Looker VS Waves

• Powerful Data Modeling
  Looker uses LookML, a proprietary modeling language, making it possible to transform raw data into meaningful metrics and dimensions, providing deep insights without needing SQL expertise.
• Ease of Use
  Its intuitive user interface enables non-technical users to create visualizations and reports with relative ease, reducing the workload on data teams.
• Customization
  Looker offers extensive customization options for data exploration and visualization, allowing dashboards and reports to be tailored to specific user needs.
• Embedded Analytics
  Provides robust capabilities for embedding analytics into applications or portals, broadening the scope of data-driven decision-making throughout the organization.
• Real-time Data
  Supports real-time data analytics by querying live data, which ensures up-to-date insights and helps in making timely decisions.
• Integrations
  Looker integrates seamlessly with a wide range of databases and cloud data warehouses, including Google BigQuery, Amazon Redshift, and Snowflake.

Possible disadvantages

• Learning Curve
  LookML, while powerful, can be complex for beginners who are not already familiar with data modeling or SQL, resulting in a steep learning curve.
• Cost
  Looker can be expensive, especially for small businesses, as pricing is typically based on the number of users and the data volume processed.
• Performance
  Query performance can sometimes be slow, especially with complex data models and large data sets, which may impact the user experience.
• Customization Constraints
  While Looker offers great customization, certain advanced customizations may require significant expertise and time, posing a potential barrier.
• Limited Offline Capabilities
  Looker is primarily designed for online use, so it lacks robust offline capabilities, which can be a limitation for users who need access to data in situations without internet connectivity.

• User-Friendly Interface
  Waves offers a simple and intuitive interface that is easy to navigate, making it suitable for both beginners and experienced users.
• Custom Token Creation
  Allows users to create their own custom tokens with minimal technical knowledge, enabling more individuals and businesses to leverage blockchain technology.
• Fast Transactions
  Offers quick transaction speeds, reducing the time users spend waiting for confirmations compared to other platforms.
• Low Transaction Fees
  Provides low-cost transaction fees, making it an economical choice for users who execute frequent transactions.
• Decentralized Exchange
  Includes a built-in decentralized exchange (DEX) that allows users to trade a variety of cryptocurrencies directly from the platform while maintaining control over their assets.

Possible disadvantages

• Limited Smart Contract Functionality
  Waves' smart contract capabilities are not as advanced or flexible as those offered by some other platforms like Ethereum, which may limit potential use cases.
• Adoption and Ecosystem
  Despite its potential, Waves has not achieved the same level of adoption or ecosystem support as some larger blockchain platforms, potentially limiting network effects and development.
• Centralization Concerns
  Critics have pointed out that certain aspects of the network, such as the governance model, might not be as decentralized as some other blockchains.
• Variable Token Quality
  With the ease of creating custom tokens, there's a risk of poor-quality or scam tokens circulating, which requires users to exercise caution.
• Community Size
  The community size is smaller compared to other big players in the blockchain space, which might affect support and user-driven innovation.

No analysis of Waves yet.

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• edit home page to add folder section

  Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the... Source: over 3 years ago

• Stars, tables, and activities: How do we model the real world?

  Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins... - Source: dev.to / almost 4 years ago

• dbt for Data Quality Testing & Alerting at FINN

  We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / over 4 years ago

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Tracking Waves since Mar 2021.