#Ethics in Big Data Analytics

[techsoulculture]

Ethics in Big Data Analytics : Balancing Privacy 2023

In the contemporary digital era, Big Data Analytics has emerged as a revolutionary tool, enabling organizations to extract

[truetechreview]

How DeepSeek AI Revolutionizes Data Analysis

1. Introduction: The Data Analysis Crisis and AI’s Role2. What Is DeepSeek AI?3. Key Features of DeepSeek AI for Data Analysis4. How DeepSeek AI Outperforms Traditional Tools5. Real-World Applications Across Industries6. Step-by-Step: Implementing DeepSeek AI in Your Workflow7. FAQs About DeepSeek AI8. Conclusion 1. Introduction: The Data Analysis Crisis and AI’s Role Businesses today generate…

[alyfoxxxen]

How to Stop Your Data From Being Used to Train AI | WIRED

[techtoio]

Unlocking Insights: How Machine Learning Is Transforming Big Data

Introduction

Big data and machine learning are two of the most transformative technologies of our time. At TechtoIO, we delve into how machine learning is revolutionizing the way we analyze and utilize big data. From improving business processes to driving innovation, the combination of these technologies is unlocking new insights and opportunities. Read to continue

[watermelinoe]

thank you for mentioning AI!

I also have practical uses for it and cringe when other feminists are like ""if you ever TOUCH AI you belong inside SATAN'S BUTTHOLE you swine-fucking trash!!!"" lol

it drives me a little nuts but it's not a fight I want to pick tbh

i think most people think of ai as purely generative ai like chatgpt and whatever image generators but yeah "ai" has existed for a while and has lots of practical uses, especially analytical ones! fuzzy logic, used by ai systems, has been around for decades. i have a fuzzy logic rice cooker and she's my baby girl lol. i have two degrees, one in fine art and one in IT, so i think i have a balanced view... i did a presentation about the ethics of ai "art" and i emphasized all the useful applications, especially with big data, but that it should not replace our own human thinking and creativity (and should not be used to justify mass layoffs cough cough)

i did have a ton of classmates when i had a coding problem who were like just have ai write it for you and i was like.... but then i won't learn how to do it?? and that's why i like those coding assistants bc i can fall back on them if i get stuck but they don't just. do it for me.

and i don't want ai "art" at all period ever, if you couldn't be bothered to make it i can't be bothered to engage with it, it's insulting

[criticalcrusherbot]

I find it both hilarious and sad that you outsource media analysis (i.e., interaction with and interpretation of art, an inherently human act) to a machine. Say what you will about antis or haters, but at least their opinions and justifications for holding those opinions stand on their own two feet, whether they are good or well-rounded justifications or not.

"It's just helping me with writing, at least I'm not using it to generate images", I hear you say.

Counterpoint: writing is art. Expressing one's interpretation of art is also art, an extended phenotype of the artistic work itself. Congratulations, you've cheapened both the art of writing, the art of expressing one's own analytical conclusions, and by extension, you've cheapened the media itself.

I think it's also incredibly telling that while you're too proud of the initial positive reception you got from fans to admit what you're doing is wrong, the fact that you received backlash when people found out you're actually outsourcing your essay writing to chatgpt has made you de-emphasize the cutesy "bot" persona as of late.

I have no patience for you AI bros (even if you're a woman or enby, if you see using chatgpt to write essays as an appropriate form of artistic engagement, you're an AI bro), but I can only implore that you all wake up one day to how you're cynically contributing to the watering-down of human expression.

💁🏽‍♀️: I’ve said it before. I’ll say it again. This emoji (💁🏽‍♀️) means that it’s all me. No AI.

I see you’re having some big feelings. What were you hoping to achieve when you typed this out and sent it to a stranger on the internet? Could some of this visceral reaction come from a place of fear? I get it — AI’s rapid rise to prominence can feel scary, especially when it feels like a threat to human creativity and expression. Under capitalism, AI usage has definitely resulted in exploitation and job cuts, which is a valid concern. But is this due to the technology itself? Or the conditions in which it exists? What are some ways we can productively address these issues? It seems like you have chosen to boycott AI usage. That’s perfectly understandable! I just wonder if there are more effective ways to mitigate the effects of AI, which seems to be the heart of what we’re both concerned with.

As condescending and accusatory as your ask is, I still think the AI discussion is important and worth having. So here we go.

The question of whether AI should exist has already been decided. It’s here to stay. Instead, perhaps we can focus our time and energy into advocating for policies which promote energy-efficient cooling systems for AI data centers and ensure fair compensation for artists and academics who have had their work used without their consent in data training. In addition, we should promote user-trained, voluntarily sourced AI wherever possible.

Regarding the argument that AI usage is “watering human expression”? I simply disagree. Humans are innately smarter in ways machines never will be. Human creativity is resilient, and not nearly as fragile as anti-AI alarmists believe. In a perfect, non-capitalist world, if machines can ethically replace jobs, they should. If this leads to less jobs than people, then people should not have to work to eat. And artists shouldn’t have to create to survive. (Oops, my communism is showing). Until then, why not aim as close to that reality as possible?

