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🚀 Stop Merging Data Manually in Excel! 📊 😫 Still copying and pasting data from multiple tables? There’s a smarter way. ⚡ Excel’s Consolidate feature lets you combine data from multiple ranges into a single summary in just a few clicks—saving time and reducing errors. ✅ Merge data faster... show more

Tips Excel

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558,039 просмотров • 3 месяцев назад •via X (Twitter)

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📊 Master the TEXTSPLIT Function in Excel Still separating text manually? The TEXTSPLIT function lets you split text into multiple columns or rows instantly using a delimiter such as commas, spaces, hyphens, or other characters. Why TEXTSPLIT is Useful ✅ Clean messy datasets faster ✅ Separate names, emails, and addresses automatically ✅ Save time on repetitive text processing ✅ Improve data preparation for analysis ✅ Replace manual Text-to-Columns workflows (Save this for later).

📊 Master the TEXTSPLIT Function in Excel Still separating text manually? The TEXTSPLIT function lets you split text into multiple columns or rows instantly using a delimiter such as commas, spaces, hyphens, or other characters. Why TEXTSPLIT is Useful ✅ Clean messy datasets faster ✅ Separate names, emails, and addresses automatically ✅ Save time on repetitive text processing ✅ Improve data preparation for analysis ✅ Replace manual Text-to-Columns workflows (Save this for later).

Tips Excel | AI Productivity

18,207 просмотров • 3 месяцев назад

What if your personal data became an asset you actually owned? In this May 2026 AMA, Matrix AI Network explores one of the most important questions facing AI, Web3, and the future digital economy: Who owns the data that powers artificial intelligence? As AI models continue to improve, the next major bottleneck is no longer computing power—it is access to high-quality, verified human data. The discussion covers how personal biodata can become a valuable digital asset, how data quality is measured, and why future AI companies may depend directly on users as data providers. Topics include: ✅ Biodata as a new asset class ✅ AI-grade data quality scoring ✅ Wearable devices for raw data ✅ Data ownership and monetization models ✅ Preventing fake data and device spoofing ✅ Real-world applications in healthcare, sports science and mental wellness ✅ Hypnus and the future biodata ecosystem ✅ Project direction The future may not belong to companies that own data. It belongs to the people who create it. Watch now 👇 #AI #Web3 #DataOwnership

What if your personal data became an asset you actually owned? In this May 2026 AMA, Matrix AI Network explores one of the most important questions facing AI, Web3, and the future digital economy: Who owns the data that powers artificial intelligence? As AI models continue to improve, the next major bottleneck is no longer computing power—it is access to high-quality, verified human data. The discussion covers how personal biodata can become a valuable digital asset, how data quality is measured, and why future AI companies may depend directly on users as data providers. Topics include: ✅ Biodata as a new asset class ✅ AI-grade data quality scoring ✅ Wearable devices for raw data ✅ Data ownership and monetization models ✅ Preventing fake data and device spoofing ✅ Real-world applications in healthcare, sports science and mental wellness ✅ Hypnus and the future biodata ecosystem ✅ Project direction The future may not belong to companies that own data. It belongs to the people who create it. Watch now 👇 #AI #Web3 #DataOwnership

Matrix AI Network

61,436 просмотров • 3 месяцев назад

A data analyst makes ~$70k a year. But here’s the ugly truth: 70% of that time is wasted on grunt work ... copying, cleaning, merging, and stuffing data into Excel. Painful, right? Don’t worry… I recorded a 10-min video showing how this AI agent can turn 3 hours of pain into a 20-minute, clean, 100% hallucination-free report. Let me show you how you can do this... To prove it, I’m giving 100 people free access to Sheet0. Like + repost + comment “ACCESS” to try it 👇

A data analyst makes ~$70k a year. But here’s the ugly truth: 70% of that time is wasted on grunt work ... copying, cleaning, merging, and stuffing data into Excel. Painful, right? Don’t worry… I recorded a 10-min video showing how this AI agent can turn 3 hours of pain into a 20-minute, clean, 100% hallucination-free report. Let me show you how you can do this... To prove it, I’m giving 100 people free access to Sheet0. Like + repost + comment “ACCESS” to try it 👇

Beginnersblog

29,247 просмотров • 11 месяцев назад

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

85,107 просмотров • 1 год назад

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below I’ll send you the details.

