting concepts out there that would fit really well and make for a genuinely really interesting story in the 90s, but they get thrown off because the author doesn't know enough about the 90s to write for that time period, so they make it into a modern au instead. there's nothing inherently wrong with that, and i think there's room for modern aus to be done well here, i even have my own half-serious modern au, but i do think you often lose part of what makes sally face special when you turn the story into any other kind of contemporary love story/horror story/etc where all the characters just have ~iphones~ and use ~snapchat~ and all these things.

like, the 90s was not some kind of alien planet, and a vast number of the problems that you're solving with smartphones can be worked around very easily with just a bit of research or thought. long distance walkie-talkies, pagers, and PDAs were all (though sometimes expensive) perfectly capable contemporary technologies for talking to people when you are not physically with them. in fact, a lot of the abbreviations and slang we use over text right now was developed by young people in the 90s using pagers to talk to their friends. PDAs were a bit more out there in the 90s than they were in the aughts, but it's still completely plausible for henry in particular to have one, considering he already owns a home computer, which was not at all ubiquitous in the 90s. considering the apparent financial limitations that he and sal live under (it's never stated explicitly, but i mean, they live at addison's, they can't be in a great financial situation) and how insanely expensive computers were back then, it's more than likely that henry's job requires a home computer of some sort, meaning that a PDA would probably be incredibly useful to him if he were away from it, because there's no way in hell he's getting himself a luggable or another kind of early laptop to bring with him, that would've been too expensive.

and that's ignoring the fact that so many situations where two characters are apart form each other but need to communicate could just be fixed by rewriting the plot so that they can meet in person. i know that's not what people wanna hear because rewriting sucks, but you can find a lot of reasons for characters to meet each other randomly or to have reasons to meet up later if you give it a bit of problem-solving. part of what makes the pre-smartphone era interesting to write for and so optimized for horror, and probably a big reason that gabry chose this time period for the story in the first place, is the level of disconnection between each character in the story BECAUSE they don't have things like smartphones. having to work around this technological limitation is part of the fun, because you get a very enjoyable push and pull of closeness vs. disconnection between each character.

this is great for alienating ash, the only one who doesn't live in the apartments (except for neil), and causing her internal conflict about her relationships with the rest of her friends, especially as the story progresses and they start discovering more shit about the cult, and her instincts are to call the cops because she's a lot more normal than her friends are. or, it's good for alienating travis, who also doesn't live there and is far more isolated than everyone else (more on that next), or for creating an unhealthy and codependent relationship between sal and larry, who, with the walkies, are the only two in the friend group who DO have semi-instant access to each other all the time--all of which are plot points i put into my writing.

and if that's not enough, think about the implications for travis's character in particular. his father is a preacher, and a huge talking point of christian extremists in the 90s was that things like television were evil and demonic in some way. they campaigned against these things heavily. with the kind of person that we know kenneth phelps to be and the way many technologies we take for granted today, including TVs, were still being adopted by older generations, it's not out of the question at all that travis doesn't own something like a TV or a VCR, putting him even more out of the loop with what other people his age are doing than he already would be, having approximately 0 friends. he doesn't know what DND is, and he doesn't know how to look it up because he's not familiar with computers or the internet, he just knows his dad thinks it's demonic, so he steers clear of it.

the intention of cult leaders like kenneth is to keep their victims as isolated as possible, and not owning a TV, VCR, home computer, etc, is a great way to keep travis and his sisters isolated and disconnected from their peers, and therefore more connected to the cult, and it's a lot easier to justify not owning these things in the 90s, where the story already takes place, than it is if you're writing a modern au. a modern au for this situation would require all kinds of technological workarounds to make sure that travis owned a phone but couldn't do anything his father didn't want him doing on it. he's the kind of father who would go through and monitor his kid's texts, he wouldn't just let travis have snapchat or whatever, but i digress.

