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Microsoft Ponders Leaving China, Blogspot Blocking and Other Non-issues
China is in the news for many reasons but when it comes to the Internet one of the the main stays is the blocking of websites, persecuting of bloggers that cause social unrest with their writings and making foreign internet companies comply with national laws in order to keep the Chinese internet pure. Today a sum up of what has been happening in that field recently.
Microsoft ponders reconsidering it’s China business
At the UN Internet Governance Forum in Athens, Fred Tipson, senior policy counsel for Microsoft was quoted by the BBC, as saying,
“Concerns over the repressive regime might force it [Microsoft] to reconsider its business in China.
He also said, “Things are getting bad… and perhaps we have to look again at our presence there,” he told a conference in Athens. “We have to decide if the persecuting of bloggers reaches a point that it’s unacceptable to do business there.”
Microsoft is active with its blogger platform MSN Spaces in China and as such, pondering to leave China would constitute canceling this service. I don’t think they intend to stop trying to sell Windows XP and the coming Vista.
Blocking and Blogging
Blogspot, Google’s platform for bloggers has been blocked again. It had been accessible for a couple of months and someone decided to pull the IP again.
Competition wise this sounds like good news for Chinese blog service providers like Bokee and Blogcn as this means less competition. Having been blocked before in China it probably won’t make much of a difference though. If MSN spaces were to leave China it would be better.
Chinese Internet research company Iresearch differs and states,
“Blog real name mechanism can virtually achieve the development of blog industry and guarantee the harmonious development of Internet culture.” (Quote is from their newsletter)
I wonder how independent their research is.
There is a big chance the measures will never materialize, as until now has happened with the idea to make it mandatory for posters of video’s to Chinese versions of Youtube, like chúng tôi to get a permit first.
If the Blog Real Name Registration would be implemented this could mean a renewed interest in using overseas blog service providers as long as they are not blocked of course.
China and Censorship, a Non-issue
To top it off I admit all the above is not true, or at least part of it. At the forum in Athens the Chinese government representative, Yang Xiaokun, denied all censorship allegations made by major human rights groups.
“We do not have restrictions at all,” he said. “Some people say that there are journalists in China that have been arrested. We have hundreds of journalists in China, very few have been arrested. But there are criminals in all societies and we have to arrest them. But these are legal problems. It has nothing to do with freedom of expression.”
Gemme van Hasselt is an Internet Marketing Consultant, living in Shanghai, China. His musings on life can be found on China Snippets
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This website has a welcome package worth up to $1200. This bonus basket targets casino players. If your goal is to bet on sport, the site matches your deposit for a maximum of $100. Additionally, you qualify for a 7% cashback on your betting losses.Wild Casino
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Wild Casino is a Bitcoin casino, meaning it supports crypto for payments. You can use Bitcoin, BNB Coin, Cardano, Solana, USD Coin or Ethereum. If you’re not into crypto, though, don’t worry. You can still use credit/debit card options like Visa, MasterCard or wire transfer.Gxmble
Most non gamstop casinos share one thing in commonality—huge bonuses. Gxmble is no different. Armed with a welcome package worth up to €2,500, this is the kind of casino you want to join if you’re a high roller.
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Best Meme Coins For 2023: DOGE Falling, PEPE Comesback, and BEASTS Coin Rising With Its Referral Scheme
Man, by nature, is interested in varieties. It is nearly hard to keep individuals engaged with a particular location, item, or even method of making money. Moreover, in the world of cryptocurrencies, where there are hundreds of options, people are continually looking for fresh and simple methods to profit from them. In this context, two new meme coins, BEASTS Coin (BEASTS) with its referral scheme, and Pepe Coin (PEPE), which is currently experiencing a surge, are ushering in a new era of meme coins and will overtake Elon Musk’s favourite, Dogecoin (DOGE), which is currently facing a downfall.Is DOGE Fading?