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below I’ll send you the details.

Deepak Gupta

44,243 просмотров • 5 месяцев назад

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below. I'll send you the details.

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below. I'll send you the details.

Deepak Gupta

17,102 просмотров • 3 месяцев назад

This is a big leap forward to doing real data analysis with GPT-4o. It still can't quite handle the way many people use spreadsheets (Excel formulas, etc.) but it is pretty impressive. You can zoom into spreadsheets and ask about cells, modify graphs, etc. I trimmed 45 seconds.

This is a big leap forward to doing real data analysis with GPT-4o. It still can't quite handle the way many people use spreadsheets (Excel formulas, etc.) but it is pretty impressive. You can zoom into spreadsheets and ask about cells, modify graphs, etc. I trimmed 45 seconds.

Ethan Mollick

1,746,171 просмотров • 2 лет назад

YOUR AI AGENT CAN NOW COLLECT DATA FROM ALMOST ANY WEBSITE X, YouTube, Reddit, random websites, basically whatever you need for research, analytics or monitoring. Here are 3 GitHub tools that let your agent pull the data for you. 1. Agent-Reach Bundles tools for working with different platforms in one place. X, YouTube, Reddit, GitHub and more. 2. Patchright Enhanced Works through the browser with Playwright. You can listen to the requests a website makes and pull the data you need through a script. So if a website doesn’t have a proper API, you still have a way to get the data. 3. Scrapling A general purpose tool for pulling data from web pages. And the best part is that you can give all of this to your AI agent. For example: “Collect posts from 100 X accounts from the last month, find the most popular topics and analyze what’s working.” Or: “Collect reviews about this product from Reddit and YouTube and summarize the main complaints.” You tell the agent what data you need → it writes the code → collects the data → gives you the result. Basically, you’re giving your agent the ability to pull data from almost anywhere on the web. That opens up a whole different level of stuff you can automate.

YOUR AI AGENT CAN NOW COLLECT DATA FROM ALMOST ANY WEBSITE X, YouTube, Reddit, random websites, basically whatever you need for research, analytics or monitoring. Here are 3 GitHub tools that let your agent pull the data for you. 1. Agent-Reach Bundles tools for working with different platforms in one place. X, YouTube, Reddit, GitHub and more. 2. Patchright Enhanced Works through the browser with Playwright. You can listen to the requests a website makes and pull the data you need through a script. So if a website doesn’t have a proper API, you still have a way to get the data. 3. Scrapling A general purpose tool for pulling data from web pages. And the best part is that you can give all of this to your AI agent. For example: “Collect posts from 100 X accounts from the last month, find the most popular topics and analyze what’s working.” Or: “Collect reviews about this product from Reddit and YouTube and summarize the main complaints.” You tell the agent what data you need → it writes the code → collects the data → gives you the result. Basically, you’re giving your agent the ability to pull data from almost anywhere on the web. That opens up a whole different level of stuff you can automate.

TeddyCEO

192,982 просмотров • 3 дней назад

The era of manually analyzing data will come to an end. AI can now do a lot of this automatically. It's a huge time saver. I do data analysis for a living, and I'm a huge fan of writing Jupyter notebooks to do it all, but it's now hard to justify manually writing code that you can generate in a few seconds. I still check everything manually, but breaking down datasets into tables and charts is now 10x easier than it's ever been. Here is a video where I'm using Retool. I load a dataset and generate a few charts as quickly as I can think. The speed at which we can go from one idea to a working solution is astonishing.