i know i'm just doing my petty bitching and people can do whatever they want however they want to, but i really do feel like there's a huge piece of the story that is lost in turning the sally face story as it is into some kind of modern au, and it's pretty unfortunate to me that people seem to think that the 90s was such a primitive alien world of incomprehensible technology that they don't want to write for that time period at all. it's really not as terrifying as it seems, genuinely. a surface level understanding of the era's technologies would be straightforward enough for anyone who wasn't there to write something perfectly coherent, if lacking in specific cultural/technological details that nobody but me cares about because i have autism.

if you're a sally face fan reading this and you struggle with writing for the american 90s because you weren't there, go look up pagers (also called beepers) and PDAs (which are basically early pocket computers) and how they work. ask older family members if or how they used them. go look at the different kinds of home computers of the era from companies like packard-bell and IBM. learn what a pentium III is/was, or what it means to be X86 compatible. look at the history of the CD-ROM, and how when it was invented, it could contain so much data that consumers had absolutely no idea what to do with them until people started putting video games on them. go watch cathode ray dude, LGR or techmoan on youtube.

go learn things about this era, it's good for you and you will have a lot of fun, even if you're not like me, i promise, and your fanfiction will be better for it. please learn about this era. take my hand. we can go to beautiful places together.

[shrinkrants]

The technological society… will not be a universal concentration camp, for it will be guilty of no atrocity. It will not seem insane, for everything will be ordered, and the stains of human passion will be lost amid the chromium gleam. We shall have nothing more to lose, and nothing to win. Our deepest instincts and our most secret passions will be analyzed, published, and exploited. We shall be rewarded with everything our hearts ever desired. And the supreme luxury of the society of technical necessity will be to grant the bonus of useless revolt and of an acquiescent smile. (p. 427)

This sharp paragraph was not written in the 1990s, nor in the 2010s, nor in recent years. It appeared in French sociologist and philosopher Jacques Ellul’s treatise The Technological Society, originally published in 1954 and translated into English with Robert Merton’s introduction in 1964. Ellul was concerned with the emergence of a technological tyranny over humanity and the totality of efficiency, and in this classic book he masterly elaborated on these substantial issues. Quite a few claimed 70 years ago and even decades later that Ellul was too provocative, that he overstated and exaggerated. Rereading his significant and penetrating observations in the current age evokes different thoughts and reactions. What is certain is that we are only at the beginning of this age. So is it possible that even we are far from understanding the essence of Ellul’s alerting words?

To reflect more on this crucial topic dive into these insightful books for which Ellul’s The Technological Society laid the groundwork: — Beer, David. 2019. The Social Power of Algorithms. Routledge. — Fisher, Eran. 2022. Algorithms and Subjectivity: The Subversion of Critical Knowledge. Routledge — Fisher, Max. 2022. The Chaos Machine: The Inside Story of How Social Media Rewired Our Minds and Our World. Little, Brown and Company. — Schwarz, Ori. 2021. Sociological Theory for Digital Society: The Codes that Bind us Together. John Wiley & Sons. — Zuboff, Shoshana. 2018. The Age of Surveillance Capitalism. Profile Books

[affairsmastery]

A sudden blackout risk looms over America’s power grid as massive data centers consume energy at an alarming rate. In Virginia’s Data Center Alley, home to 200+ data hubs, 60 facilities abruptly disconnected last summer, causing a surge in excess electricity. This unexpected shift forced grid operators to scramble, averting potential cascading power outages.

With data demand tripling in the last decade—and poised to triple again—energy regulators now face a new grid vulnerability: large-scale, unannounced data center shutdowns. As AI and crypto mining expand, experts warn that our power infrastructure isn’t ready for this growing challenge.

