#Introduction to Data Analytics

[themanjeet]

Introduction to Data Analytics

In today’s world, businesses are generating more data than ever before. This data can be used to gain insights into customer behavior, identify trends, and make better business decisions.

https://medium.com/@rolandmack63/introduction-to-data-analytics-1dd13bef5ab8

[phasesandplaylists]

Hello whomever might read this,

I've been wanting to post on here for a while. With 2025 around the corner, I decided to use Tumblr to track my goals and document my progress. Hopefully, I'll figure out how to relate that with Twitter(X) and whatever platform helps one land a job these days.

Basic info:

I'm a writer.

My name's Chisom and I'm 25 years (26 next year). I'm Nigerian and a University graduate with a BSc in Computer Science/Statistics. I live in Nigeria.

Other tidbits:

I listen to basically any type of music, but Pop is my main genre.

Fandoms I belong to: Directioner, Nctzen, Potterhead, etc.

I'm currently studying Data Analysis with every intention to land a job in the field next year. Most of my posts will be in regards to studying.

Languages spoken: English, Hausa, Igbo, Spanish (intermediate)

Currently studying: Korean, Swahili, Chinese. Korean takes priority currently.

Song I currently have on repeat:

Nice to meet you♥️

[blessedmediaa]

Certified Digital Marketers in the UK

Top 5 Certified Digital Marketers in the UK

Introduction

Certified Digital Marketers in the UK, staying ahead of the competition requires expertise, innovation, and a deep understanding of the latest trends. Businesses across the UK are increasingly turning to certified digital marketing professionals to achieve online success.

But with so many professionals offering digital marketing services, how do you identify the best? In this blog, we introduce the top 5 certified digital marketers in the UK, each known for their exceptional skills and proven track record. Whether you’re a startup, an established brand, or an entrepreneur, working with the right expert can be a game-changer for your business.

Why Work with a Certified Digital Marketer in the UK?

Digital marketing is more than just running ads or posting content on social media. It involves strategic planning, data analysis, and the ability to adapt to ever-changing algorithms. Here’s why hiring a certified digital marketer in the UK is crucial:

Expertise in SEO & PPC – Improve rankings and get more traffic.

Content & Social Media Mastery – Engage and grow your audience.

Data-Driven Decision Making – Maximize ROI with analytics.

Updated Knowledge – Stay ahead with the latest digital trends.

Now, let’s explore the top digital marketing experts in the UK who can help take your business to the next level.

Top 5 Certified Digital Marketers in the UK

1. Neil Patel – The Global SEO Authority Certified Digital Marketers in the UK

Expertise: SEO, Content Marketing, Growth Hacking Neil Patel is a globally recognized digital marketing expert with deep expertise in SEO and content marketing. His strategies have helped businesses across the UK and beyond achieve remarkable online success.

Why Choose Neil Patel?

Proven strategies for SEO growth and traffic increase.

Offers free tools for SEO and marketing analysis.

Works with leading brands worldwide.

If you’re looking for top-rated digital marketers in the UK specializing in organic growth, Neil Patel is a name you can trust.

2. Andrew Davis – The Content Marketing Specialist Certified Digital Marketers in the UK

Expertise: Storytelling, Branding, Digital Strategy Andrew Davis is a well-known figure in the digital marketing space, focusing on content marketing and brand storytelling. He has worked with businesses across the UK to enhance their online engagement and brand authority.

Why Choose Andrew Davis?

Helps businesses craft powerful brand stories.

Expert in video content marketing.

One of the leading digital marketing experts in the UK.

If content is the backbone of your digital strategy, Andrew Davis can help you create compelling narratives that connect with your audience.

3. Marie Page – The Social Media Growth Expert

Expertise: Social Media Marketing, Facebook Ads, Engagement Strategies Marie Page is a certified digital marketing professional in the UK specializing in social media growth and paid advertising. She has helped countless brands scale their online presence through strategic campaigns.

Why Choose Marie Page?

Expertise in Facebook and Instagram Ads.

Helps businesses build strong online communities.

Recognized as one of the best online marketers in the UK.

If you’re looking to grow your brand’s social media presence, Marie Page’s strategies are highly effective.

4. Luke Brynley-Jones – The Paid Advertising & Strategy Expert

Expertise: PPC, LinkedIn Marketing, Lead Generation Luke Brynley-Jones is a top digital marketing specialist in the UK with expertise in paid advertising and lead generation. He has helped businesses increase their ROI through data-driven ad strategies.

Why Choose Luke Brynley-Jones?

Specializes in LinkedIn marketing & lead generation.

Helps businesses optimize ad spend for maximum ROI.

Known as a certified marketing professional in the UK.

For businesses focused on B2B marketing and paid ad strategies, Luke Brynley-Jones is a top choice.

5. Gavin Bell – The Facebook Advertising Guru

Expertise: Facebook Ads, Sales Funnels, Conversion Optimization Gavin Bell is widely regarded as one of the best digital marketers in the UK, particularly in the field of Facebook advertising. He has helped businesses improve their ad performance and maximize conversions.

Why Choose Gavin Bell?

Expert in high-converting Facebook ad campaigns.

Helps brands reduce ad costs while increasing leads.

Recognized as one of the top-rated digital marketers in the UK.

If paid social media advertising is your priority, Gavin Bell’s expertise can help you achieve the best results.

How to Choose the Right Digital Marketer for Your Business

Finding the right certified digital marketer in the UK depends on your business goals. Here’s how to choose the best one for you:

1. Identify Your Goals

Do you need help with SEO, social media marketing, or paid advertising? Define your objectives before selecting a marketer.

2. Check Certifications & Experience

A certified digital marketing professional in the UK should have credentials from recognized institutions like Google, HubSpot, or Facebook.

3. Review Case Studies & Testimonials

Look at their past work and success stories. This helps you understand their expertise and effectiveness.

4. Evaluate Their Strategy & Approach

Each marketer has a unique method. Ensure their approach aligns with your brand’s vision and budget.

5. Compare Pricing & ROI

While hiring an expert is an investment, consider the return on investment (ROI) they can deliver.

