#Streaming Data

[weekendance]

“In forte crescita il pubblico dei fantasmi”. Già lo scorso anno eravamo rimasti interdetti di fronte ai “38 dei 158 milioni di brani globalmente disponibili che hanno generato zero riproduzioni nel 2022” – per non contare gli altri e numerosissimi interrogativi circa la sostenibilità in generale del carrozzone dello streaming. E come giustamente nota il tizio qui sopra, non è ancora neanche cominciato l’assalto dei “brani creati da AI” (che in larga parte, si suppone, sostituiranno tutto quell’oceano di “lo-fi hip hop per studiare e rilassarsi” che già di suo, va detto, aveva delle discrete caratteristiche post-umane). ROB ABELOW

[raziakhatoon]

 Data Engineering Concepts, Tools, and Projects

All the associations in the world have large amounts of data. If not worked upon and anatomized, this data does not amount to anything. Data masterminds are the ones. who make this data pure for consideration. Data Engineering can nominate the process of developing, operating, and maintaining software systems that collect, dissect, and store the association’s data. In modern data analytics, data masterminds produce data channels, which are the structure armature.

How to become a data engineer:

 While there is no specific degree requirement for data engineering, a bachelor's or master's degree in computer science, software engineering, information systems, or a related field can provide a solid foundation. Courses in databases, programming, data structures, algorithms, and statistics are particularly beneficial. Data engineers should have strong programming skills. Focus on languages commonly used in data engineering, such as Python, SQL, and Scala. Learn the basics of data manipulation, scripting, and querying databases.

 Familiarize yourself with various database systems like MySQL, PostgreSQL, and NoSQL databases such as MongoDB or Apache Cassandra.Knowledge of data warehousing concepts, including schema design, indexing, and optimization techniques.

Data engineering tools recommendations:

    Data Engineering makes sure to use a variety of languages and tools to negotiate its objects. These tools allow data masterminds to apply tasks like creating channels and algorithms in a much easier as well as effective manner.

1. Amazon Redshift: A widely used cloud data warehouse built by Amazon, Redshift is the go-to choice for many teams and businesses. It is a comprehensive tool that enables the setup and scaling of data warehouses, making it incredibly easy to use.

One of the most popular tools used for businesses purpose is Amazon Redshift, which provides a powerful platform for managing large amounts of data. It allows users to quickly analyze complex datasets, build models that can be used for predictive analytics, and create visualizations that make it easier to interpret results. With its scalability and flexibility, Amazon Redshift has become one of the go-to solutions when it comes to data engineering tasks.

2. Big Query: Just like Redshift, Big Query is a cloud data warehouse fully managed by Google. It's especially favored by companies that have experience with the Google Cloud Platform. BigQuery not only can scale but also has robust machine learning features that make data analysis much easier. 3. Tableau: A powerful BI tool, Tableau is the second most popular one from our survey. It helps extract and gather data stored in multiple locations and comes with an intuitive drag-and-drop interface. Tableau makes data across departments readily available for data engineers and managers to create useful dashboards. 4. Looker:  An essential BI software, Looker helps visualize data more effectively. Unlike traditional BI tools, Looker has developed a LookML layer, which is a language for explaining data, aggregates, calculations, and relationships in a SQL database. A spectacle is a newly-released tool that assists in deploying the LookML layer, ensuring non-technical personnel have a much simpler time when utilizing company data.

5. Apache Spark: An open-source unified analytics engine, Apache Spark is excellent for processing large data sets. It also offers great distribution and runs easily alongside other distributed computing programs, making it essential for data mining and machine learning. 6. Airflow: With Airflow, programming, and scheduling can be done quickly and accurately, and users can keep an eye on it through the built-in UI. It is the most used workflow solution, as 25% of data teams reported using it. 7. Apache Hive: Another data warehouse project on Apache Hadoop, Hive simplifies data queries and analysis with its SQL-like interface. This language enables MapReduce tasks to be executed on Hadoop and is mainly used for data summarization, analysis, and query. 8. Segment: An efficient and comprehensive tool, Segment assists in collecting and using data from digital properties. It transforms, sends, and archives customer data, and also makes the entire process much more manageable. 9. Snowflake: This cloud data warehouse has become very popular lately due to its capabilities in storing and computing data. Snowflake’s unique shared data architecture allows for a wide range of applications, making it an ideal choice for large-scale data storage, data engineering, and data science. 10. DBT: A command-line tool that uses SQL to transform data, DBT is the perfect choice for data engineers and analysts. DBT streamlines the entire transformation process and is highly praised by many data engineers.