Starting with Dogecoin, its value has fallen by 16.52% in the last month. While its value continues to decline, there has been a significant movement of Dogecoin worth $335 million in the past week, creating concerns within the Dogecoin community. Although determining the exact importance of these transactions is difficult, many Dogecoin experts believe that wealthy crypto investors, commonly known as crypto whales, are looking to diversify their investments due to Dogecoin’s lack of profitability in 2023. Consequently, thousands of investors have been impacted by this trend and are already selling their Dogecoin to minimise their losses.PEPE’s Bullish Comeback
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It’s worth noting that Pepe Coin made its debut on the Ethereum network in April 2023 and quickly gained market traction. By May 5, 2023, its market capitalization had surpassed $1 billion, thereby initiating a new wave of frog-themed meme currencies.BEASTS Coin: A Promising Meme Coin
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This article was published as a part of the Data Science Blogathon.
Over the past few years, Snowflake has grown from a virtual unknown to a retailer with thousands of customers. Businesses have adopted Snowflake as migration from on-premise enterprise data warehouses (such as Teradata) or a more flexibly scalable and easier-to-manage alternative to an existing cloud data warehouse (such as Amazon Redshift or Google BigQuery).Snowflake: Data lake or Data Warehouse?
Data lakes offer low-cost object storage of raw data and rely on external query tools to analyze large datasets using highly available computing resources. Because they access a file system rather than a structured format, data lakes are not highly performant without optimization. But once optimized, they can be extremely cost-effective, especially at scale. They are also well equipped to process streaming data.
The Data warehouse stores structured data in a proprietary format for analytical access through a tightly coupled query layer. Computational speed is high compared to a non-optimized data lake but is also more expensive.So, where does the Snowflake fit?
With other data warehouses, Snowflake requires a proper data format, works with structured and semi-structured (but not unstructured) data, and requires its query engine. However, it differs from a traditional data warehouse in two key aspects:
1. It is only offered in the cloud
2. It separates the storage from the elastic compute layer
These improvements initially differentiated Snowflake in the market from Teradata and Redshift. However, each has tried to match those attributes—Teradata with its Vantage cloud service and Amazon with Redshift, which separates compute and storage. As a result, these services now share these two properties with cloud data lakes, which can add to the flurry of confusion about when to use which.Where to store the data for cost optimization?
So Snowflake is not a data lake. But is there any reason not to store all your information on it and rely on its ability to process data with SQL quickly? One reason you should consider it is the cost.
Of course, the cost is essential when deciding how to use different analytics platforms. Using Snowflake to run complex queries on large volumes of data at high speed can significantly increase costs.
Snowflake charges based on how long the Virtual Data Warehouse (VDW) is running, plus VDW size (number of cores) and prepaid feature set (Enterprise, Standard, or Business-Critical). A given VDW, the rates are identical to the load on the VDW. This differs from the data lake, which offers spot pricing; a cheaper instance can handle a smaller bag.
Snowflake processes data in its proprietary format, and data transformation for Snowflake acceptance can be costly. Because receiving data streams creates a continuous load, it can keep the Snowflake VDW meter running 24/7. Since Snowflake does not charge differently for a 5% or 80% load of a given virtual datastore size, these costs can be high.
• Computing snowflakes is more expensive than running the same job in a data lake.
So there is a real risk of Snowflake running into an inexorable cost scenario. When you realize that you may have too much data stored in Snowflake, it can become even more expensive to get the data out because it needs to be transformed into a different format.
A similar scenario could arise involving your data scientists, who may repeatedly analyze the same or similar data sets as they experiment with different models and test various hypotheses. This is highly computationally intensive. They must be able to connect to the ML or AI tools of their choice and not be locked into a single technology just because a proprietary data format requires it.
For these reasons, relying on Snowflake for all your data analysis needs can be inefficient and expensive. From a business perspective, it may be better to supplement Snowflake with a data lake.Compare Snowflake and Databricks
There are a lot of people who are confused between snowflake and Databricks. How does the Snowflake approach compare to Databricks’ self-proclaimed Lakehouse tool, and how stark are the differences between the two? Check out our Databricks vs Snowflake comparison to find out.