Final Thoughts

The digital marketing industry in the UK is thriving, and having the right expert by your side can elevate your brand’s success. Whether you need an SEO specialist, social media marketer, or advertising strategist, these top 5 certified digital marketers in the UK are among the best in the industry.

At BlessedMediaa, we understand the importance of expert-driven marketing solutions. If you’re looking for a trusted digital marketing agency in the UK, we’re here to help.

🚀 Want to grow your business online? Contact BlessedMediaa today for customized digital marketing strategies!

Key Takeaways

✅ Working with a certified digital marketer in the UK ensures expertise in SEO, PPC, content marketing, and social media. ✅ Neil Patel, Andrew Davis, Marie Page, Luke Brynley-Jones, and Gavin Bell are among the top digital marketing specialists in the UK. ✅ Choose a marketer based on your business goals, experience, and ROI potential. ✅ Digital marketing success depends on expert-driven strategies and continuous optimization.

🔹 Need expert digital marketing services? Contact BlessedMediaa today!

If you found this article informative, be sure to share your thoughts or questions in the comments section below. Stay tuned for more insights on groundbreaking technologies, and don’t forget to subscribe for the latest updates.

Thank you for reading!

[vuelitics1]

Unlock the power of Business Intelligence (BI) and elevate your business to new heights! In this video, we break down the fundamentals of BI, showing you how data-driven decisions can transform your company. Learn about the core components of BI, including Data Collection, Integration, Analysis, and Visualization, and discover why BI is essential for making informed decisions. Key Takeaways: Understand the basics of Business Intelligence Learn the key steps involved in BI Discover the benefits of BI for your business See real-world examples of BI in action Whether you're new to BI or looking to deepen your understanding, this video is for you. Don't forget to like, comment, and subscribe for more insights on how to leverage BI for your business growth! Helpful Resources: Explore our blog for more in-depth articles: https://vuelitics.com/blog

Connect With Us:

Facebook: https://www.facebook.com/profile.php?id=61560856345182&sk=about_details Instagram:https://www.instagram.com/vuelitics_velan/ Twitter:https://x.com/vuelitics Linkedin: https://www.linkedin.com/company/vuelitics/ Youtube: https://www.youtube.com/@Vuelitics Website: https://vuelitics.com/

[juliebowie]

Introduction to Big Data: Understanding the Fundamentals

In an era dominated by digital transformation, the term “Big Data” has become ubiquitous, symbolizing a seismic shift in how organizations collect, process, and utilize vast amounts of information. From enhancing business strategies to driving innovation across various sectors, Big Data has proven to be a cornerstone of the modern technological landscape.

This blog delves into the essence of Big Data, exploring its fundamentals, characteristics, sources, technologies, and applications, and concludes with an invitation to elevate your Data Science skills through Pickl.AI’s Data Science course.

Introduction

Big Data represents a paradigm shift in the way data is harnessed and leveraged for insights. Traditional data management techniques fall short in handling the volume, velocity, and variety of data generated in today’s interconnected world. Understanding Big Data is crucial for anyone aiming to thrive in a data-driven environment.

Definition of Big Data

Big Data refers to the massive, complex datasets that are beyond the capabilities of traditional data processing tools to manage and analyze. It encompasses data that is not only large in size but also varied in type and generated at an unprecedented speed. The defining characteristics of Big Data, often referred to as the three Vs — Volume, Velocity, and Variety — help in understanding its scope and challenges.

Volume: Refers to the enormous amount of data generated every second. Examples include data from social media platforms, sensors, transactions, and more.

Velocity: Describes the speed at which data is generated and processed. Real-time data processing is a key aspect of Big Data.

Variety: Encompasses the different types of data, including structured, semi-structured, and unstructured data such as text, images, video, and more.

Importance of Big Data in Today’s Digital Landscape

The significance of Big Data lies in its potential to unlock valuable insights and drive decision-making processes across various domains. Here’s why Big Data is vital in today’s digital landscape:

Enhanced Decision Making: By analyzing vast amounts of data, organizations can make more informed and accurate decisions.

Improved Customer Experience: Big Data allows businesses to understand customer behavior and preferences, leading to personalized services and improved satisfaction.

Operational Efficiency: Data-driven insights help in optimizing operations, reducing costs, and improving efficiency.

Innovation and Development: Big Data fuels innovation by providing the necessary insights for developing new products and services.

Competitive Advantage: Companies leveraging Big Data can gain a significant edge over competitors by quickly adapting to market trends and customer needs.

Characteristics of Big Data

Big Data is characterized by the following attributes, often expanded from the initial three Vs to include more dimensions:

Volume: Refers to the vast quantities of data generated from various sources.

Velocity: The speed at which data is generated, collected, and analyzed.

Variety: The diverse types of data, including structured, semi-structured, and unstructured formats.

Veracity: The quality and accuracy of data, addressing issues such as data inconsistency and uncertainty.

Value: The potential of Big Data to generate actionable insights and business value.

These characteristics highlight the challenges and opportunities associated with managing and analyzing Big Data.

Sources of Big Data

Big Data is generated from multiple sources, each contributing to the vast pool of information. Key sources include:

Social Media: Platforms like Facebook, Twitter, and Instagram generate vast amounts of user data through posts, comments, and interactions.

Sensors and IoT Devices: Devices connected to the Internet of Things (IoT) generate continuous streams of data from various applications, including smart homes, industrial equipment, and wearable technology.

Transactional Data: E-commerce sites, banking, and other financial services generate massive datasets from transactions and customer interactions.

Web and Log Data: Data generated from web traffic, server logs, and online interactions provide insights into user behavior and system performance.

Multimedia Data: Images, videos, audio files, and other multimedia content contribute significantly to Big Data, particularly with the rise of platforms like YouTube and Instagram.

Public Data: Government databases, research publications, and open data initiatives provide valuable datasets for analysis and innovation.

Big Data Technologies

Handling Big Data requires specialized technologies and tools designed to manage, process, and analyze large and complex datasets efficiently. Key Big Data technologies include:

Hadoop Ecosystem

Hadoop is an open-source framework that allows for the distributed processing of large datasets across clusters of computers using simple programming models. Key components include:

Hadoop Distributed File System (HDFS): A scalable and fault-tolerant file system designed to store large datasets.