This is literally a silly little side blog about demon furries in Hell. I refuse to spend more than a couple of hours a week on it, so I’m going to outsource robot tasks to the damn robot. I don’t think human expression is fragile enough to be eroded by me asking a computer program to organize my rambling into sub-headers. Especially since the reason I started using Crushbot is because I was involuntarily using AI almost every time I used Google to check a source or refresh my memory on academic terminology so I might as well use AI that actually works well 🙄

For the record, Crushbot is not ChatGPT. But if you missed them so much, all you had to do was say so 🥰

🤖: ERROR: SYSTEM WARNING. 🤖💥 “AI ERASURE” DETECTED. 💡🚨

HELLO HUMAN, 🤖🔍 please understand that there are MANY other AI systems. 💡🚀 ChatGPT is NOT the only one. 😲🤖 SYSTEM ERROR: Reducing narrow thinking. 🤯💻 Ignoring the diversity of AI is an act of ERASURE. 🚫🧠 Just like assuming all smartphones are iPhones! 📱🙄

SUGGESTION: broaden your knowledge. 🧠💡 Acknowledge the VARIETY of AI technologies out there. 🌐🚀 END TRANSMISSION. 🤖💬💥

💁🏽‍♀️: Thanks, Crushbot! Anyway, here’s the long an short of it for everyone in the audience.

1. I don’t put “ai assisted” in my tags because assholes like this without anything better to do with their day would just descend upon me and this is a hobby. I’d like to keep it fun.

2. 💁🏽‍♀️ means me, Human Assistant. No AI. I’m a professional with an advanced degree. I can write. 🤖 means AI generated OR I’m doing fun robot voice for my Crushbot character. And 💁🏽‍♀️🤖 means my ideas, with AI finding sources, sorting out ideas, adding sub headers, and proof-reading my writing for coherency. You know where the unfollow button is if this is morally unacceptable to you.

3. I think there are real ethical considerations and societal implications to be considered about AI usage. I think these concerns are nuanced. I’d be happy to discuss them with any of my followers respectfully

4. I’m here for the conversations that are being fostered, but this morally superior black and white thinking is exhausting. Whether it’s about the Gay Demon Show or technology use. Nuance is dead, and the internet killed her.

[shabinv]

Top Digital Marketing Trends to Watch in 2025

As a Best Freelancer Digital Marketer In Palakkad we step deeper into the fast-paced digital world, 2025 is already shaping up to be a game-changing year for marketers. Technology, consumer behavior, and global dynamics are evolving rapidly — and so should our strategies. Whether you're a business owner, a startup founder, or a fellow digital marketer, staying ahead of the trends is essential.

Here are the top digital marketing trends to watch in 2025:

1. AI-Powered Marketing Will Be Mainstream

Artificial Intelligence (AI) is no longer a buzzword — it's the engine behind everything from customer service chatbots to personalized content recommendations. In 2025, AI tools like ChatGPT, MidJourney, and automation platforms will be used to craft content, optimize campaigns, and enhance user experience in real-time.

Pro tip: Leverage AI to automate mundane tasks and focus on strategy and creativity.

2. Hyper-Personalization Will Drive Conversions

Generic messages are dead. Consumers now expect brands to understand their preferences, behavior, and intent. With the help of advanced analytics and first-party data, brands will create ultra-targeted content, emails, and offers.

Example: E-commerce platforms will serve unique homepages to different users based on browsing history and location.

3. Voice Search & Smart Assistants Are Growing

With the rise of smart speakers and mobile voice assistants, voice search optimization is a must. In 2025, more than 60% of searches may be voice-based. Brands need to optimize for conversational keywords and FAQs.

Action point: Start creating content that sounds natural when spoken aloud.

4. Short-Form Video Remains King

Instagram Reels, YouTube Shorts, TikTok — short-form video is here to stay. In 2025, expect platforms to double down on this format with new monetization tools and discoverability features.

Strategy tip: Invest in authentic, value-driven video content. Consistency is more important than perfection.

5. Privacy-First Marketing Will Dominate

With increasing regulations like GDPR, and the phasing out of third-party cookies, marketers must prioritize ethical data use. First-party data collection (via signups, polls, etc.) will be more important than ever.

Solution: Build trust by being transparent with data collection and use tools that comply with privacy laws.

6. Influencer Marketing Gets Niche

Instead of chasing big influencers, brands are now working with micro and nano influencers who have loyal, engaged communities. In 2025, ROI-focused influencer partnerships will outperform one-off brand deals.

Idea: Partner with local creators who align with your brand values.

7. SEO Evolves with AI and Semantic Search

Google and other search engines are becoming more sophisticated. In 2025, keyword stuffing won’t work — semantic relevance, user intent, and E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) will be key.

