GoodData Announces New Collaborative Data Modeling Solution

New Modeling Tool Will Improve Collaboration Between Engineers and Analysts to Streamline the Start Process for Enterprise Data Products

GoodData, a leader in end-to-end analytics solutions, today announced the release of a new web-based logical data model (LDM) modeler. The new LDM modeler brings new capabilities and tooling and enables the simplification of data modeling when starting a new data product or extending existing enterprise reporting.

The web-based LDM modeler compliments the recently released GoodData data source management interface, which enables easy connection to Google BigQuery, Amazon Redshift, Snowflake or a CSV file. When integrated together within GoodData’s interface, users gain the benefits of a single tool and can speed time to market for new data products as a result of better communication between teams taking care of physical data and those developing reporting, including the logical data model. This all supports GoodData’s semantic layer and its ability to simplify the complexity of data and make it more understandable to end-users.

“Achieving smooth collaboration between data engineers and data analysts is the greatest challenge facing enterprises building new data products for customers, or a reporting portal with a roll-out plan for every company branch. With our recent release, companies will bring analytics faster to their markets, both internal and external,” said Zdenek Svoboda, GoodData’s VP of Product & Marketing and co-founder.

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The key benefits of the GoodData semantic layer which is supported by our new LDM modeler includes:

  • Ease of use for non-technical users. The LDM modeler makes data more understandable for non-technical business users with lower data literacy because it simplifies understanding of the data semantics. This is in contrast to other situations when reports are built on top of source data. Typical business users don’t understand the data structure and meaning is hard to decipher.
  • Alignment between users.  Relationships and metrics are key elements in GoodData’s semantic layer. With a shared data model, business analysts in different entities get consistent results wherever they are, which support the single version of truth provided by analytics.
  • Augmented ad hoc analytics and data discovery. The data model allows business analysts to work with augmented analytics by allowing them to work only with relevant data for their insights and suggests next steps for their analytical projects.
  • Improved collaboration between data engineers and analysts. The new LDM modeler brings drag and drop experience to data analysts and allows them to communicate and easily explain the data model to the rest of the team.

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An additional benefit of the recent release is the guidance GoodData provides when modeling the output source from the company’s cloud data warehouse. GoodData suggests the data structure according to the data model and vice versa. When the data source or data structure  is changed, which is common, the data model can also be updated, so that teams save time in communication and explaining the changes. Moreover, thanks to the GoodData semantic layer, business analysts don’t have to change report definitions as typically required for other SQL-based reporting platforms.

By combining collaboration tools in data modeling with GoodData’s free and growth pricing tiers, which allows companies to better control data analytics spend as they startup and grow, GoodData is an ideal platform to start any analytics project as well as validate the viability of a business model for no cost to the organization.

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