MapReduce: A programming model for processing and generating large datasets with a parallel, distributed algorithm.

YARN: A resource management layer for scheduling and handling resource requests from applications.

Hive: A data warehousing solution that provides SQL-like querying capabilities.

Apache Spark

Apache Spark is an open-source, distributed computing system known for its speed and ease of use in processing large datasets. It provides an in-memory computing framework, making it much faster than Hadoop’s MapReduce.

NoSQL Databases

NoSQL databases are designed to handle unstructured and semi-structured data, providing flexibility and scalability. Examples include:

MongoDB: A document-oriented NoSQL database.

Cassandra: A highly scalable, distributed NoSQL database designed for handling large amounts of data across many commodity servers.

HBase: A scalable, distributed database that supports structured data storage for large tables.

Data Processing and ETL Tools

Tools for extracting, transforming, and loading (ETL) data are crucial for preparing Big Data for analysis. Examples include:

Apache NiFi: An integrated data logistics platform for automating the movement of data between systems.

Talend: A platform that provides tools for data integration, data management, and data quality.

Data Analysis and Visualization Tools

Analyzing and visualizing Big Data requires specialized tools to uncover insights and present them effectively. Key tools include:

Apache Spark MLlib: A machine learning library for Apache Spark, providing algorithms for classification, regression, clustering, and more.

Tableau: A data visualization tool that allows for the creation of interactive and shareable dashboards.

Power BI: A business analytics service by Microsoft, providing interactive visualizations and business intelligence capabilities.

Applications of Big Data

Big Data has transformative potential across various sectors, driving innovation and improving efficiency. Explore how Big Data transforms industries through applications in healthcare, finance, retail, transportation, energy, and entertainment.

Learn how predictive analytics, personalized recommendations, route optimization, and smart grids enhance efficiency, improve customer experiences, and drive innovation across various sectors, making data-driven decisions a cornerstone of modern business strategies.

Healthcare

Big Data is revolutionizing healthcare by enabling personalized medicine, improving patient outcomes, and enhancing operational efficiency. With its features, Big Data can transform the healthcare industry. The following list shows the same:

Predictive Analytics: Identifying patterns and predicting patient outcomes, enabling proactive care and early intervention.

Genomic Research: Analyzing large-scale genomic data to understand genetic disorders and develop targeted therapies.

Operational Efficiency: Optimizing hospital operations, reducing wait times, and improving resource allocation.

Finance

The financial industry leverages Big Data to enhance decision-making, manage risks, and improve customer experiences. These include the following:

Fraud Detection: Using advanced analytics to identify and prevent fraudulent activities in real-time.

Risk Management: Analyzing market trends and customer data to assess and mitigate financial risks.

Customer Insights: Understanding customer behavior and preferences to offer personalized financial products and services.

Retail

In retail, Big Data helps businesses understand customer preferences, optimize supply chains, and enhance marketing strategies. Some of the key applications of Big Data in retail industry are highlighted below:

Customer Analytics: Analyzing purchasing patterns to offer personalized recommendations and improve customer loyalty.

Inventory Management: Optimizing stock levels and reducing waste by predicting demand and managing supply chains efficiently.

Marketing Optimization: Tailoring marketing campaigns to target specific customer segments and maximize ROI.

Transportation and Logistics

Big Data is transforming transportation and logistics by improving operational efficiency, reducing costs, and enhancing customer experiences. The following list showcases how Big Data is used in the transportation and logistics industry:

Route Optimization: Analyzing traffic patterns and delivery routes to optimize transportation and reduce fuel consumption.

Predictive Maintenance: Using sensor data to predict and prevent equipment failures, reducing downtime and maintenance costs.

Supply Chain Visibility: Providing real-time insights into supply chain operations, improving transparency and efficiency.

Energy

The energy sector leverages Big Data to optimize production, manage consumption, and improve sustainability. Some of its key applications are listed below:

Smart Grids: Analyzing data from smart meters and sensors to optimize energy distribution and reduce outages.

Predictive Maintenance: Monitoring equipment and infrastructure to predict and prevent failures, improving reliability.

Energy Consumption: Analyzing consumption patterns to promote energy efficiency and reduce waste.

Entertainment

In the entertainment industry, Big Data is used to understand audience preferences, optimize content delivery, and enhance user experiences. Here are some of the key applications of Big Data that are transforming the entertainment industry.

Content Recommendation: Using data analytics to recommend personalized content to users on streaming platforms.

Audience Analytics: Understanding viewer behavior and preferences to inform content creation and marketing strategies.

Revenue Optimization: Analyzing data from ticket sales, merchandise, and advertising to maximize revenue streams.

Conclusion

The advent of Big Data has fundamentally transformed the way organizations operate, providing unprecedented opportunities for innovation, efficiency, and growth. From healthcare to finance, retail to energy, Big Data is driving advancements and enabling data-driven decision-making across various sectors.

Understanding the fundamentals and applications of Big Data is essential for anyone looking to thrive in today’s digital landscape.

To harness the full potential of Big Data, a strong foundation in Data Science is crucial. If you’re ready to embark on a journey to become a proficient data scientist, consider enrolling in Pickl.AI’s Data Science course. This comprehensive program offers hands-on training and expert guidance to equip you with the skills needed to excel in the field of Data Science.

Start your journey with Pickl.AI and transform your career with the best Data Science program available. Join now and unlock the power of Big Data to drive your success.

[strategiadvizo]

Elevating Employability: Short-Term Course Suggestions for College Students

Empower your future with our latest blog on short-term courses for college students! 🚀 Enhance your employability and unlock new opportunities. Dive in to discover courses that fit your passion and career goals. #EmpowermentThroughEducation #SkillUp

“विद्या ददाति विनयं, विनयाद् याति पात्रताम्।” “Education bestows humility, humility leads to worthiness.” In a world that’s constantly evolving, the importance of education—especially for students from lesser-known colleges in India—cannot be overstated. Education not only paves the way for personal growth but also significantly boosts employability in today’s competitive job market. Here are…

[river-taxbird]

The Four Horsemen of the Digital Apocalypse

Blockchain. Artificial Intelligence. Internet of Things. Big Data.