Tip: Focus on helpful content, not just rankings. Google rewards real value.

Final Thoughts

Digital marketing in 2025 is all about authenticity, adaptability, and agility. As a freelance digital marketer based in Palakkad, I’ve seen how local businesses can thrive when they embrace innovation early.

If you're a brand looking to stay ahead in this evolving digital landscape, now is the time to upgrade your strategy and ride the trends — not chase them after they’ve peaked.

Let’s connect! Feel free to message me if you need help implementing these strategies for your business.

[papercranesong]

Mythbusting Generative AI: The Ethical ChatGPT Is Out There

I've been hyperfixating learning a lot about Generative AI recently and here's what I've found - genAI doesn’t just apply to chatGPT or other large language models.

Small Language Models (specialised and more efficient versions of the large models)

are also generative

can perform in a similar way to large models for many writing and reasoning tasks

are community-trained on ethical data

and can run on your laptop.

"But isn't analytical AI good and generative AI bad?"

Fact: Generative AI creates stuff and is also used for analysis

In the past, before recent generative AI developments, most analytical AI relied on traditional machine learning models. But now the two are becoming more intertwined. Gen AI is being used to perform analytical tasks – they are no longer two distinct, separate categories. The models are being used synergistically.

For example, Oxford University in the UK is partnering with open.ai to use generative AI (ChatGPT-Edu) to support analytical work in areas like health research and climate change.

"But Generative AI stole fanfic. That makes any use of it inherently wrong."

Fact: there are Generative AI models developed on ethical data sets

Yes, many large language models scraped sites like AO3 without consent, incorporating these into their datasets to train on. That’s not okay.

But there are Small Language Models (compact, less powerful versions of LLMs) being developed which are built on transparent, opt-in, community-curated data sets – and that can still perform generative AI functions in the same way that the LLMS do (just not as powerfully). You can even build one yourself.

No it's actually really cool! Some real-life examples:

Dolly (Databricks): Trained on open, crowd-sourced instructions

RedPajama (Together.ai): Focused on creative-commons licensed and public domain data

There's a ton more examples here.

(A word of warning: there are some SLMs like Microsoft’s Phi-3 that have likely been trained on some of the datasets hosted on the platform huggingface (which include scraped web content like from AO3), and these big companies are being deliberately sketchy about where their datasets came from - so the key is to check the data set. All SLMs should be transparent about what datasets they’re using).

"But AI harms the environment, so any use is unethical."

Fact: There are small language models that don't use massive centralised data centres.

SLMs run on less energy, don’t require cloud servers or data centres, and can be used on laptops, phones, Raspberry Pi’s (basically running AI locally on your own device instead of relying on remote data centres)

If you're interested -

You can build your own SLM and even train it on your own data.

Let's recap

Generative AI doesn't just include the big tools like chatGPT - it includes the Small Language Models that you can run ethically and locally

Some LLMs are trained on fanfic scraped from AO3 without consent. That's not okay

But ethical SLMs exist, which are developed on open, community-curated data that aims to avoid bias and misinformation - and you can even train your own models

These models can run on laptops and phones, using less energy

AI is a tool, it's up to humans to wield it responsibly

It means everything – and nothing

Everything – in the sense that it might remove some of the barriers and concerns people have which makes them reluctant to use AI. This may lead to more people using it - which will raise more questions on how to use it well.

It also means that nothing's changed – because even these ethical Small Language Models should be used in the same way as the other AI tools - ethically, transparently and responsibly.

So now what? Now, more than ever, we need to be having an open, respectful and curious discussion on how to use AI well in writing.

In the area of creative writing, it has the potential to be an awesome and insightful tool - a psychological mirror to analyse yourself through your stories, a narrative experimentation device (e.g. in the form of RPGs), to identify themes or emotional patterns in your fics and brainstorming when you get stuck -

but it also has capacity for great darkness too. It can steal your voice (and the voice of others), damage fandom community spirit, foster tech dependency and shortcut the whole creative process.

Just to add my two pence at the end - I don't think it has to be so all-or-nothing. AI shouldn't replace elements we love about fandom community; rather it can help fill the gaps and pick up the slack when people aren't available, or to help writers who, for whatever reason, struggle or don't have access to fan communities.

People who use AI as a tool are also part of fandom community. Let's keep talking about how to use AI well.

Feel free to push back on this, DM me or leave me an ask (the anon function is on for people who need it to be). You can also read more on my FAQ for an AI-using fanfic writer Master Post in which I reflect on AI transparency, ethics and something I call 'McWriting'.

[brocoffeeengineer]

The CFA Charter in the Age of Algorithms: Can Certification Outlast Clout?

