Looker VS QuickVerify

• 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.

• Ease of Use
  QuickVerify offers a user-friendly interface that simplifies the process of verifying employment and education information, making it easily accessible for users with different levels of technical expertise.
• Accurate Results
  The platform provides reliable and accurate verification results, which can help companies make informed decisions based on verified data.
• Time Efficiency
  QuickVerify significantly reduces the time required to verify an applicant's credentials when compared to traditional methods, streamlining the pre-employment screening process.
• Cost-Effective
  By utilizing digital verification methods, QuickVerify can be more cost-effective than manual verification processes, offering potential savings for businesses.

Possible disadvantages

• Privacy Concerns
  There can be privacy issues related to handling sensitive personal information, making it crucial for QuickVerify to adhere to strict data protection laws and regulations.
• Limited Reach
  The service may have limitations in verifying data from smaller institutions or companies that are not part of their network, which can hinder verification for some candidates.
• Dependence on Network Operators
  The effectiveness of QuickVerify largely depends on the cooperation and integration with network operators and institutions, which can sometimes lead to delays or incomplete verifications.
• Service Costs
  While cost-effective, the service still requires a financial investment that may not be feasible for all businesses, especially smaller enterprises with limited budgets.

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Looker Review

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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 QuickVerify since Mar 2021.