Snowflake + optimized cloud data lake = flexible and affordable analytics
None of the above is meant to disparage Snowflake or to suggest that it shouldn’t be part of your overall solution. Snowflake is a handy data warehouse and should be considered a way to provide predictable and fast analytics performance. However, by incorporating it as part of an open, optimized data lake architecture, you can ensure that you get all (or most) of Snowflake’s benefits while keeping your cloud costs under control.
Using an optimized data lake and cloud data warehouse like Snowflake allows companies to apply different patterns to different use cases based on cost and performance requirements.
You can use cheap data lake storage and keep all your data – not just recent or structured data.
Data transformation and preparation are likely much cheaper in a data lake than in Snowflake, especially for streaming data.
You are not limited in choice of query tools and can query the data lake directly or send it to Snowflake as needed. With additional tools such as search engines, time series databases, or ML/AI tools, you retain maximum flexibility and agility to work with the rest of the data as you please.Prepare your Data Lake for Analysis
Manually preparing data in a data lake using tools like AWS Glue or Apache Spark is usually resource-intensive. Here we will use Upsolver’s Data Lake engineering platform. Upsolver provides a low-code, self-service, optimized compute layer on top of your data lake, making it powerful to serve as a cost-effective repository for analytics services.
Upsolver includes data lake engineering best practices to make processing efficient, automating the essential but time-consuming data pipeline work that every data lake requires to function well. It includes:
Converting data into columnar formats with efficient querying like Apache Parquet instead of requiring engines to query raw data.
Continuous file compression ensures performance by avoiding the “small file problem.”
Appropriate data partitioning to speed up query response.
Upsolver uses low-cost compute options such as AWS Spot EC2 instances whenever possible to reduce query costs. This can reduce calculation costs by 10X compared to standard EC2, which is much cheaper than a data warehouse.
Upsolver handles UPSERTS tables correctly, meaning you can continuously load tables from streaming data that stay current as the data and even the schema change.
Use Upsolver to normalize, filter, aggregate, and join data to your liking through a visual SQL IDE to create transformations. Then run these transformations directly in the data lake before writing them to Snowflake (including joins, aggregations, enrichments, etc.) or querying them as an external table from Snowflake’s SQL query engine.
Combining Snowflake with Upsolver’s data-rich data lake gives you the flexibility to run processing where it makes the most sense in terms of cost and choice of analytics tools.
You can even use Upsolver to continuously transform and stream data directly to Snowflake.How to build a real-time streaming architecture using Snowflake, Data Lake Storage, and Upsolver on AWS?
First, and most importantly, be clear about which of your data streams must go to Snowflake and which can be stored in raw format in a lake for other purposes. (Remember not to keep ancient data on Snowflake; Athena is a much better tool for querying large datasets.) Then design the architecture so that the transformed streaming data is automatically sent to Snowflake.
In this reference architecture, Snowflake is only one of several data consumers. Data is optimized (sometimes significantly) for each consumer. In some cases, prepared data is most economically queried on a data lake with a query tool such as Athena; in others, the output is to a specialized data store:
• search analysis or logging (Elasticsearch)
• OLAP (Snowflake) querying
• chart analysis (Neptune)
With an open data lake architecture like this, you keep a single version of the truth in the data lake as raw data, plus you can refine and distribute the data for specific purposes.
1. Upsolver receives data streams and stores them in raw format in a data lake.
2. Data intended for OLAP or ad hoc queries are prepared, cleaned, aggregated, and formatted for direct question by Athena and output to Snowflake for processing and processing.
3. As requests come in from other analytics services, the data is prepared and then delivered to the service.Conclusion
Data lakes are open, more scalable, cost-effective, and can support a broader range of business cases. Now, you can use a codeless data lake engineering platform to create a pipeline to receive, prepare quickly, and format unlimited amounts of streaming data. You can then directly query or send to Snowflake—the best of both worlds.