Data Engineering  Projects:

Data engineering is an important process for businesses to understand and utilize to gain insights from their data. It involves designing, constructing, maintaining, and troubleshooting databases to ensure they are running optimally. There are many tools available for data engineers to use in their work such as My SQL, SQL server, oracle RDBMS, Open Refine, TRIFACTA, Data Ladder, Keras, Watson, TensorFlow, etc. Each tool has its strengths and weaknesses so it’s important to research each one thoroughly before making recommendations about which ones should be used for specific tasks or projects.

  Smart IoT Infrastructure:

As the IoT continues to develop, the measure of data consumed with high haste is growing at an intimidating rate. It creates challenges for companies regarding storehouses, analysis, and visualization. 

  Data Ingestion:

Data ingestion is moving data from one or further sources to a target point for further preparation and analysis. This target point is generally a data storehouse, a unique database designed for effective reporting.

 Data Quality and Testing: 

Understand the importance of data quality and testing in data engineering projects. Learn about techniques and tools to ensure data accuracy and consistency.

 Streaming Data:

Familiarize yourself with real-time data processing and streaming frameworks like Apache Kafka and Apache Flink. Develop your problem-solving skills through practical exercises and challenges.

Conclusion:

Data engineers are using these tools for building data systems. My SQL, SQL server and Oracle RDBMS involve collecting, storing, managing, transforming, and analyzing large amounts of data to gain insights. Data engineers are responsible for designing efficient solutions that can handle high volumes of data while ensuring accuracy and reliability. They use a variety of technologies including databases, programming languages, machine learning algorithms, and more to create powerful applications that help businesses make better decisions based on their collected data.

[michigantopnews]

Michigan Sues Roku - Streaming Giant Pushes Back on Child Privacy Claims

Attorney General Dana Nessel accuses Roku of illegally collecting children’s personal data; Roku disputes allegations, citing privacy protections. Michigan Attorney General Sues Roku Over Alleged Data Privacy Violations LANSING, Michigan — Michigan Attorney General Dana Nessel has filed a federal lawsuit against Roku, Inc., accusing the streaming platform of violating federal and state laws…

[fruitfulchaos]

GO BURN CD'S. GO FILL PHYSICAL DISCS. PIRATE EVERYTHING. DOWNLOAD BOOKS, MUSIC, GAMES, SHOWS, FILMS. SAVE SNAPSHOTS ON WAYBACK. FUCK THE MEDIA COMPANIES. STREAMING ISN'T FOREVER. PURCHASE ISN'T OWNERSHIP. FORGE THE OWNERSHIP WITH YOUR OWN HANDS. MAKE MEDIA YOUR BITCH. STAY VIGILANT. I LOVE YOU.

[lungthief]

based on a joke from last night’s @savedatateam aai1 stream, i present: the rise and fall of a miles edgeworth midwest princess. a look behind the scenes:

[probablyasocialecologist]

Amazon’s recent decision to stop allowing people to download copies of their Kindle e-books to a computer has vindicated some of my longstanding beliefs about digital media. Specifically, that it doesn’t exist and you don’t own it unless you can copy and access it without being connected to the internet. The recent move by the megacorp and its shiny-headed billionaire CEO Jeff Bezos is another large brick in the digital wall that tech companies have been building for years to separate consumers from the things they buy—or from their perspective, obtain “licenses” to. Starting Wednesday, Kindle users will no longer be able to download purchased books to a computer, where they can more easily be freed of DRM restrictions and copied to e-reader devices via USB. You can still send ebooks to other devices over WiFi for now, but the message the company is sending is one tech companies have been telegraphing for years: You don’t “own” anything digital, even if you paid us for it. The Kindle terms of service now say this, explicitly. “Kindle Content is licensed, not sold, to you,” meaning you don’t “buy a book,” you obtain a “digital content license.”