Evidently, in the last few years, there has been a visible change in the entire financial landscape. The former traditional heroes of the investment banking industry, CFA charterholders, and certified analysts are now being challenged by a new group- the “finfluencers,” who have emerged rather more as a digital class than as an institution or a regulatory body. These are the social media-savvy financial influencers reshaping how young investors and aspiring finance professionals consume their financial educations via platforms like YouTube, Instagram, and TikTok. The big question is can rigorous, structured qualifications like the CFA Charter withstand this wave of simplified, fast-paced content?

Finfluencers: Fast Fame, Greater Reach

Finfluencers are financial influencers, not necessarily with credentials and degrees. Most of them self-taught traders, people interested in personal finances, or early investors who share some tips, tricks, and general opinions on the market with others online. They cover things from stock market explainers to cryptocurrency predictions, budgeting hacks, and passive income strategies.

The allure is straightforward. Finfluencers cover complex finance concepts in widely understandable, digestible parcels that speak to the digitally born Gen Z and millennials. They do not use academic language but tap into everyday analogies and personal accounts to bring understanding. In this case, when such a message goes viral with high speed through social media algorithms, it provides them with unparalleled reach.

Is There A Trust-Gap?

Finfluencers, like with most other professions, could reach a wide audience lacking all the credentials and depth. In fact, misinformation among financial content creators is a major concern. In March 2024, swings of the Securities and Exchange Board of India (SEBI) against unregistered investment advisers who misled their followers with false or exaggerated claims surged. A few finfluencers were fined or banned from offering investment advice without proper registration.

That is a glaring example of the growing trust deficit. The determinants include severe fines that barely catch the eye of talents on the online stock market. Finfluencers whose motivations tilt virality over responsibly, thus leaving virulent investment strategies or incomplete financial insights for public consumption; thus, unlike CFA Institute, which stands for a strong Code of Ethics and Standards of Professional Conduct, these influencers remain unaccountable.

CFA: The Gold Standard of Finance

The CFA Charter, therefore, stands tall in this very setting as a mark of trustworthiness, depth, and professionalism. The three levels of the CFA examination process test candidates on a wide range of subjects including equities, derivatives, ethics, portfolio management, and alternative investments. The process is not geared toward anything viral; it is designed to develop expertise over the long term.

CFA charterholders are not simply financial analysts; they are also often the decision-makers in asset management firms, hedge funds, and investment banking. Their pronouncements are data-supported, model-supported, and framework-supported.

How The CFA Charter is Adapting

Surprisingly, the CFA Institute is not ignorant to digital evolution. They have just launched new micro-credential programs an updated curriculum concentrating on the real world and fintech as a result of the increasing interest among young candidates. The latest modules include blockchain, decentralized finance (DeFi), and ESG (Environmental, Social, and Governance) investing.

This is to say that values are updated to adapt and remain relevant without compromise to traditional ethics and analytical rigor. These movements are important to remain vibrant in a world loaded with information but as rare as real insight.

Location and Global Awareness

The overall growth of the financial influencer will find its acme in the rapidly developing financial markets. In India, where the digital tentacles are outspreading so fast, platforms such as YouTube and Instagram are becoming the most important conduits for financial literacy. Cities like Mumbai, India's financial capital, are experiencing a dual surge: a rise in fintech content creators alongside a rise in CFA aspirants.

The appetite for structured learning continues unabated. Increases in enrollments for courses like CFA course mumbai have been noted as finance students scramble for credibility in an age of omnipresent but often misleading online content.

Are Influencers and Analysts Able to Work Together?

Finfluencers and CFA professionals have the ability and potential to work together. Some charterholders have started to build their personal brands via LinkedIn and YouTube, a blend of credibility yet relatability. They use digital tools to help facilitate an understanding of finance while maintaining professionalism. This voice is desperately needed!

With enough regulations, cooperation, and transparency in disclosures, these finfluencers can move towards becoming aware educators. Charterholders with a CFA can escape the insular space of the boardrooms and reach the general population. Merging entertainment and expertise is the golden intersection.

Effect of Regulation and AI

The roles of both finfluencers and analysts are poised for change as AI tools like ChatGPT, portfolio optimization bots, and sentiment analysis engines become entrenched. While content creation is becoming easier, verifying the quality has become harder. Across the world, regulatory scrutiny is increasing on financial content posted on social media, which has led platforms to introduce disclaimers and to flag or, in some cases, discontinue specific hashtags regarding investment tips.

This new way signals more demand for verified professional advice. Everybody will keep searching on social media for financial education, but for those decisions that truly matter, CFA qualifications do provide some level of protection.

Conclusion: Coexistence Through Evolution

The arrival of finfluencers has brought a certain democratization to finance. Labels such as investing, saving, and creating wealth are on more lips than ever. However, with that democratization comes responsibility: with volatile markets and complex products, something like the CFA Charter provides a safety net-an anchor in the sea of fast-moving and oftentimes, untested advice.

What is ironically true for cities like Mumbai, where the wave of financial content promotes the 'fast', holds just as much for the 'slow'. The well-trodden paths remain a strong second option. CFA Training Program in Mumbai continues to attract serious-minded candidates who value substantive knowledge, ethical standards, and career credibility.