The Data warehouse stores structured data in a proprietary format for analytical access through a tightly coupled query layer. Computational speed is high compared to a non-optimized data lake but is also more expensive.
Snowflake offers some separation of storage from computing. It cannot be considered a data lake due to its reliance on proprietary data formats and structured storage. A data lake is built on broad access to data and the ability to choose between different compute queries and data tools;
Snowflake charges based on how long the Virtual Data Warehouse (VDW) is running, plus VDW size (number of cores) and prepaid feature set (Enterprise, Standard, or Business-Critical). A given VDW, the rates are identical to the load on the VDW.
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In this article, we will compare the properties of the agile paradigm with those of other models.Waterfall Model vs. the Agile Model
What is Waterfall methodology, and how does it work?
The Waterfall Model is also known as the Liner Sequential Life Cycle Model. Because the Waterfall Model is followed in a sequential sequence, the project development team will only go on to the next phase of development or testing if the previous step has been successfully completed.What is the Agile approach, and how does it work?
Agile methodology is a concept that aids in the software development process by allowing for continuous iteration of development and testing. Unlike the Waterfall paradigm, development and testing are done simultaneously under this methodology. This method helps clients, developers, managers, and testers to communicate more effectively.The Key Difference Between Waterfall and Agile
Agile is a continuous iteration of development and testing in the software development process, while Waterfall is a linear sequential life cycle model.
The Agile technique is noted for its flexibility, while the Waterfall methodology is a regimented software development process.
When comparing the Waterfall and Agile methodologies, the Agile approach is incremental, while the Waterfall is a sequential design process.
Testing is done simultaneously with software development in Agile, while testing is done after the “Build” step in the Waterfall technique.
Agile allows for modifications in project development needs, while Waterfall does not allow for changes once the project is underway.Benefits of the Waterfall Model
It’s one of the simplest models to work with. Each phase has particular deliverables and a review procedure according to its nature.
It works effectively for little projects with simple needs.
Project completion in a shorter amount of time
Both the process and the outcomes are thoroughly recorded.
Method for reorganizing teams that is easily adaptable
When it comes to managing dependencies, this project management style comes in handy.Benefits of the Agile Model
It is a client-focused procedure. As a result, it ensures that the customer is kept informed at all times.
Agile teams are highly motivated and self-organized, therefore development projects are more likely to provide superior results.
The agile software development technique ensures that development quality is maintained.
The whole procedure is predicated on gradual development. As a result, both the customer and the team are aware of what is and is not complete. As a result, the risk of the development process is reduced.Waterfall Model Limitations
It isn’t the best model for a major project.
It is a less effective strategy if the requirement is not apparent from the start.
It’s really tough to return to prior stages and make modifications.
After the development phase is completed, the testing phase begins. As a result, there’s a good likelihood that flaws will be discovered later in development when they’ll be more costly to correct.Agile Model Limitations
For modest development initiatives, this strategy is ineffective.
In order to make crucial choices in a meeting, an expert is required.
When compared to other development approaches, the cost of adopting an agile process is somewhat higher.
