InetSoft vs Looker Comparison

Recently, users on G2 Crowd roundly endorsed the superiority of Style Intelligence over competing BI platform Looker. From the user level to the administrative, from data mashups to customization, InetSoft's Style Intelligence outranked it's competitor in nearly every category.

G2 Crowd is a Chicago-based firm that collects reviews on other companies' software products, targeting the CRM and marketing automation markets in additiona to business intelligence software. It prides itself on being an unbiased platform where real users share their feedback.

Data from peer reviews, web traffic, and other social media data from LinkedIn, Twitter etc. are fed into a formula that gives more weight to peer reviews over others.

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#1 Ranking: Read how InetSoft was rated #1 for user adoption in G2's user survey-based index Read More

A Good Alternative to Looker

InetSoft users on the G2 Crowd website express their appreciation for InetSoft's ability to be deployed in a matter of hours, as opposed to deployments stretching on for weeks that are typical of other BI platforms. On the other hand, users of Looker have complained of its inability to handle large amounts of data as it is more geared toward accommodating smaller workloads.

Other limitations of Looker include not being able to modify the look of complex visualizations, and having to port data using outdated methodologies such as an ETL processes.

InetSoft Style Intelligence rated higher in Big Data Services, Data Visualization, Ease of Use, and Ease of Setup. In addition, InetSoft is rated higher in Customization and Breadth of Partner applications because of its ability to combine data sources and provide easily customizable data modeling.

Unfortunately, Lookers interface sets out to accomplish self-service but falls short of ranking higher than InetSoft in its abilities to search data, filter data columns and calculate fields, all functions which empower the end user to continue in their data discovery.

It is because of this that InetSoft is better suited for collaboration and workflow to accomplish anything else performance related. InetSoft outperforms Looker in WYSIWYG report Design and Integrating APIs and also won high ratings in User, Role and Access Management.

why select InetSoft
“Flexible product with great training and support. The product has been very useful for quickly creating dashboards and data views. Support and training has always been available to us and quick to respond.
- George R, Information Technology Specialist at Sonepar USA

What Are the Drawbacks of Google Looker App?

Google Looker, like any software application, has its share of drawbacks. While it offers numerous benefits for data analysis and visualization, users may encounter several challenges or limitations when using the platform. Here are some potential drawbacks of Google Looker:

  1. Learning Curve: One significant drawback of Google Looker is its steep learning curve. While the platform aims to make data analytics accessible to non-technical users, mastering its features and functionalities can take time. Users may need to invest significant resources in training and onboarding to effectively utilize the platform, especially if they are not familiar with SQL or data modeling concepts.

  2. Complexity of Data Modeling: Google Looker relies heavily on data modeling to create interactive dashboards and reports. While this approach offers flexibility and customization options, it also introduces complexity, especially for users with limited experience in data modeling. Creating and maintaining data models can be challenging, requiring a deep understanding of the underlying data structure and business requirements.

  3. Performance Issues: Depending on the size and complexity of the data being analyzed, users may experience performance issues when querying and visualizing data in Google Looker. Slow query execution times and laggy dashboard loading can hinder productivity and impact user experience, especially when dealing with large datasets or complex analytical queries.

  4. Limited Integration Options: While Google Looker offers integration with various data sources and platforms, it may not support all the integrations required by users. Lack of support for certain data sources or applications can limit the platform's usefulness and force users to rely on manual data extraction and preprocessing workflows.

  5. Cost: Google Looker is a premium product, and its pricing structure may be prohibitive for some organizations, especially small businesses and startups. The cost of licenses, user seats, and additional features can add up quickly, making it challenging for organizations with limited budgets to justify the investment in the platform.

  6. Dependency on Internet Connectivity: Google Looker is a cloud-based platform, which means users rely on stable internet connectivity to access and use the application. Any disruptions in internet connectivity can prevent users from accessing their data and dashboards, impacting productivity and decision-making processes.

  7. Limited Customization Options: While Google Looker offers a range of customization options for dashboards and reports, some users may find the platform's customization capabilities limiting. Advanced customization features, such as custom visualizations or fine-grained control over dashboard layout, may be lacking compared to other data visualization tools.

  8. Security and Compliance Concerns: Storing sensitive data in the cloud and granting access to third-party applications like Google Looker can raise security and compliance concerns for some organizations. Ensuring data security, privacy, and compliance with regulatory requirements can be challenging when using cloud-based analytics platforms like Google Looker.

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