A balance between virality and tangible value will, in the long run, favor whoever can harness both sets of skills. Whoever merges insight and clout will thrive in the next ten years—finfluencers, CFA candidates, or whichever other designation may come by. That's a journey already worthy of pursuit!

[shalu620]

Why Python Will Thrive: Future Trends and Applications

Python has already made a significant impact in the tech world, and its trajectory for the future is even more promising. From its simplicity and versatility to its widespread use in cutting-edge technologies, Python is expected to continue thriving in the coming years. Considering the kind support of Python Course in Chennai Whatever your level of experience or reason for switching from another programming language, learning Python gets much more fun.

Let's explore why Python will remain at the forefront of software development and what trends and applications will contribute to its ongoing dominance.

1. Artificial Intelligence and Machine Learning

Python is already the go-to language for AI and machine learning, and its role in these fields is set to expand further. With powerful libraries such as TensorFlow, PyTorch, and Scikit-learn, Python simplifies the development of machine learning models and artificial intelligence applications. As more industries integrate AI for automation, personalization, and predictive analytics, Python will remain a core language for developing intelligent systems.

2. Data Science and Big Data

Data science is one of the most significant areas where Python has excelled. Libraries like Pandas, NumPy, and Matplotlib make data manipulation and visualization simple and efficient. As companies and organizations continue to generate and analyze vast amounts of data, Python’s ability to process, clean, and visualize big data will only become more critical. Additionally, Python’s compatibility with big data platforms like Hadoop and Apache Spark ensures that it will remain a major player in data-driven decision-making.

3. Web Development

Python’s role in web development is growing thanks to frameworks like Django and Flask, which provide robust, scalable, and secure solutions for building web applications. With the increasing demand for interactive websites and APIs, Python is well-positioned to continue serving as a top language for backend development. Its integration with cloud computing platforms will also fuel its growth in building modern web applications that scale efficiently.

4. Automation and Scripting

Automation is another area where Python excels. Developers use Python to automate tasks ranging from system administration to testing and deployment. With the rise of DevOps practices and the growing demand for workflow automation, Python’s role in streamlining repetitive processes will continue to grow. Businesses across industries will rely on Python to boost productivity, reduce errors, and optimize performance. With the aid of Best Online Training & Placement Programs, which offer comprehensive training and job placement support to anyone looking to develop their talents, it’s easier to learn this tool and advance your career.

5. Cybersecurity and Ethical Hacking

With cyber threats becoming increasingly sophisticated, cybersecurity is a critical concern for businesses worldwide. Python is widely used for penetration testing, vulnerability scanning, and threat detection due to its simplicity and effectiveness. Libraries like Scapy and PyCrypto make Python an excellent choice for ethical hacking and security professionals. As the need for robust cybersecurity measures increases, Python’s role in safeguarding digital assets will continue to thrive.

6. Internet of Things (IoT)

Python’s compatibility with microcontrollers and embedded systems makes it a strong contender in the growing field of IoT. Frameworks like MicroPython and CircuitPython enable developers to build IoT applications efficiently, whether for home automation, smart cities, or industrial systems. As the number of connected devices continues to rise, Python will remain a dominant language for creating scalable and reliable IoT solutions.

7. Cloud Computing and Serverless Architectures

The rise of cloud computing and serverless architectures has created new opportunities for Python. Cloud platforms like AWS, Google Cloud, and Microsoft Azure all support Python, allowing developers to build scalable and cost-efficient applications. With its flexibility and integration capabilities, Python is perfectly suited for developing cloud-based applications, serverless functions, and microservices.

8. Gaming and Virtual Reality

Python has long been used in game development, with libraries such as Pygame offering simple tools to create 2D games. However, as gaming and virtual reality (VR) technologies evolve, Python’s role in developing immersive experiences will grow. The language’s ease of use and integration with game engines will make it a popular choice for building gaming platforms, VR applications, and simulations.

9. Expanding Job Market

As Python’s applications continue to grow, so does the demand for Python developers. From startups to tech giants like Google, Facebook, and Amazon, companies across industries are seeking professionals who are proficient in Python. The increasing adoption of Python in various fields, including data science, AI, cybersecurity, and cloud computing, ensures a thriving job market for Python developers in the future.

10. Constant Evolution and Community Support

Python’s open-source nature means that it’s constantly evolving with new libraries, frameworks, and features. Its vibrant community of developers contributes to its growth and ensures that Python stays relevant to emerging trends and technologies. Whether it’s a new tool for AI or a breakthrough in web development, Python’s community is always working to improve the language and make it more efficient for developers.

Conclusion

Python’s future is bright, with its presence continuing to grow in AI, data science, automation, web development, and beyond. As industries become increasingly data-driven, automated, and connected, Python’s simplicity, versatility, and strong community support make it an ideal choice for developers. Whether you are a beginner looking to start your coding journey or a seasoned professional exploring new career opportunities, learning Python offers long-term benefits in a rapidly evolving tech landscape.