If the project manager does not know what result he or she wants, the project might quickly go off course.Differences between the Agile and Waterfall Models
The following is a comparison between Agile and Waterfall methodologies −
AgileWaterfallThe project development lifecycle is divided into sprints.There are many stages to the software development chúng tôi takes a step-by-step chúng tôi waterfall technique is a way of designing in a progressive order.Agile methodologies are noted for their adaptabilityBecause waterfall is a structured software development technique, it may be extremely strict at times.Agile may be thought of as a collection of many chúng tôi development of software will be done as a single project.Agile is a flexible strategy that enables modifications to project development that needs to be made even after the original planning is complete.Once the project development begins, there is no way to change the specifications.Because Agile methodology uses an iterative development approach, planning, development, prototyping, and other software development stages may occur several chúng tôi the Waterfall approach, all project development stages, such as design, development, and testing, are completed once.After each sprint, the test plan is evaluated.During the testing phase, the test strategy is seldom communicated.Agile development is a method of software development in which needs are anticipated to change and evolve over chúng tôi technique is excellent for projects with specific needs and unanticipated modifications.Testing is done simultaneously with software development in the Agile process.The “Testing” step follows the “Build” phase in this technique.Agile presents a product mentality in which the software product meets the requirements of its end users and adapts to their chúng tôi approach demonstrates a project mentality and focuses only on completing the chúng tôi Time & Materials or non-fixed financing, the Agile approach performs incredibly effectively. In fixed-price circumstances, it may create chúng tôi obtaining a risk agreement at the start of the process, it is possible to reduce risk in firm-fixedprice contracts.Small, focused teams with a high level of coordination and synchronization are chúng tôi ability of a team to coordinate and synchronize is severely hampered.Almost every day of a project, the product owner and his team create requirements.Prior to the start of a project, business analysts establish requirements.The test team may easily participate in requirement chúng tôi change in requirements is tough for the test to commence.During the SDLC process, the description of project specifics may be changed at any chúng tôi use the waterfall software development technique, a detailed description is chúng tôi a consequence of the Agile Team’s interchangeability, they work more quickly. Project managers are also unnecessary since the projects are controlled by the whole team.Because the process is usually easy under the waterfall technique, the project manager is needed at every level of the SDLC.Exploratory Programming vs. Agile Model
Agile ModelExploratory ProgrammingEach incrementally delivered portion is built via an iteration following each timebox in an agile paradigm.Exploratory programming is a method for developing unstructured programs.Agile teams, on the other hand, adhere to well-defined and disciplined methods that include systematic requirements gathering and thorough design.Exploratory programming defies software engineering conventions, allowing for unstructured code to be created and evaluated.After each iteration, the Agile model’s primary principle is to provide an incremental version to the client.After development, the program is tested and any defects detected are repaired. This cycle of testing and problem repair continues until the program meets the customer’s expectations.Agile vs. RAD: Which is Better?
Agile ModelRAD ModelThe Agile paradigm discourages the creation of prototypes, preferring instead to focus on the methodical development of each incremental feature at the conclusion of each chúng tôi core concept of RAD is to create rapid and dirty prototypes that are later developed into production-quality code.Agile initiatives logically split the solution down into features that are created and delivered in chúng tôi RAD paradigm focuses on building all of an application’s functionality by doing it poorly at first and then gradually improving the code over time.After each iteration, the Agile team only shows the client finished work.Customers may be shown screen mockups and prototypes by RAD teams, although these may be based on simplifications such as database lookup rather than real calculations.Tiny projects are not ideal for the agile approach since it is difficult to break the project into small components that may be produced progressively.When a corporation hasn’t worked on a project that’s nearly identical, it’s difficult to employ the RAD paradigm since previous code can’t be reused.Incremental Development vs. Agile Development
Agile developmentIncremental developmentEach incrementally delivered portion is built via an iteration following each time box in the Agile paradigm. The Agile model’s core idea is to create agility by eliminating tasks that waste time and chúng tôi software’s requirements are broken down into various modules that may be built and supplied in stages. The basic features are created initially, then additional features are added to the program in consecutive chúng tôi the Agile paradigm, an iteration’s end date is set and cannot be amended. To finish that iteration on schedule, the development team may have to opt to minimize the supplied functionality.There is no set deadline for completing the next iteration in the incremental development methodology.Spiral Model vs. Agile Model
Agile modelSpiral modelThe Agile model’s core idea is to create agility by eliminating tasks that waste time and chúng tôi Spiral model’s fundamental concept is risk chúng tôi Agile strategy emphasizes delivering an increment to the client after each Time-box, resulting in more frequent customer involvement.The spiral model primarily deals with many types of unplanned hazards, however, there is minimal client chúng tôi agile paradigm is best suited for huge projects that can be broken down into tiny chunks and developed progressively over chúng tôi Spiral model is appropriate for projects that are vulnerable to a variety of hazards that are difficult to predict at the outset.Documentation is not used in the agile chúng tôi the Spiral model, proper documentation is essential.