Do these terms sound familiar? You have probably been hearing some or all of them non stop for years. "They are the future. You don't want to be left behind, do you?"

While these topics, particularly crypto and AI, have been the subject of tech hype bubbles and inescapable on social media, there is actually something deeper and weirder going on if you scratch below the surface.

I am getting ready to apply for my PhD in financial technology, and in the academic business studies literature (Which is barely a science, but sometimes in academia you need to wade into the trash can.) any discussion of digital transformation or the process by which companies adopt IT seem to have a very specific idea about the future of technology, and it's always the same list, that list being, blockchain, AI, IoT, and Big Data. Sometimes the list changes with additions and substitutions, like the metaverse, advanced robotics, or gene editing, but there is this pervasive idea that the future of technology is fixed, and the list includes tech that goes from questionable to outright fraudulent, so where is this pervasive idea in the academic literature that has been bleeding into the wider culture coming from? What the hell is going on?

The answer is, it all comes from one guy. That guy is Klaus Schwab, the head of the World Economic Forum. Now there are a lot of conspiracies about the WEF and I don't really care about them, but the basic facts are it is a think tank that lobbies for sustainable capitalist agendas, and they famously hold a meeting every year where billionaires get together and talk about how bad they feel that they are destroying the planet and promise to do better. I am not here to pass judgement on the WEF. I don't buy into any of the conspiracies, there are plenty of real reasons to criticize them, and I am not going into that.

Basically, Schwab wrote a book titled the Fourth Industrial Revolution. In his model, the first three so-called industrial revolutions are:

1. The industrial revolution we all know about. Factories and mass production basically didn't exist before this. Using steam and water power allowed the transition from hand production to mass production, and accelerated the shift towards capitalism.

2. Electrification, allowing for light and machines for more efficient production lines. Phones for instant long distance communication. It allowed for much faster transfer of information and speed of production in factories.

3. Computing. The Space Age. Computing was introduced for industrial applications in the 50s, meaning previously problems that needed a specific machine engineered to solve them could now be solved in software by writing code, and certain problems would have been too big to solve without computing. Legend has it, Turing convinced the UK government to fund the building of the first computer by promising it could run chemical simulations to improve plastic production. Later, the introduction of home computing and the internet drastically affecting people's lives and their ability to access information.

That's fine, I will give him that. To me, they all represent changes in the means of production and the flow of information, but the Fourth Industrial revolution, Schwab argues, is how the technology of the 21st century is going to revolutionize business and capitalism, the way the first three did before. The technology in question being AI, Blockchain, IoT, and Big Data analytics. Buzzword, Buzzword, Buzzword.

The kicker though? Schwab based the Fourth Industrial revolution on a series of meetings he had, and did not construct it with any academic rigor or evidence. The meetings were with "numerous conversations I have had with business, government and civil society leaders, as well as technology pioneers and young people." (P.10 of the book) Despite apparently having two phds so presumably being capable of research, it seems like he just had a bunch of meetings where the techbros of the mid 2010s fed him a bunch of buzzwords, and got overly excited and wrote a book about it. And now, a generation of academics and researchers have uncritically taken that book as read, filled the business studies academic literature with the idea that these technologies are inevitably the future, and now that is permeating into the wider business ecosystem.

There are plenty of criticisms out there about the fourth industrial revolution as an idea, but I will just give the simplest one that I thought immediately as soon as I heard about the idea. How are any of the technologies listed in the fourth industrial revolution categorically different from computing? Are they actually changing the means of production and flow of information to a comparable degree to the previous revolutions, to such an extent as to be considered a new revolution entirely? The previous so called industrial revolutions were all huge paradigm shifts, and I do not see how a few new weird, questionable, and unreliable applications of computing count as a new paradigm shift.

What benefits will these new technologies actually bring? Who will they benefit? Do the researchers know? Does Schwab know? Does anyone know? I certainly don't, and despite reading a bunch of papers that are treating it as the inevitable future, I have not seen them offering any explanation.

There are plenty of other criticisms, and I found a nice summary from ICT Works here, it is a revolutionary view of history, an elite view of history, is based in great man theory, and most importantly, the fourth industrial revolution is a self fulfilling prophecy. One rich asshole wrote a book about some tech he got excited about, and now a generation are trying to build the world around it. The future is not fixed, we do not need to accept these technologies, and I have to believe a better technological world is possible instead of this capitalist infinite growth tech economy as big tech reckons with its midlife crisis, and how to make the internet sustainable as Apple, Google, Microsoft, Amazon, and Facebook, the most monopolistic and despotic tech companies in the world, are running out of new innovations and new markets to monopolize. The reason the big five are jumping on the fourth industrial revolution buzzwords as hard as they are is because they have run out of real, tangible innovations, and therefore run out of potential to grow.

[digitalmarketer-amal]

Amal p k Your Gateway to Top Freelance Digital Marketing Services in Kerala

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Why Choose Best freelance digital marketer in kerala | calicut | kochi?

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What Sets Best freelance digital marketer in kerala | calicut | kochi Apart?

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Success Stories: How Best freelance digital marketer in kerala | calicut | kochi is Transforming Businesses Amaldigiworld.in has helped numerous businesses in Kerala achieve their digital marketing goals. From increasing website traffic to improving search engine rankings, their success stories speak for themselves. Here are a few examples:

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[copperbadge]

I am so close to being done with Royals/Ramblers I can taste it, and it's one of those frustrating situations where the last remaining work to be done is just annoying. I have to write one damn scene, which of course is the most emotionally fraught and difficult one, and then pick from the *counts on fingers* three separate versions of the epilogue I wrote, none of which are very satisfying. I'll probably slam them all together and then sort it out somehow.

And then I definitely have to give the whole thing one more pass before I think about posting, because it's going to clock in at right around 150K words, and I already have notes on continuity issues that need fixing.

Anyway, please enjoy this scene, in which I realized at the same time Gregory and Eddie did what a great joke their names make. (Some brief context -- Joan uses she/her but doesn't like the word "princess", so she chose the gender neutral Princeps as her title.)

