GoodData - Detailed Review

Frequently Asked Questions about GoodData

What are the core features of GoodData’s analytics platform?

GoodData is a versatile analytics platform that supports various use cases, including Analytics as Code (AaC), embedded analytics, and data products. It allows organizations to build customized data solutions that can be embedded into applications, monetized, or used internally to enhance decision-making. Key features include flexible architecture, seamless integration capabilities, and the ability to create customized analytics experiences without traditional BI constraints.

How does GoodData integrate AI and machine learning into its analytics?

GoodData integrates AI and machine learning through several features. For instance, the FlexConnect protocol allows businesses to connect to any data source, including APIs and machine learning models, and integrate predictive insights directly into analytics workflows. This enables real-time decision-making and the application of custom computations using languages like Python or Rust. Additionally, GoodData’s AI Assistant and Smart Search features use natural language interfaces to simplify complex analytics and make insights more accessible to non-technical users.

Can non-technical users interact with data on GoodData?

Yes, GoodData is designed to be user-centric, making it accessible to both technical users and business stakeholders. The Smart Search and AI Assistant features allow users to interact with data using natural language queries, eliminating the need for specialized technical knowledge. For example, users can ask questions like “What were the revenue trends last year?” and the platform will automatically generate relevant visualizations and allow for further refinements.

How does GoodData handle data security and privacy?

Security is a top priority for GoodData. The platform has robust privacy protocols in place to protect sensitive information. It also offers full transparency and auditability of all AI models, ensuring compliance with regulatory requirements and building trust with stakeholders. The recommendations engine, for instance, uses metadata and aggregated usage statistics without accessing or sharing company-specific information or report data.

Can I create custom metrics in GoodData’s Analytical Designer?

Yes, you can create custom metrics in the Analytical Designer. While you cannot create metrics directly, you can expand facts by applying different calculations such as sum, average, minimum, and maximum. Additionally, you can use any two facts/metrics/attributes in an insight to create a new metric. For more details, refer to the section on creating metrics in insights within the Analytical Designer documentation.

Why do some items disappear from the Data Catalog in Analytical Designer?

Items in the Data Catalog change dynamically as you create your insight. The Analytical Designer shows only items that you can add to your insight at the moment. For example, if you add items that are not connected to any date dimension, the date attribute will be hidden because it cannot be used to filter or slice your data. This ensures that only relevant data elements are displayed based on the current insight configuration.

How do insight filters and dashboard filters interact in GoodData?

Insight filters and dashboard filters interact in a way that ensures data consistency across different levels of analysis. For instance, if you apply a filter at the insight level, it will affect the data displayed within that specific insight. Similarly, dashboard filters can be applied to multiple insights on a dashboard, ensuring that all insights reflect the same filtered data. For detailed information, refer to the section on how dashboard data filters and insight date filters interact.

Can I hide certain items from the Data Catalog in embedded mode?

Yes, you can hide items in the embedded mode using parameters such as `includeObjectsWithTags` and `excludeObjectsWithTags`. These parameters allow you to display or hide specific facts, metrics, attributes, and dates. However, if you assign tags to folders, these parameters do not show or hide the folders themselves; you need to show or hide at least one item in the folder to affect its visibility.

How does GoodData’s analytics engine work?

GoodData’s analytics engine takes metrics and queries, translates them into SQL using the information coded in the Logical Data Model (LDM), and queries the database directly. The returned results are then cached before being passed to the end user. This process can be utilized either through the API directly or via the web interface, ensuring efficient and accurate data processing.

What are the plans for future AI-driven features in GoodData?

GoodData plans to launch advanced AI-driven trend analysis and anomaly detection capabilities in 2025. These tools will automatically explain unusual data patterns, provide richer context for decision-making, and highlight key trends that require attention. Additionally, the AI Assistant will enhance the analytics experience by automating dashboard creation and improving data visualization workflows.