Buying gadget gifts for fellow techies isn’t too difficult: You’ll likely know the things they’ve had their eye on. But there are some gadgets that non-techies will love, too.
The secret with making your choices is to discount the Gadget Factor we all love, and to think about things which will either enhance the pleasure friends and family get from their existing interests and passions, or which make their life easier.
I’ve already covered a couple of areas that will work for many: music and photography.Music
Check out my audio gift guide for recommended headphones and speakers for the music lovers in your life.Photography & videography
Similarly, you don’t need to be a gadget fan to appreciate camera accessories. If someone loves taking photos, check out my photography and videography gift guide.Robot vacuum cleaners
There was a time when giving someone a vacuum cleaner as a gift would not have been appreciated! But these days, a robot vacuum cleaner is a great way to give someone the greatest gift of all: time. If a gadget can take care of the hoovering and mopping, that’s more time someone has to spend doing the things they enjoy.
Robot vacuum cleaners are available at all price levels, but when you’re buying a gift, it’s probably wise to avoid the $100-ish ones. Most tend to start at around $250. Some options worth considering here are:
The latest version of one of the most popular models, suitable for both hard floors and carpets, and particularly good for pet hair.
Stepping up a level, you can get models that combine vacuuming and mopping. Some of these are better than others, but the 360 S7 Pro works well.
Top of the robo-cleaner food chain these days are self-emptying models. Rather than have to empty an onboard bin every two to three days, the dock does that for you, so you only have to empty that bin about once a month. I recently tested, and was impressed by, the Neabot Q11.Coffee warmers
If you have a tea or coffee lover in your life, then a way to keep their drink warm for longer can go down well. You can get both heated coasters and heated mugs – the former are the inexpensive option, while the latter are the best performing.
This heated coaster comes with a matching ceramic mug for a particularly neat appearance, though it can be used with any mug.
Ember makes a range of well-regarded heated mugs, with this stainless steel one the starting point. Other models, like copper, get more expensive.
The ultimate version is a heated travel mug. Again, Ember is the best name for these, with the 12 ounce cup keeping coffee electrically heated at the desired temperature for up to three hours.Smart pet food dispensers
If you have a dog owner or cat staff to buy for, a smart pet food dispenser is a useful gift, while a treat dispenser is a fun one.
An easy way to ensure a cat or small dog is kept fed while away, this model is on a par with more basic ones, but enables the schedule to be set in an app, making it easier to program.
The top-rated treat dispenser on Amazon, this one combines 1080p camera and two-way audio, so someone can talk to their pet while at work or away, as well as see their reactions.Smart sous vide
A sous vide is a really great way to easily get perfectly cooked food every time, and an app-controlled sous vide makes life even easier. Just select the food in the app and it then sends cooking instructions (temperature and time) to the sous vide device.
The Anova Nano is popular, highly rated, and an affordable price. Note that the recipient will need a large cooking pot, too – either a large saucepan or pressure cooker pot.
The Pro offers exactly the same capabilities, but boosts the heating element from 750W to 1200W for faster cooking. Again, a large cooking pot is needed.Smart photo frames
Digital photo frames are a popular choice for grandparents, and although they may be happy with a basic one, they’ll quickly fall in love with a smart model for one simple reason: Other family members can upload photos to it remotely. This means they get a constantly updated stream of family photos.
I reviewed this model last year, and it remains a good option. You’ll want to do the setup for a non-techy, but once you have they don’t need to do a thing – new photos will be displayed automatically as family members upload them. You don’t need to be a techie to send photos to it either – this can be done via an app, a website, or even by email.
Photo: Hert Niks/Unsplash
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