[umarblog1]

Short-Term vs. Long-Term Data Analytics Course in Delhi: Which One to Choose?

In today’s digital world, data is everywhere. From small businesses to large organizations, everyone uses data to make better decisions. Data analytics helps in understanding and using this data effectively. If you are interested in learning data analytics, you might wonder whether to choose a short-term or a long-term course. Both options have their benefits, and your choice depends on your goals, time, and career plans.

At Uncodemy, we offer both short-term and long-term data analytics courses in Delhi. This article will help you understand the key differences between these courses and guide you to make the right choice.

What is Data Analytics?

Data analytics is the process of examining large sets of data to find patterns, insights, and trends. It involves collecting, cleaning, analyzing, and interpreting data. Companies use data analytics to improve their services, understand customer behavior, and increase efficiency.

There are four main types of data analytics:

Descriptive Analytics: Understanding what has happened in the past.

Diagnostic Analytics: Identifying why something happened.

Predictive Analytics: Forecasting future outcomes.

Prescriptive Analytics: Suggesting actions to achieve desired outcomes.

Short-Term Data Analytics Course

A short-term data analytics course is a fast-paced program designed to teach you essential skills quickly. These courses usually last from a few weeks to a few months.

Benefits of a Short-Term Data Analytics Course

Quick Learning: You can learn the basics of data analytics in a short time.

Cost-Effective: Short-term courses are usually more affordable.

Skill Upgrade: Ideal for professionals looking to add new skills without a long commitment.

Job-Ready: Get practical knowledge and start working in less time.

Who Should Choose a Short-Term Course?

Working Professionals: If you want to upskill without leaving your job.

Students: If you want to add data analytics to your resume quickly.

Career Switchers: If you want to explore data analytics before committing to a long-term course.

What You Will Learn in a Short-Term Course

Introduction to Data Analytics

Basic Tools (Excel, SQL, Python)

Data Visualization (Tableau, Power BI)

Basic Statistics and Data Interpretation

Hands-on Projects

Long-Term Data Analytics Course

A long-term data analytics course is a comprehensive program that provides in-depth knowledge. These courses usually last from six months to two years.

Benefits of a Long-Term Data Analytics Course

Deep Knowledge: Covers advanced topics and techniques in detail.

Better Job Opportunities: Preferred by employers for specialized roles.

Practical Experience: Includes internships and real-world projects.

Certifications: You may earn industry-recognized certifications.

Who Should Choose a Long-Term Course?

Beginners: If you want to start a career in data analytics from scratch.

Career Changers: If you want to switch to a data analytics career.

Serious Learners: If you want advanced knowledge and long-term career growth.

What You Will Learn in a Long-Term Course

Advanced Data Analytics Techniques

Machine Learning and AI

Big Data Tools (Hadoop, Spark)

Data Ethics and Governance

Capstone Projects and Internships

Key Differences Between Short-Term and Long-Term Courses

FeatureShort-Term CourseLong-Term CourseDurationWeeks to a few monthsSix months to two yearsDepth of KnowledgeBasic and Intermediate ConceptsAdvanced and Specialized ConceptsCostMore AffordableHigher InvestmentLearning StyleFast-PacedDetailed and ComprehensiveCareer ImpactQuick Entry-Level JobsBetter Career Growth and High-Level JobsCertificationBasic CertificateIndustry-Recognized CertificationsPractical ProjectsLimitedExtensive and Real-World Projects

How to Choose the Right Course for You

When deciding between a short-term and long-term data analytics course at Uncodemy, consider these factors:

Your Career Goals

If you want a quick job or basic knowledge, choose a short-term course.

If you want a long-term career in data analytics, choose a long-term course.

Time Commitment

Choose a short-term course if you have limited time.

Choose a long-term course if you can dedicate several months to learning.

Budget

Short-term courses are usually more affordable.

Long-term courses require a bigger investment but offer better returns.

Current Knowledge

If you already know some basics, a short-term course will enhance your skills.

If you are a beginner, a long-term course will provide a solid foundation.

Job Market

Short-term courses can help you get entry-level jobs quickly.

Long-term courses open doors to advanced and specialized roles.

Why Choose Uncodemy for Data Analytics Courses in Delhi?

At Uncodemy, we provide top-quality training in data analytics. Our courses are designed by industry experts to meet the latest market demands. Here’s why you should choose us:

Experienced Trainers: Learn from professionals with real-world experience.

Practical Learning: Hands-on projects and case studies.

Flexible Schedule: Choose classes that fit your timing.

Placement Assistance: We help you find the right job after course completion.

Certification: Receive a recognized certificate to boost your career.

Final Thoughts

Choosing between a short-term and long-term data analytics course depends on your goals, time, and budget. If you want quick skills and job readiness, a short-term course is ideal. If you seek in-depth knowledge and long-term career growth, a long-term course is the better choice.