[womaneng]

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Hey there! 🚀 Becoming a data analyst is an awesome journey! Here’s a roadmap for you:

1. Start with the Basics 📚:

- Dive into the basics of data analysis and statistics. 📊

- Platforms like Learnbay (Data Analytics Certification Program For Non-Tech Professionals), Edx, and Intellipaat offer fantastic courses. Check them out! 🎓

2. Master Excel 📈:

- Excel is your best friend! Learn to crunch numbers and create killer spreadsheets. 📊🔢

3. Get Hands-on with Tools 🛠️:

- Familiarize yourself with data analysis tools like SQL, Python, and R. Pluralsight has some great courses to level up your skills! 🐍📊

4. Data Visualization 📊:

- Learn to tell a story with your data. Tools like Tableau and Power BI can be game-changers! 📈📉

5. Build a Solid Foundation 🏗️:

- Understand databases, data cleaning, and data wrangling. It’s the backbone of effective analysis! 💪🔍

6. Machine Learning Basics 🤖:

- Get a taste of machine learning concepts. It’s not mandatory but can be a huge plus! 🤓🤖

7. Projects, Projects, Projects! 🚀:

- Apply your skills to real-world projects. It’s the best way to learn and showcase your abilities! 🌐💻

8. Networking is Key 👥:

- Connect with fellow data enthusiasts on LinkedIn, attend meetups, and join relevant communities. Networking opens doors! 🌐👋

9. Certifications 📜:

- Consider getting certified. It adds credibility to your profile. 🎓💼

10. Stay Updated 🔄:

- The data world evolves fast. Keep learning and stay up-to-date with the latest trends and technologies. 📆🚀

. . .

[techsikhm]

[bluedenebii]

as a young afab queer person going into computer/data science, it makes me so sad that the face of the tech industry is a largely misogynistic homophobic transphobic trump-suck-up unethical billionaire bro club like musk, bezos, and zuckerberg. like, computers and the internet have limitless potential, but we’re using it for this????

i cannot wait until all these dipshits get what’s coming to them so a new generation of leaders can rise up and make tech kind.

[cozidreamsreimagine]

Is Your Phone Listening to You? (Probably.) 🤨

Okay, how many times have you talked about something random, like, say, Victorian doorknobs, and then BAM! Your phone's suddenly showing you ads for antique hardware? 🧐 Yeah, it's creepy AF. But is your phone actually listening to you? Short answer: probably.

The Data Minefield

Look, we all know those "free" apps aren't actually free. You're paying with your data, babe. And that data includes, yep, your voice. Companies use this info to target ads, and while they claim they're not recording your every word, it sure feels that way sometimes, doesn't it?

Fight Back Against the Algorithm

So, what can you do? Well, you can ditch your smartphone and live off the grid (tempting, tbh). Or, you can be a little more mindful of the apps you use, check your privacy settings, and maybe, just maybe, have those weird conversations about Victorian doorknobs in person. Just sayin'. 😉

Want to add some personality to your tech while you ponder the mysteries of the digital age? Head over to my shop for some cool designs that'll make your phone (and you) look fly. 😎

[uthra-krish]

Exploring Data Science Tools: My Adventures with Python, R, and More

Welcome to my data science journey! In this blog post, I'm excited to take you on a captivating adventure through the world of data science tools. We'll explore the significance of choosing the right tools and how they've shaped my path in this thrilling field.

Choosing the right tools in data science is akin to a chef selecting the finest ingredients for a culinary masterpiece. Each tool has its unique flavor and purpose, and understanding their nuances is key to becoming a proficient data scientist.

I. The Quest for the Right Tool

My journey began with confusion and curiosity. The world of data science tools was vast and intimidating. I questioned which programming language would be my trusted companion on this expedition. The importance of selecting the right tool soon became evident.

I embarked on a research quest, delving deep into the features and capabilities of various tools. Python and R emerged as the frontrunners, each with its strengths and applications. These two contenders became the focus of my data science adventures.