Friday evening, when Gregory came on the air for the address, Eddie was sitting next to him, and Joan was leaning on Eddie's shoulder. Her excitement was almost a visible thing; she'd been fussed over that afternoon, Gregory helping her pick out clothing followed by Jerry doing her makeup for camera and Eddie doing a slightly less clumsy job of braiding her hair than she generally did. 

"Good evening, Fons-Askaz, Askazer-Shivadlakia, our neighbors, and our viewers abroad," Gregory said. Behind the camera, Jerry mouthed the words along with him absently. "I'm pleased to greet you all this Friday evening and I hope you're well. I find myself, for the second time in a year, setting aside the usual issues of the day and questions from citizens to talk to you about family...."

His idea had been to talk about Joan's history just a little, then introduce her as the newest Royal, their daughter the Princeps. He could use that as a platform to present to the country his new funding package for adoptive families, meant to encourage adoption and support children coming out of the foster system. Each half of that would hopefully make the other half seem less random.

It went pretty smoothly; Eddie chimed in at all the right moments, and Joan got to say a few words of introduction at the end. After he signed off, he gave her a hug and a forehead-kiss and told her she'd done a great job. 

And then Noah, standing with Monday and Jerry behind the camera in the little studio, said, "Well, you crashed the internet again."

Gregory sighed. "Can't blame Eddie this time, can we?" 

"It was only the tourism website, and it wasn't on purpose," Eddie said. 

"He was always breaking my stuff when we were kids," Monday said.

"Nope, this one's all Joan," Noah replied. "As soon as you introduced her as your daughter, traffic started spiking -- palace website, tourism website, and every royals' Photogram."

"Katie in Communications says told you so," Jerry said, already on the phone with her.

"Joan's Photogram is down, looks like bandwidth-suck. And there goes mine, and yours," Noah said, nodding at Gregory. "There's two hashtags trending, PrincessJoan and PrincepsJoan." 

"Let me call my guy at Photogram," Eddie said, taking his phone out. 

"You have a guy just like, at Photogram?" Monday asked.

"Yeah, he handles my requests, I send him sausages," Eddie answered. 

"How is it you simultaneously live in the 22nd century and the 14th?" Monday asked. 

"Have him kill the Princess hashtag," Noah suggested.

"It's fine," Joan said. "They can use it for now, it'll keep things, um." She narrowed her eyes, searching for the word. "Segmented. Spread out the discussion a little."

"Someone's been reading my data analytics memos," Gregory said. 

"You leave 'em out," she pointed out. 

"Good news is people seem excited," Noah continued. "The hashtag's glitching, it's moving so fast, but overall pretty positive," he added.

"Well, we knew this would be intense," Gregory said. Joan, studying her own phone, squeaked. "Joan?" 

"Mas Corbin tagged me," she said, with possibly the most excitement they'd seen from her, at least since her first trip in the Jaguar. 

"The footballer?" Gregory asked, confused.

"Who?" Noah and Eddie chorused. 

"He's a Shivadh footballer, I think he's playing in Ireland right now," Gregory said, and his voice took on a slight edge as he considered some of the reasons a football player might mention his daughter. "What did he say?" 

"Dedicating my next game to my new Princeps JoanMac, long may she reign," Joan read, and Gregory relaxed. "Congrats to Gin&Tonic, she's cute as a button. Mas Corbin thinks I'm cute!"

"Gin and Tonic?" Gregory asked, and then said, "Gregory and Theophile," right as Eddie and Monday both began to laugh. "How did neither of us think of that before?"

"You get used to it," Noah said to Joan. "All kinds of famous people are going to have opinions on you."

"What do I do?!"

"Gram him back," Noah said. "Comment and say thanks and that you're a fan and you'll be watching the game."

"I'm gonna have to do a video with some gin and tonic recipes," Eddie said, as Noah and Joan debated the best wording for her response. Gregory leaned back in his chair, exhaling, and let the chaos happen around him for a minute. 

[m2iconsulting]

Impact Assessment in Microfinance: Driving Sustainable Growth

Introduction

Microfinance plays a pivotal role in empowering low-income individuals and small businesses by providing them with access to financial services. However, to ensure that microfinance initiatives are truly effective, it is crucial to conduct thorough impact assessments. At M2i Consulting, we specialize in evaluating the effectiveness of microfinance programs and their contribution to sustainable development. This blog explores the importance, methods, and outcomes of impact assessment in microfinance.

Why Impact Assessment Matters

Impact assessment in microfinance helps stakeholders understand whether financial inclusion efforts are achieving their intended goals. It provides insights into:

The socio-economic upliftment of borrowers

The effectiveness of credit accessibility

The sustainability of microfinance institutions (MFIs)

The improvement in income generation and livelihood

By systematically measuring these aspects, MFIs can refine their strategies, enhance their services, and ensure long-term benefits for borrowers.

Key Methods of Impact Assessment

M2i Consulting employs various methodologies to conduct impact assessments, ensuring comprehensive and reliable results. Some of the most widely used approaches include:

Baseline and Endline Surveys

These surveys track changes in income, savings, and business growth before and after availing microfinance services.

Randomized Control Trials (RCTs)

RCTs compare groups that have received microfinance interventions with those that have not, ensuring an unbiased assessment of impact.

Qualitative Research Methods

Focus group discussions and in-depth interviews help gauge borrowers' perspectives and experiences.

Social Performance Metrics

These indicators measure financial literacy, women empowerment, and social mobility resulting from microfinance initiatives.

Outcomes of Effective Impact Assessment

When microfinance institutions implement robust impact assessment practices, they can achieve:

Enhanced Decision-Making: Data-driven insights help optimize loan structures and financial products.

Increased Transparency: Stakeholders, including investors and regulators, gain confidence in the institution’s operations.

Greater Financial Inclusion: Identifying gaps and addressing them leads to more inclusive financial services.

Improved Borrower Success Rates: Borrowers benefit from better-tailored financial solutions, leading to improved repayment rates and financial stability.

M2i Consulting: Your Partner in Microfinance Impact Assessment

At M2i Consulting, we leverage data analytics, field research, and industry expertise to conduct impactful microfinance assessments. Our mission is to ensure that microfinance interventions create lasting positive changes in the lives of the underserved.