The era of manually analyzing data will come to an end. AI can now do a lot of this automatically. It's a huge time saver. I do data analysis for a living, and I'm a huge fan of writing Jupyter notebooks to do it all, but it's now hard to justify manually writing code that you can generate in a few seconds. I still check everything manually, but breaking down datasets into tables and charts is now 10x easier than it's ever been. Here is a video where I'm using Retool. I load a dataset and generate a few charts as quickly as I can think. The speed at which we can go from one idea to a working solution is astonishing.

Santiago

70,812 просмотров • 11 месяцев назад

AI is transforming the way businesses operate 🤖. It helps companies work faster, cut costs, and make smarter decisions. From automating repetitive tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI can’t function without data 📊. Massive amounts of high-quality data are required to train models and make them effective. Right now, most of this data is controlled by a few centralized giants 🔒, making it expensive, siloed, and out of reach for smaller businesses and innovators. This is where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By combining decentralized storage with AI infrastructure powered by blockchain, OORT makes data open, secure, and accessible to everyone. It’s building a foundation where businesses of all sizes can tap into AI’s full potential and compete in the AI-driven economy 🚀

AI is transforming the way businesses operate 🤖. It helps companies work faster, cut costs, and make smarter decisions. From automating repetitive tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI can’t function without data 📊. Massive amounts of high-quality data are required to train models and make them effective. Right now, most of this data is controlled by a few centralized giants 🔒, making it expensive, siloed, and out of reach for smaller businesses and innovators. This is where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By combining decentralized storage with AI infrastructure powered by blockchain, OORT makes data open, secure, and accessible to everyone. It’s building a foundation where businesses of all sizes can tap into AI’s full potential and compete in the AI-driven economy 🚀

Sky Wee

58,239 просмотров • 10 месяцев назад

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

Santiago

142,696 просмотров • 1 год назад

$BTC Statistical Study using Claude - A Beginner's Workflow Here's an example of a z-score study on $BTC - still tinkering so don't take this as overtly useful information but the creation of a dashboard for the visualization of statistical data is phenomenal. my current workflow: > import $BTC time data - .csv file (can get this information from multiple venues - Binance is where I got mine) > creating bins - if you have a larger data set - you can use recent data to prevent overt bias in the long direction or filter consolidation and trending regime data into separate bins for statistical analysis - however, you will have to define thresholds and determine what that entails. > defining metrics in Claude that you want to use for statistical analysis e.g. for z-score what is it based on and what type of calculation? make sure you understand the calculations being performed for any metrics that you are doing a study for and modify them accordingly. > prompting Claude to do a statistical analysis with specific instructions and then tell it to create visualization for this. I've been messing around with this and I'm seriously impressed by the output.

$BTC Statistical Study using Claude - A Beginner's Workflow Here's an example of a z-score study on $BTC - still tinkering so don't take this as overtly useful information but the creation of a dashboard for the visualization of statistical data is phenomenal. my current workflow: > import $BTC time data - .csv file (can get this information from multiple venues - Binance is where I got mine) > creating bins - if you have a larger data set - you can use recent data to prevent overt bias in the long direction or filter consolidation and trending regime data into separate bins for statistical analysis - however, you will have to define thresholds and determine what that entails. > defining metrics in Claude that you want to use for statistical analysis e.g. for z-score what is it based on and what type of calculation? make sure you understand the calculations being performed for any metrics that you are doing a study for and modify them accordingly. > prompting Claude to do a statistical analysis with specific instructions and then tell it to create visualization for this. I've been messing around with this and I'm seriously impressed by the output.

Stoic

19,782 просмотров • 1 год назад

I’ve had my team of volunteers manually checking the NoBlogs data released by the deaf liberal DEI hire fed DataRepublican (small r) today….and we already know it’s incomplete. We’ve been tracking NoBlogs for years using human subject matter experts, not shitty AI analysis. We have our own dataset. And there’s data missing from the set released by Data Republican. This is just one example. Doing human analysis takes time. But shitty AI analysis by a liberal DEI hire will never defeat the work of people who do research on the ground and go undercover with Antifa and the far left.