II. Python: The Swiss Army Knife of Data Science

Python, often hailed as the Swiss Army Knife of data science, stood out for its versatility and widespread popularity. Its extensive library ecosystem, including NumPy for numerical computing, pandas for data manipulation, and Matplotlib for data visualization, made it a compelling choice.

My first experiences with Python were both thrilling and challenging. I dove into coding, faced syntax errors, and wrestled with data structures. But with each obstacle, I discovered new capabilities and expanded my skill set.

III. R: The Statistical Powerhouse

In the world of statistics, R shines as a powerhouse. Its statistical packages like dplyr for data manipulation and ggplot2 for data visualization are renowned for their efficacy. As I ventured into R, I found myself immersed in a world of statistical analysis and data exploration.

My journey with R included memorable encounters with data sets, where I unearthed hidden insights and crafted beautiful visualizations. The statistical prowess of R truly left an indelible mark on my data science adventure.

IV. Beyond Python and R: Exploring Specialized Tools

While Python and R were my primary companions, I couldn't resist exploring specialized tools and programming languages that catered to specific niches in data science. These tools offered unique features and advantages that added depth to my skill set.

For instance, tools like SQL allowed me to delve into database management and querying, while Scala opened doors to big data analytics. Each tool found its place in my toolkit, serving as a valuable asset in different scenarios.

V. The Learning Curve: Challenges and Rewards

The path I took wasn't without its share of difficulties. Learning Python, R, and specialized tools presented a steep learning curve. Debugging code, grasping complex algorithms, and troubleshooting errors were all part of the process.

However, these challenges brought about incredible rewards. With persistence and dedication, I overcame obstacles, gained a profound understanding of data science, and felt a growing sense of achievement and empowerment.

VI. Leveraging Python and R Together

One of the most exciting revelations in my journey was discovering the synergy between Python and R. These two languages, once considered competitors, complemented each other beautifully.

I began integrating Python and R seamlessly into my data science workflow. Python's data manipulation capabilities combined with R's statistical prowess proved to be a winning combination. Together, they enabled me to tackle diverse data science tasks effectively.

VII. Tips for Beginners

For fellow data science enthusiasts beginning their own journeys, I offer some valuable tips:

Embrace curiosity and stay open to learning.

Work on practical projects while engaging in frequent coding practice.

Explore data science courses and resources to enhance your skills.

Seek guidance from mentors and engage with the data science community.

Remember that the journey is continuous—there's always more to learn and discover.

My adventures with Python, R, and various data science tools have been transformative. I've learned that choosing the right tool for the job is crucial, but versatility and adaptability are equally important traits for a data scientist.

As I summarize my expedition, I emphasize the significance of selecting tools that align with your project requirements and objectives. Each tool has a unique role to play, and mastering them unlocks endless possibilities in the world of data science.

I encourage you to embark on your own tool exploration journey in data science. Embrace the challenges, relish the rewards, and remember that the adventure is ongoing. May your path in data science be as exhilarating and fulfilling as mine has been.

Happy data exploring!

[techdriveplay]

Why Quantum Computing Will Change the Tech Landscape

The technology industry has seen significant advancements over the past few decades, but nothing quite as transformative as quantum computing promises to be. Why Quantum Computing Will Change the Tech Landscape is not just a matter of speculation; it’s grounded in the science of how we compute and the immense potential of quantum mechanics to revolutionise various sectors. As traditional…

[lbhslefttiddie]

I haven’t seen you around much here lately, so I just wanted to say I hope you’re doing well ^^ . If you have any life challenges going on right now, I believe in you to conquer them!!!

thank you!!! the life challenges is my phone and computer both had a stroke and died within a month of each other 😔 it was super cursed but im cool im being very brave about it

[dhivyakrishnan107667]

From Beginner to Pro: A Game-Changing Big Data Analytics Course

Are you fascinated by the vast potential of big data analytics? Do you want to unlock its power and become a proficient professional in this rapidly evolving field? Look no further! In this article, we will take you on a journey to traverse the path from being a beginner to becoming a pro in big data analytics. We will guide you through a game-changing course designed to provide you with the necessary information and education to master the art of analyzing and deriving valuable insights from large and complex data sets.