By implementing structured impact assessments, microfinance institutions can drive sustainable growth and empower communities effectively. Contact M2i Consulting today to learn how our tailored assessment solutions can elevate your microfinance initiatives.

Conclusion

Impact assessment is a crucial element in the microfinance sector, ensuring that financial services truly benefit those in need. Through systematic evaluation methods, institutions can refine their approaches and maximize positive social and economic impacts. M2i Consulting remains committed to providing industry-leading impact assessment services to drive meaningful change in the microfinance landscape.

[formulaphoe]

a deep dive into endurance racing

wec for beginners

image source: british gq

the fia world endurance championship (wec) is a racing discipline where speed meets strategy, and drivers push their limits for hours on end. if you're new to this exhilarating world, or if you've been following it from a distance, we're going to explore everything you need to know about this thrilling motorsport.

what is wec?

image source: dailysportscar

the wec, established in 2012, is an international series of endurance races organised by the fédération internationale de l'automobile (fia). it brings together the best manufacturers and drivers from around the globe, testing not just their speed, but also their ability to endure the grueling demands of long-distance racing. each race can last anywhere from six to 24 hours, with teams often swapping drivers and strategising pit stops to keep their cars in peak condition.

key features

endurance racing format: unlike traditional races that might only last a couple of hours, wec events are marathons. the races include the iconic 24 hours of le mans, a test of stamina, skill, and strategy, held annually since 1923. other races in the championship include six-hour events at various tracks around the world.

diverse categories: the wec features several classes of cars, including le mans prototype (lmp) and grand touring (gt) categories. each class has its own unique set of regulations and performance characteristics, making for an exciting mix on the track

global reach: the championship hosts races in various countries, providing fans with a chance to experience a multitude of different tracks and cultures. from the rolling hills of spa-francorchamps in belgium to the iconic circuit de la sarthe in france, each location brings its own challenges and charm.

evolution of wec

image source: wec-magazin

the history of the wec is a fascinating one. it replaced the previous intercontinental le mans cup and aimed to revitalize interest in endurance racing. the early years saw fierce competition, particularly in the lmp1 class, which featured powerful hybrid prototypes from manufacturers like audi, porsche, and toyota. these teams showcased cutting-edge technology, blending performance with environmental considerations.

as the years progressed, regulations changed, leading to the introduction of the le mans daytona h (lmdh) class, which aims to bring more manufacturers into the fold. this class allows for greater technical freedom while ensuring that costs remain manageable, making it more accessible for teams looking to compete at the highest level.

iconic races and legendary teams

image source: autosport

one of the standout features of wec is its iconic races. the 24 hours of le mans is undoubtedly the crown jewel, drawing massive crowds and significant media attention. winning at le mans is considered one of the highest honours in motorsport, and teams prepare for it all year round.

aside from le mans, other races like the 6 hours of silverstone and the 6 hours of fuji have become staples in the endurance racing calendar. legendary teams such as audi, porsche, and toyota have built a rich legacy in these events, each with their own stories of triumph and heartache.

the role of technology

image source: pit lane

technology plats a massive role in wec racing. cars are equipped with hybrid powertrains, advanced aerodynamics, and sophisticated data analytics. this focus on innovation not only pushes the boundaries of performance on the track, but also helps manufacturers develop technologies that can be applied to road cars too. the crossover between motorsport and everyday vehicles is a hallmark of wec's philosophy, blending sustainability with speed.

sustainability and the future

as we move towards a more environmentally-conscious future, the wec has made significant strides in promoting sustainability. with the introduction of hybrid technology and plans for fully electric racing, the championship is at the forefront of a green revolution in motorsport. this focus on eco-friendliness doesn't sacrifice the excitement and competitiveness that fans crave; instead, it enhances the sport's relevance in a changing world.

how to get involved

image source: racer

whether you're a die-hard motorsport enthusiast or a casual fan, getting involved in the wec can be incredibly rewarding. attending a race is an experience like no other. the atmosphere is electric, and the camaraderie among fans is palpable. for those who prefer to enjoy the action from home, wec races are broadcast worldwide, often featuring comprehensive coverage that highlights not just the racing, but also the stories behind the teams and drivers that make up the sport.

sources

"fia world endurance championship." fia wec, www.fiawec.com/en/

"fia world endurance championship." wikipedia, 9 aug. 2024, en.wikipedia.org/wiki/FIA_World_Endurance_Championship

"wec beginner's guide: about the fia wec." wec-magazin, www.wec-magazin.com/features/about-the-fia-wec/

"fia world endurance championship." federation internationale de l'automobile, www.fia.com/events/world-endurance-championship/season-2023/fia-world-endurance-championship

"the world of wec: a beginner's guide to endurance racing." circuit of the americas, 1 sept. 2023, www.circuitoftheamericas.com/blog/2023/9/1/the-world-of-wec-a-beginners-guide-to-endurance-racing/

"history of the wec." wec-magazin, www.wec-magazin.com/features/history-of-the-wec/

if any errors or typos are noticed, PLS PLS point them out via comment, ask, or dm. if there is a specific topic you would like me to cover, send in an ask and i'll look into it!

[vague-humanoid]

I first heard about ghost artists in the summer of 2017. At the time, I was new to the music-streaming beat. I had been researching the influence of major labels on Spotify playlists since the previous year, and my first report had just been published. Within a few days, the owner of an independent record label in New York dropped me a line to let me know about a mysterious phenomenon that was “in the air” and of growing concern to those in the indie music scene: Spotify, the rumor had it, was filling its most popular playlists with stock music attributed to pseudonymous musicians—variously called ghost or fake artists—presumably in an effort to reduce its royalty payouts. Some even speculated that Spotify might be making the tracks itself. At a time when playlists created by the company were becoming crucial sources of revenue for independent artists and labels, this was a troubling allegation.

At first, it sounded to me like a conspiracy theory. Surely, I thought, these artists were just DIY hustlers trying to game the system. But the tips kept coming. Over the next few months, I received more notes from readers, musicians, and label owners about the so-called fake-artist issue than about anything else. One digital strategist at an independent record label worried that the problem could soon grow more insidious. “So far it’s happening within a genre that mostly affects artists at labels like the one I work for, or Kranky, or Constellation,” the strategist said, referring to two long-running indie labels.* “But I doubt that it’ll be unique to our corner of the music world for long.”

