data.world

Website

data.world

Pricing URL

Official data.world Pricing

$ Details

-

Release Date

2015 January

Categories

#Data Integration #Data Dashboard #AI Platform #Data Management Platform (DMP)

Startup details

Country

United States

State

Texas

City

Austin

Founder(s)

Brett Hurt

Employees

50 - 99

D (Programming Language)

Website

dlang.org

Pricing URL

-

$ Details

Release Date

-

Categories

#Programming Language #OOP #Generic Programming Language #Dynamic Programming Language

data.world features and specs

• Collaborative Environment
  data.world provides a platform for teams to collaborate on data projects in real-time, making it easier for data scientists, analysts, and enthusiasts to work together and share insights.
• Integration Capabilities
  The platform supports integrations with popular tools and services like Excel, Tableau, and Python, making it easier to import, export, and manipulate data across various applications.
• Extensive Dataset Catalog
  data.world offers a vast collection of public datasets, empowering users to find and leverage data from a wide range of sources for their projects.
• Querying Tools
  Users can execute SQL queries directly on the data.world platform, enabling powerful data analysis and transformations within the environment.
• User-Friendly Interface
  The platform features an intuitive user interface that makes it accessible for users with varying levels of technical expertise.

Possible disadvantages of data.world

• Pricing
  While data.world offers a free tier, more advanced features and functionality require a paid subscription, which might be cost-prohibitive for individuals or smaller organizations.
• Learning Curve
  Despite its user-friendly interface, there is still a learning curve associated with fully utilizing all of the platform's features, particularly for users who are not familiar with SQL or data analysis tools.
• Performance Limitations
  For very large datasets or complex analytical operations, the platform may experience performance constraints, potentially requiring users to rely on more powerful, external data processing tools.
• Data Privacy Concerns
  As with any cloud-based platform, there are inherent data privacy and security concerns. Users must be cautious about the sensitivity of the data they upload and ensure compliance with relevant regulations.
• Feature Parity with Competitors
  While data.world offers many great features, some users might find that other data collaboration platforms provide more advanced or specialized tools that better suit their needs.

D (Programming Language) features and specs

• Performance
  D is designed to be a high-performance systems programming language, offering performance comparable to C and C++ through native machine code compilation.
• Expressiveness
  D features a rich standard library and modern language constructs, such as garbage collection, first-class arrays, and advanced templating, making it easier to write expressive and maintainable code.
• Memory Safety
  D offers optional garbage collection along with manual memory management. This hybrid approach can help in developing safer applications by reducing memory-related errors.
• Interoperability
  D can easily interoperate with C API, enabling seamless integration with existing C libraries and systems. It also supports better C++ interoperability compared to other languages.
• Built-in Unit Testing
  D has built-in support for unit tests, allowing developers to write and run tests as part of the language itself, facilitating test-driven development.
• Concurrency
  D offers built-in concurrency support with message passing, similar to the actor model found in languages like Erlang, making it easier to write concurrent and parallel programs.

Possible disadvantages of D (Programming Language)

• Adoption
  D is not as widely adopted as other languages like C, C++, or Java. This limited adoption means fewer libraries, frameworks, and community support.
• Toolchain Maturity
  While D's compilers and tools have improved over the years, they may still lack the maturity and feature set of more established languages, which can affect developer productivity.
• Learning Curve
  D's richness and combination of paradigms (such as imperative, object-oriented, and functional programming) can present a steep learning curve for new developers.
• Garbage Collection
  Although D offers optional garbage collection, its reliance on it for memory safety might be seen as a drawback for real-time system development where deterministic memory management is crucial.
• Ecosystem
  The ecosystem for D is less vibrant compared to more popular languages, leading to potentially fewer third-party libraries, tools, and resources.
• Standard Library Documentation
  The standard library documentation can be inconsistent or less comprehensive compared to other languages, making it difficult for developers to fully utilize all features of the language.

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