Step 1: Understanding the Basics of Big Data Analytics

Before diving into the intricacies of big data analytics, it is crucial to grasp its fundamental concepts and methodologies. A solid foundation in the basics will empower you to navigate through the complexities of this domain with confidence. In this initial phase of the course, you will learn:

The definition and characteristics of big data

The importance and impact of big data analytics in various industries

The key components and architecture of a big data analytics system

The different types of data and their relevance in analytics

The ethical considerations and challenges associated with big data analytics

By comprehending these key concepts, you will be equipped with the essential knowledge needed to kickstart your journey towards proficiency.

Step 2: Mastering Data Collection and Storage Techniques

Once you have a firm grasp on the basics, it's time to dive deeper and explore the art of collecting and storing big data effectively. In this phase of the course, you will delve into:

Data acquisition strategies, including batch processing and real-time streaming

Techniques for data cleansing, preprocessing, and transformation to ensure data quality and consistency

Storage technologies, such as Hadoop Distributed File System (HDFS) and NoSQL databases, and their suitability for different types of data

Understanding data governance, privacy, and security measures to handle sensitive data in compliance with regulations

By honing these skills, you will be well-prepared to handle large and diverse data sets efficiently, which is a crucial step towards becoming a pro in big data analytics.

Step 3: Exploring Advanced Data Analysis Techniques

Now that you have developed a solid foundation and acquired the necessary skills for data collection and storage, it's time to unleash the power of advanced data analysis techniques. In this phase of the course, you will dive into:

Statistical analysis methods, including hypothesis testing, regression analysis, and cluster analysis, to uncover patterns and relationships within data

Machine learning algorithms, such as decision trees, random forests, and neural networks, for predictive modeling and pattern recognition

Natural Language Processing (NLP) techniques to analyze and derive insights from unstructured text data

Data visualization techniques, ranging from basic charts to interactive dashboards, to effectively communicate data-driven insights

By mastering these advanced techniques, you will be able to extract meaningful insights and actionable recommendations from complex data sets, transforming you into a true big data analytics professional.

Step 4: Real-world Applications and Case Studies

To solidify your learning and gain practical experience, it is crucial to apply your newfound knowledge in real-world scenarios. In this final phase of the course, you will:

Explore various industry-specific case studies, showcasing how big data analytics has revolutionized sectors like healthcare, finance, marketing, and cybersecurity

Work on hands-on projects, where you will solve data-driven problems by applying the techniques and methodologies learned throughout the course

Collaborate with peers and industry experts through interactive discussions and forums to exchange insights and best practices

Stay updated with the latest trends and advancements in big data analytics, ensuring your knowledge remains up-to-date in this rapidly evolving field

By immersing yourself in practical applications and real-world challenges, you will not only gain valuable experience but also hone your problem-solving skills, making you a well-rounded big data analytics professional.

Through a comprehensive and game-changing course at ACTE institute, you can gain the necessary information and education to navigate the complexities of this field. By understanding the basics, mastering data collection and storage techniques, exploring advanced data analysis methods, and applying your knowledge in real-world scenarios, you have transformed into a proficient professional capable of extracting valuable insights from big data.

Remember, the world of big data analytics is ever-evolving, with new challenges and opportunities emerging each day. Stay curious, seek continuous learning, and embrace the exciting journey ahead as you unlock the limitless potential of big data analytics.

[thefreethoughtprojectcom]

A large collective and imaginative effort is needed to resist data colonialism’s new injustices. This effort is a crucial step on the longer journey to confronting and reversing colonialism itself.

Read More: https://thefreethoughtproject.com/be-the-change/ai-companies-want-to-colonize-our-data-heres-how-we-stop-them

#TheFreeThoughtProject #TFTP