By July, the story had burst into public view, after a Vulture article resurfaced a year-old item from the trade press claiming that Spotify was filling some of its popular and relaxing mood playlists—such as those for “jazz,” “chill,” and “peaceful piano” music—with cheap fake-artist offerings created by the company. A Spotify spokesperson, in turn, told the music press that these reports were “categorically untrue, full stop”: the company was not creating its own fake-artist tracks. But while Spotify may not have created them, it stopped short of denying that it had added them to its playlists. The spokesperson’s rebuttal only stoked the interest of the media, and by the end of the summer, articles on the matter appeared from NPR and the Guardian, among other outlets. Journalists scrutinized the music of some of the artists they suspected to be fake and speculated about how they had become so popular on Spotify. Before the year was out, the music writer David Turner had used analytics data to illustrate how Spotify’s “Ambient Chill” playlist had largely been wiped of well-known artists like Brian Eno, Bibio, and Jon Hopkins, whose music was replaced by tracks from Epidemic Sound, a Swedish company that offers a subscription-based library of production music—the kind of stock material often used in the background of advertisements, TV programs, and assorted video content.

For years, I referred to the names that would pop up on these playlists simply as “mystery viral artists.” Such artists often had millions of streams on Spotify and pride of place on the company’s own mood-themed playlists, which were compiled by a team of in-house curators. And they often had Spotify’s verified-artist badge. But they were clearly fake. Their “labels” were frequently listed as stock-music companies like Epidemic, and their profiles included generic, possibly AI-generated imagery, often with no artist biographies or links to websites. Google searches came up empty.

In the years following that initial salvo of negative press, other controversies served as useful distractions for Spotify: the company’s 2019 move into podcasting and eventual $250 million deal with Joe Rogan, for example, and its 2020 introduction of Discovery Mode, a program through which musicians or labels accept a lower royalty rate in exchange for algorithmic promotion. The fake-artist saga faded into the background, another of Spotify’s unresolved scandals as the company increasingly came under fire and musicians grew more emboldened to speak out against it with each passing year.

Then, in 2022, an investigation by the Swedish daily Dagens Nyheter revived the allegations. By comparing streaming data against documents retrieved from the Swedish copyright collection society STIM, the newspaper revealed that around twenty songwriters were behind the work of more than five hundred “artists,” and that thousands of their tracks were on Spotify and had been streamed millions of times.

[ghnosis]

48/115 interviews coded!

I realized I never explained what coding means! dry academic stuff under the cut:

per Kathy Charmaz, "coding means categorizing segments of data with a short name that simultaneously summarizes and accounts for each piece of data. your codes show how you select, separate, and sort data to begin an analytic accounting of them." so what I do is I take the transcript of the interview and I read it line by line, and then I create some short little codes to help me describe what is going on in the data. this is called initial coding.

in practice, it looks like this:

I'm doing this by hand in Excel bc the software I *should* be using (NVivo) costs $475/year LMFAOOO

some of these codes, like TikTok or Year Zero or genderqueer, are used so I can quickly give statistics. this is how I know most of my interviewees are nonbinary/genderqueer/genderfluid/etc.

codes also show me emerging trends in data. for example, a lot of you used the word "flamboyant" or "theatrical" when I asked you if Ghost felt queer to you. a looooot of you talked about religious trauma, which I hadn't expected!

codes also help me understand you better, and explain you to academics. some codes are called in vivo codes (that's where NVivo gets its name), which are codes for things like your own personal definitions of things (like 'edgy' or 'queer' or 'goofy'), ghoul or Papa nicknames (insider knowledge/shorthands), or words like "shipping" that come from wider fandom.

once I get through the first round of coding, I'll take a break from the data for a while and go back to literature. this will be focused - some of you are linking the figure of Satan with queerness, for example, so I'll find some literary analysis that does the same thing (Per Faxneld's 2011 text Satanic Feminism is invaluable for this). I'll also be reading more about methodology, to make sure that I'm not just operating on hunches and cherry-picking data. I've been doing a lot of reading on feminist standpoint theory and queer theory as its own methodology, for example.

my plan, and we'll see how this pans out, is to write my methodology chapter and my literature review/introduction chapter after my first pass of coding, then go back to the data/transcripts with fresh eyes for coding round 2. this gets called "focused coding" sometimes. they follow trends I found in the data. again per Charmaz, "Focused coding checks your preconceptions about the topic." coding round 2 is when I'll probably bite the bullet and get NVivo, because I'll need software that lets me look across data better than Excel does. but! focused coding will be a problem for another day, lol.

[elementramarketing]

Fuel Your Growth with Performance Marketing

Turn clicks into customers with laser-focused strategies and real-time results.

Introduction: Marketing That Delivers, Not Just Promises

In today’s fast-paced digital landscape, businesses no longer have the luxury of spending blindly on ads and waiting for miracles. What they need is performance marketing—a results-driven approach that focuses on conversions, not just impressions. It's data-backed, ROI-focused, and scalable, making it the future of modern marketing.

🎯 What is Performance Marketing?

Performance marketing is a digital strategy where advertisers pay only for measurable results—be it clicks, leads, sales, or app installs. Unlike traditional branding methods, performance marketing demands proof. Every campaign is trackable, every rupee spent is accountable.

Key components include:

Pay-Per-Click (PPC) advertising

Affiliate marketing

Social media paid campaigns

Native and display ads

Retargeting & programmatic advertising

💡 Why Businesses Love Performance Marketing

Performance marketing offers powerful benefits for brands across industries:

✅ Cost-Effective – No upfront lump sums; pay only for outcomes ✅ Trackable & Transparent – Live dashboards show real-time performance ✅ Highly Targeted – Reach only your ideal audience with pinpoint accuracy ✅ Scalable – Start small, test, and grow based on results ✅ Optimized for ROI – Every ad is backed by metrics that matter

From startups to big brands, everyone wants results—and this strategy delivers.