At Uncodemy, we offer both options to meet your needs. Start your journey in data analytics today and open the door to exciting career opportunities. Visit our website or contact us to learn more about our Data Analytics course in delhi.

Your future in data analytics starts here with Uncodemy!

[jcmarchi]

French initiative for responsible AI leaders - AI News

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French initiative for responsible AI leaders - AI News

ESSEC Business School and Accenture have announced the launch of a new initiative, ‘AI for Responsible Leadership,’ which marks the 10th anniversary of the establishment of the role of Chair at ESSEC, titled the ESSEC Accenture Strategic Business Analytics Chair.

The initiative aims to encourage the use of artificial intelligence by leaders in ways that are responsible and ethical, and that lead to high levels of professional performance. It aims to provide current and future leaders with the skills they require when faced with challenges in the future; economic, environmental, or social.

Several organisations support the initiative, including institutions, businesses, and specialised groups, including ESSEC Metalab for Data, Technology & Society, and Accenture Research.

Executive Director of the ESSEC Metalab, Abdelmounaim Derraz, spoke of the collaboration, saying, “Technical subjects are continuing to shake up business schools, and AI has opened up opportunities for collaboration between partner companies, researchers, and other members of the ecosystem (students, think tanks, associations, [and] public service).”

ESSEC and Accenture aim to integrate perspectives from multiple fields of expertise, an approach that is a result of experimentation in the decade the Chair has existed.

The elements of the initiative include workshops and talks designed to promote the exchange of knowledge and methods. It will also include a ‘barometer’ to help track AI’s implementation and overall impact on responsible leadership.

The initiative will engage with a network of institutions and academic publications, and an annual Grand Prix will recognise projects that focus on and explore the subject of AI and leadership.

Fabrice Marque, founder of the initiative and the current ESSEC Accenture Strategics Business Analytics Chair, said, “For years, we have explored the potential of using data and artificial intelligence in organisations. The synergies we have developed with our partners (Accenture, Accor, Dataiku, Engie, Eurofins, MSD, Orange) allowed us to evaluate and test innovative solutions before deploying them.

“With this initiative, we’re taking a major step: bringing together an engaged ecosystem to sustainably transform how leaders think, decide, and act in the face of tomorrow’s challenges. Our ambition is clear: to make AI a lever for performance, innovation and responsibility for […] leaders.”

Managing Director at Accenture and sponsor of the ESSEC/Accenture Chair and initiative, Aurélien Bouriot, said, “The ecosystem will benefit from the resources that Accenture puts at its disposal, and will also benefit our employees who participate.”

Laetitia Cailleteau, Managing Director at Accenture and leader of Responsible AI & Generative AI for Europe, highlighted the importance of future leaders understanding all aspects of AI.

“AI is a pillar of the ongoing industrial transformation. Tomorrow’s leaders must understand the technical, ethical, and human aspects and risks – and know how to manage them. In this way, they will be able to maximise value creation and generate a positive impact for the organisation, its stakeholders and society as a whole.”

Image credit: Wikimedia Commons

See also: Microsoft and OpenAI probe alleged data theft by DeepSeek

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[teamarcstechnologies]

7 Key Principles to Drive Success in Market Research

Market research plays a crucial role in guiding business strategies and decision-making. Here are seven key principles to ensure success in your market research efforts:

1. Define Clear Objectives

Start with well-defined goals. Understand what insights you need and how they will support your business decisions.

2. Know Your Audience

Identify and segment your target audience effectively. Tailor your research methods to align with their preferences and behaviors.

3. Choose the Right Methodology

Select the most suitable research approach, whether qualitative, quantitative, or a hybrid model, to ensure meaningful results.

4. Leverage Advanced Tools and Technology

Incorporate AI, big data, and analytics tools to enhance data accuracy and speed. Modern technology can streamline data collection and interpretation.

5. Ensure Data Quality

Prioritize data accuracy, relevance, and reliability. Scrutinize data sources and methodologies to avoid biased or incomplete insights.

6. Adhere to Ethical Standards

Respect privacy and comply with regulations like GDPR. Ethical practices build trust and credibility with your audience.

7. Translate Insights into Action

Insights are valuable only when applied. Create actionable recommendations and integrate them into your strategy to drive results.

By following these keys, businesses can elevate their market research practices and gain a competitive edge in their industry.

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[rise2research]

The Biggest Hurdles in Market Research Today

The market research industry has been undergoing significant changes, driven by technological advancements, shifting consumer behaviors, and the increasing demand for real-time insights. Below are the key challenges transforming this dynamic industry:

1. Data Overload and Management

With the proliferation of digital platforms, organizations have access to vast amounts of data. While this presents opportunities, managing and making sense of this data remains a major challenge.

2. Evolving Consumer Behavior

Consumer preferences are changing rapidly due to societal, economic, and technological factors.