I’ve had my team of volunteers manually checking the NoBlogs data released by the deaf liberal DEI hire fed DataRepublican (small r) today….and we already know it’s incomplete. We’ve been tracking NoBlogs for years using human subject matter experts, not shitty AI analysis. We have our own dataset. And there’s data missing from the set released by Data Republican. This is just one example. Doing human analysis takes time. But shitty AI analysis by a liberal DEI hire will never defeat the work of people who do research on the ground and go undercover with Antifa and the far left.

Karlyn Borysenko, anti-communist cult leader

26,030 просмотров • 18 дней назад

This April AMA is here. In this session, the team breaks down how biodata (like sleep and brain data) can be standardized, valued, and turned into real-world assets (RWA). What you’ll learn: 1. The 4 key milestones for Biodata RWA in 2026 2. Why sleep data is the first step in building a data economy 3. How data becomes structured, scored, and monetizable 4. The role of MAN token in rewarding and settling data usage 5. How privacy is protected with distributed storage & computation 6. Ownership models: sell vs license your data 7. Why institutions (AI, pharma, insurance) need verified biodata In the future, your data won’t just exist, it will work for you.

This April AMA is here. In this session, the team breaks down how biodata (like sleep and brain data) can be standardized, valued, and turned into real-world assets (RWA). What you’ll learn: 1. The 4 key milestones for Biodata RWA in 2026 2. Why sleep data is the first step in building a data economy 3. How data becomes structured, scored, and monetizable 4. The role of MAN token in rewarding and settling data usage 5. How privacy is protected with distributed storage & computation 6. Ownership models: sell vs license your data 7. Why institutions (AI, pharma, insurance) need verified biodata In the future, your data won’t just exist, it will work for you.

Matrix AI Network

15,296 просмотров • 4 месяцев назад

Introducing Minara AI - your ultimate AI assistant for digital finance, like having a 24/7 personal CFO. Just ask your questions, get powerful market insights, and turn them into actionable strategies—backed by real-time data. Instantly. Overall, Minara can provides: ✅ Profressional analysis & insights as you need on crypto, stocks, RWA, DeFi,NFTs and more. (Far better than ChatGPT-5 and Grok-4) ✅ 50+ real-time data sources, including on-chain, financial, social and prediction data. ✅ Vibe trading crypto and tokenized stocks in one place. ✅ Create any agentic financial workflow with prompts. ✅ Manage your portfolio and track profit&loss ✅ Financial planning & forecasting (integrating Polymarket) No learning curve. For everyone. Join the waitlist and experience the revolution NOW👇

Introducing Minara AI - your ultimate AI assistant for digital finance, like having a 24/7 personal CFO. Just ask your questions, get powerful market insights, and turn them into actionable strategies—backed by real-time data. Instantly. Overall, Minara can provides: ✅ Profressional analysis & insights as you need on crypto, stocks, RWA, DeFi,NFTs and more. (Far better than ChatGPT-5 and Grok-4) ✅ 50+ real-time data sources, including on-chain, financial, social and prediction data. ✅ Vibe trading crypto and tokenized stocks in one place. ✅ Create any agentic financial workflow with prompts. ✅ Manage your portfolio and track profit&loss ✅ Financial planning & forecasting (integrating Polymarket) No learning curve. For everyone. Join the waitlist and experience the revolution NOW👇

Minara AI

231,756 просмотров • 1 год назад

Instagram launches forced Data Collection to use their app If you login and get this prompt, you must accept data all this data collection or you will be promoted to log out and not allowed to use the App Here is a full down of what’s mandatory to give up to use Instagram: Collection and use of personal data: They collect our activity on Instagram (posts, stories, likes, comments, searches, time spent), device info, IP address, contacts (if synced), messages, location (when enabled), demographics, and inferred interests Sharing of data with other Meta companies. They take all the personal data they collected and share across Facebook, WhatsApp, Threads, Oculus, etc. Cross-border transfers of personal data: Your data is sent and stored in the US and other countries where Meta has offices/data centers or partners. Location information: Precise location (GPS when you use features like Stories or check-ins), approximate location from IP/Wi-Fi, and location-based activity history. Stop using META products