[...]

Amazon is far from alone in this long-running trend towards eliminating digital ownership. For many people, digital distribution and streaming services have already practically ended the concept of owning and controlling your own media files. Spotify is now almost synonymous with music for some younger generations, having strip-mined the music industry from both ends by demonetizing more than 60% of the artists on its platform and pushing algorithmic slop while­ simultaneously raising subscription fees.  Of course, surrendering this control means being at the complete mercy of Amazon and other platforms to determine what we can watch, read, and listen to—and we’ve already seen that these services frequently remove content for all sorts of reasons. Last October, one year after the Israeli military began its campaign of genocide in Gaza, Netflix removed “Palestinian Stories,” a collection of 19 films featuring Palestinian filmmakers and characters, saying it declined to renew its distribution license. Amazon also once famously deleted copies of 1984 off of people’s Kindles. Fearing piracy, many software companies have moved from the days of “Don’t Copy That Floppy” to the cloud-based software-as-a-service model, which requires an internet connection and charges users monthly subscription fees to use apps like Photoshop. No matter how you look at it, digital platforms have put us on a path to losing control of any media that we can’t physically touch. How did we get here? 

28 February 2025

[mint-mango]

he’s immune to criticism your honor

[chainsawctopus]

The princess slayyyyyed

Drew all the different princesses @savedatateam got so far on their first stream! I am once again asking you to go support them right now they're great guys please I swear

[ilikedetectives]

I love how Emma encouraged Dev to go for Minthara romance scene in Act 1 during Dev's stream, and both of their reactions when the explicit scene played out should be framed in a museum. "I'm worth it love" to "Oh my God!!" in the span of a few mins.

Meanwhile Dev's face turns RED in less than a min lol

[ironworked]

Given the reasons behind 911's move from FOX to ABC (x, x), its ratings and viewers for this season so far, the currently developing spin-off, its year to year evolution, 911 vs its timeslot rivals and other ABC shows (shown below), and this ranking of this year's broadcast shows so far

911 year-to-year evolution:

vs ABC shows (this season):

vs timeslot rivals:

...

[earlykatgetsthesparrow]

@itspetrovichworld u want this? (I'll tag Chara later)

[rhapsoddity]

What is VSAU!Martyns 'power's? I didn't even know you had a desgin for him :○

He can hop into a pocket dimension with whatever he has on him at the time! He reappear ls exactly where he disappeared, as long as it's unobstructed. If it is, he's stuck in his pocket dimension until he can

It's useful to dodge punches by wholeass disappearing for the impact. Once he got caught in a building collapse and was trapped in there for three days, though he had his groceries so he didn't starve,, he was just super bored tho

[chaos0pikachu]

"why is 4mins getting a second season? who asked for this"

y'all hating b/c 4mins is that bitch, Megan Thee Stallion Yuki Chiba in Mumashi, fries dipped in a chocolate milkshake, Cher in Clueless

and like, also one of VIU's top performing shows on the platform but saying 4mins was having a hot girl summer is funnier so

[bartholomewtheant]

I got feelings about rats smp lore!!!!!

Just got done with the Hamrat stream and my god, the switch from "is this happening or is it a play" the chaos, trolley problem, people getting accused, Ren mumbling about not being a captain

And the sudden switch to martyn's personal lore in the end, how this has all gotten a little bit too real.

[smilegirl64]

It just hit me that Data started his journey with dreaming on the deck of the Enterprise, with his cat and his potted plant and his paintings because that's home for him. He starts the journey in an amalgamation of home and then flies off the Enterprise but we never see him leave the area and it's like a kid riding their bike for the first time and he's just getting his bearings and-