📈 Lead Generation: The Lifeline of Sales

No leads = no business. Performance marketing supercharges your sales funnel with high-quality, intent-driven leads across platforms:

Google Search & Display Network

Meta (Facebook/Instagram) Ads

LinkedIn for B2B targeting

YouTube & OTT for awareness-based targeting

Landing pages with integrated lead capture forms

By using tools like A/B testing, heatmaps, and behavioral tracking, marketers ensure that visitors convert—not just click.

🔧 Tools & Techniques that Drive Results

The magic lies in optimization. A great campaign uses:

Advanced analytics (Google Analytics, Meta Pixel, UTM tracking)

Retargeting to re-engage bounced traffic

Conversion Rate Optimization (CRO) for better lead quality

Funnel building with precise customer journeys

AI and automation for budget control and ad performance

When campaigns are backed by smart data, results are not left to chance.

🧠 Who Should Use Performance Marketing?

E-commerce brands looking to scale sales

Startups wanting fast market penetration

Service-based businesses aiming for qualified leads

Real estate, education, fintech, and healthcare sectors for niche targeting

Agencies managing multiple client portfolios

🌟 Final Word: Measure More. Waste Less.

Marketing budgets are shrinking, but expectations are growing. Performance marketing strikes the perfect balance by focusing only on what works. It’s not about shouting louder—it’s about reaching smarter.

🔗 Ready to generate real leads and real growth?

Start your performance marketing journey today!

👉 [Click Here] to explore high-ROI digital strategies!

[indigosteeloracle]

Graph Analytics Edge Computing: Supply Chain IoT Integration

Graph Analytics Edge Computing: Supply Chain IoT Integration

By a veteran graph analytics practitioner with decades of experience navigating enterprise implementations

Introduction

Graph analytics has emerged as a transformative technology for enterprises, especially in complex domains like supply chain management where relationships and dependencies abound. However, the journey from concept to production-grade enterprise graph analytics can be fraught with challenges.

In this article, we'll dissect common enterprise graph analytics failures and enterprise graph implementation mistakes, evaluate supply chain optimization through graph databases, explore strategies for petabyte-scale graph analytics, and demystify ROI calculations for graph analytics investments. Along the way, we’ll draw comparisons between leading platforms such as IBM graph analytics vs Neo4j and Amazon Neptune vs IBM graph, illuminating performance nuances and cost considerations at scale.

Why Do Enterprise Graph Analytics Projects Fail?

The graph database project failure rate is surprisingly high despite the hype. Understanding why graph analytics projects fail is critical to avoid repeating the same mistakes:

Poor graph schema design and modeling mistakes: Many teams jump into implementation without a well-thought-out enterprise graph schema design. Improper schema leads to inefficient queries and maintenance nightmares. Underestimating data volume and complexity: Petabyte scale datasets introduce unique challenges in graph traversal performance optimization and query tuning. Inadequate query performance optimization: Slow graph database queries can cripple user adoption and ROI. Choosing the wrong platform: Mismatched technology selection, such as ignoring key differences in IBM graph database performance vs Neo4j, or between Amazon Neptune vs IBM graph, can lead to scalability and cost overruns. Insufficient integration with existing enterprise systems: Graph analytics must seamlessly integrate with IoT edge computing, ERP, and supply chain platforms. Lack of clear business value definition: Without explicit enterprise graph analytics ROI goals, projects become academic exercises rather than profitable initiatives.

These common pitfalls highlight the importance of thorough planning, vendor evaluation, and realistic benchmarking before embarking on large-scale graph analytics projects.

you know, https://community.ibm.com/community/user/blogs/anton-lucanus/2025/05/25/petabyte-scale-supply-chains-graph-analytics-on-ib Supply Chain Optimization with Graph Databases

Supply chains are inherently graph-structured: suppliers, manufa

[jollystrangernymph]

From Chips to Clouds: Exploring Intel's Role in the Next Generation of Computing

Introduction

The world of computing is evolving at breakneck speed, and at the forefront of this technological revolution is Intel Corp. Renowned for its groundbreaking innovations in microprocessors, Intel's influence extends far beyond silicon chips; it reaches into the realms of artificial intelligence, cloud computing, and beyond. This article dives deep into Intel's role in shaping the next generation of computing, exploring everything from its historical contributions to its futuristic visions.

From Chips to Clouds: Exploring Intel's Role in the Next Generation of Computing

Intel has long been synonymous with computing power. Founded in 1968, it pioneered the microprocessor revolution that transformed personal computing. Today, as we transition from conventional machines to cloud-based systems powered by artificial intelligence and machine learning, Intel remains a critical player.

The Evolution of Intel’s Microprocessors A Brief History

Intel's journey began with the introduction of the first commercially available microprocessor, the 4004, in 1971. Over decades, it has relentlessly innovated:

1970s: Introduction of the 8086 architecture. 1980s: The rise of x86 compatibility. 1990s: Pentium processors that made personal computers widely accessible.

Each evolution marked a leap forward not just for Intel but for global computing capabilities.

Current Microprocessor Technologies

Today’s microprocessors are marvels of engineering. Intel’s current lineup features:

Core i3/i5/i7/i9: Catering to everything from basic tasks to high-end gaming. Xeon Processors: Designed for servers and high-performance computing. Atom Processors: Targeting mobile devices and embedded applications.

These technologies are designed with advanced architectures like Ice Lake and Tiger Lake that enhance performance while optimizing power consumption.

Click for more info Intel’s Influence on Cloud Computing The Shift to Cloud-Based Solutions

In recent years, businesses have increasingly embraced cloud computing due to its scalability, flexibility, and cost-effectiveness. Intel has played a crucial role in this transition by designing processors optimized for data centers.

Intel’s Data Center Solutions

Intel provides various solutions tailored for cloud service providers:

Intel Xeon Scalable Processors: Designed specifically for workloads in data centers. Intel Optane Technology: Enhancing memory performance and storage capabilities.

These innovations help companies manage vast amounts of data efficiently.

Artificial Intelligence: A New Frontier AI Integration in Everyday Applications

Artificial Intelligence (AI) is becoming integral to modern computing. From smart assistants to advanced analytics tools, AI relies heavily on processing power—something that Intel excels at providing.

Intel’s AI Initiatives

Through initiat