Instagram launches forced Data Collection to use their app If you login and get this prompt, you must accept data all this data collection or you will be promoted to log out and not allowed to use the App Here is a full down of what’s mandatory to give up to use Instagram: Collection and use of personal data: They collect our activity on Instagram (posts, stories, likes, comments, searches, time spent), device info, IP address, contacts (if synced), messages, location (when enabled), demographics, and inferred interests Sharing of data with other Meta companies. They take all the personal data they collected and share across Facebook, WhatsApp, Threads, Oculus, etc. Cross-border transfers of personal data: Your data is sent and stored in the US and other countries where Meta has offices/data centers or partners. Location information: Precise location (GPS when you use features like Stories or check-ins), approximate location from IP/Wi-Fi, and location-based activity history. Stop using META products

Wall Street Apes

265,441 просмотров • 2 месяцев назад

American bought a Vizio Smart TV from Walmart. He took it home only to find you cannot use the TV without a Walmart account logged in You cent even turn it on and get past the first screen This is because Walmart bought Vizio and by having you sign in with your account they can like the data collected to you This TV collects everything and links it to your account - Contact details - Payment information - Subscription information - Account authentication and security information The optional data that most people just click next through is the really invasive data capturing, it includes - Viewing Data - Activity Data - Mobile App Data - Mobile Streaming Data It also uses built-in technology to analyze what’s playing on the TV in real time, including: - Audio and video programming, ads and gaming content - Content from connected devices like HDMI - Third-party apps like streaming services for movies, shows, episodes, channels, launch events - Device state details: volume, channel, picture controls, inputs, power on/off But it doesn’t stop there, it also collects - Basic identifiers: Name, email, phone, address, account credentials - Device/online identifiers: Device IDs, advertising IDs, IP/MAC addresses, model/serial numbers, firmware, Wi-Fi access points, cookies - Activity Data: Settings, inputs, clicks, impressions, operational/performance data, some content interaction details - Commercial/financial info: Purchases, subscriptions, warranties, payment cards - Internet/network activity: How you use the apps, sites, ads, and services - Mobile app and streaming data if you use the Vizio app You agree to have all this data collected from you just because you bought a TV…..

American bought a Vizio Smart TV from Walmart. He took it home only to find you cannot use the TV without a Walmart account logged in You cent even turn it on and get past the first screen This is because Walmart bought Vizio and by having you sign in with your account they can like the data collected to you This TV collects everything and links it to your account - Contact details - Payment information - Subscription information - Account authentication and security information The optional data that most people just click next through is the really invasive data capturing, it includes - Viewing Data - Activity Data - Mobile App Data - Mobile Streaming Data It also uses built-in technology to analyze what’s playing on the TV in real time, including: - Audio and video programming, ads and gaming content - Content from connected devices like HDMI - Third-party apps like streaming services for movies, shows, episodes, channels, launch events - Device state details: volume, channel, picture controls, inputs, power on/off But it doesn’t stop there, it also collects - Basic identifiers: Name, email, phone, address, account credentials - Device/online identifiers: Device IDs, advertising IDs, IP/MAC addresses, model/serial numbers, firmware, Wi-Fi access points, cookies - Activity Data: Settings, inputs, clicks, impressions, operational/performance data, some content interaction details - Commercial/financial info: Purchases, subscriptions, warranties, payment cards - Internet/network activity: How you use the apps, sites, ads, and services - Mobile app and streaming data if you use the Vizio app You agree to have all this data collected from you just because you bought a TV…..

Wall Street Apes

231,718 просмотров • 1 месяц назад