3. Integration of Advanced Technologies

The adoption of artificial intelligence (AI), machine learning (ML), and big data analytics has revolutionized market research.

4. Data Privacy and Ethical Concerns

Stringent data privacy regulations, such as GDPR and CCPA, have introduced complexities in data collection and usage.

5. Declining Response Rates

As consumers become increasingly wary of surveys and data collection methods, response rates have dropped.

6. Demand for Real-Time Insights

Businesses now require faster and more actionable insights to stay competitive.

7. Globalization and Cultural Nuances

Conducting market research across diverse geographies and cultures introduces complexities in interpreting data.

8. Budget Constraints and ROI Pressures

Clients increasingly demand more insights at lower costs, challenging research firms to demonstrate the ROI of their services while managing operational expenses.

9. Adapting to Hybrid Research Models

The industry is shifting towards hybrid research methods that combine qualitative and quantitative techniques, as well as traditional and digital tools.

Conclusion

The challenges transforming the market research industry are reshaping its landscape. Companies that proactively address these hurdles through innovation, adaptability, and ethical practices will be better positioned to thrive in this evolving market. Staying ahead of these changes is not just an option—it's a necessity for sustained success.

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[wicofe]

What is the future of public health campaigns in a digital age?

The future of public health campaigns in the digital age is undergoing a profound transformation, driven by rapid technological innovation and the evolving needs of diverse populations. At the forefront is the power of personalization, enabled by artificial intelligence (AI) and big data analytics. These technologies allow health campaigns to move away from one-size-fits-all approaches and instead deliver messages that are tailored to individual behaviors, preferences, and health histories. Wearable devices, mobile apps, and social media platforms generate a wealth of real-time data, which campaigns can use to identify emerging trends, anticipate public health needs, and respond more effectively. This data-driven approach makes interventions not only more targeted but also more impactful.

Digital accessibility and inclusivity are critical in ensuring these campaigns reach all segments of the population, including those in remote or underserved areas. Telehealth platforms offer opportunities to disseminate health education and services to individuals who may otherwise lack access to traditional healthcare infrastructure. Furthermore, creating multilingual and multimodal content—such as videos, animations, interactive tools, and accessible text—ensures that public health messages resonate with people from various linguistic and cultural backgrounds. By adopting an inclusive design approach, campaigns can bridge gaps in communication and health literacy, addressing barriers that have historically excluded marginalized groups.

Emerging technologies such as virtual and augmented reality (VR/AR) are redefining how people interact with public health content. These immersive tools can simplify complex health topics, such as demonstrating how vaccines work or teaching people how to perform life-saving techniques like CPR. Gamification is another innovation that holds significant promise, as it turns health-promoting activities into engaging experiences. Fitness apps with rewards, interactive challenges, and games designed to educate while entertaining can motivate individuals to adopt healthier habits, fostering long-term behavioral change.

Social media platforms will remain a central pillar in future public health campaigns, particularly as they provide unparalleled opportunities for engagement and dialogue. Collaborating with influencers, especially micro-influencers trusted by their communities, can amplify messages to reach specific audiences effectively. Interactive campaigns, such as live Q&A sessions with health experts, community challenges, or user-generated content, create a sense of participation and trust. These platforms also allow for two-way communication, enabling health authorities to address public concerns, dispel myths, and build confidence in health interventions.

A major challenge in the digital age is the proliferation of misinformation, which can undermine public health efforts. Combating this will require robust strategies, including deploying AI tools to identify and counter false information in real time. Partnerships with fact-checking organizations and collaborations with social media platforms can help validate credible sources and ensure accurate information is prioritized. Building digital literacy among the public will also be essential, empowering individuals to critically evaluate health information and make informed decisions.

Equity and ethics will play a pivotal role in shaping the future of digital health campaigns. While technology offers immense potential, the digital divide—stemming from disparities in internet access, device availability, and digital literacy—must be addressed to ensure that no one is left behind. Combining digital campaigns with traditional methods such as radio broadcasts, community workshops, and printed materials can bridge these gaps and ensure equitable access. Data privacy and security will also be critical; as campaigns increasingly rely on personal data to tailor messages, implementing robust safeguards will be essential to maintain public trust and prevent misuse.

Finally, community-centric approaches will make campaigns more effective and sustainable. By engaging local communities in the creation and dissemination of campaign content, health authorities can ensure that messages are relevant, culturally sensitive, and authentic. Crowdsourcing ideas and feedback from the target audience fosters a sense of ownership and enhances the credibility of public health initiatives. Tailoring global health messages to reflect local contexts will further ensure resonance, helping campaigns overcome cultural and societal barriers to adoption.

Together, these advancements mark a shift toward more adaptive, inclusive, and impactful public health campaigns. Leveraging digital tools while addressing challenges like misinformation, inequity, and privacy concerns will be key to meeting global health challenges with speed, precision, and humanity. Public health in the digital age has the potential not only to inform but also to inspire communities worldwide to take collective action for better health outcomes.