GoodData Product Updates

New Features Introducing Composite Keys in GoodData Cloud Deprecations Final Deprecation of the Physical Data Model (PDM) New FeaturesIntroducing Composite Keys in GoodData CloudWe're excited to announce a powerful new feature in GoodData Cloud: composite keys. This enhancement allows you to combine two or more attributes (source columns) into a unique identifier for each record, greatly enhancing data integrity and relationship mapping.What are Composite Keys?With composite keys, you can select multiple attributes from your linked dataset as a primary key. GoodData Cloud then automatically generates a composite key by concatenating the values from these columns. This results in a more distinctive identifier, facilitating the connection of datasets that might not share unique ID values otherwise.Rollout Plan and Backward CompatibilityAs of this release, composite keys are available as an opt-in early access feature. We plan to activate this feature by default for all users within the next 2 to 4 weeks, coinciding with one of our following upcoming releases. To ensure seamless integration, please upgrade to Python SDK version 1.8 or newer as soon as possible; Older versions of the Python SDK will not support the use of composite keys.How to Opt-In for Early AccessTo test composite keys during this early access phase, please contact our support team. We encourage you to explore this feature and understand its impact on your datasets ahead of the broader rollout.DeprecationsFinal Deprecation of the Physical Data Model (PDM)In our continuous effort to streamline and modernize the GoodData Cloud platform, we are announcing the final deprecation of the Physical Data Model (PDM) as of this release. The PDM-related API endpoints will be removed on the 30th of November, 2023.

We’re constantly making GoodData better! Upcoming Upgrade to Vertica 23.4.0 and the Latest CentOS 9 StreamWe’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.Upcoming Upgrade to Vertica 23.4.0 and the Latest CentOS 9 StreamWe are gradually upgrading the versions of Vertica and CentOS used by our data warehouse. This upgrade will span over a few weeks and will require no action on your part.This is a planned maintenance procedure, during which your data will be temporarily unavailable for about one hour. The exact date may vary.We will post further announcements to update you on the state of the upgrade.Learn More:New Features in Vertica 23.4.

New Features GoodData.UI 9.3.0 Python SDK 1.8 Upcoming OpenAPI Specification Change for the Logical Data Model Changes in Default Breaking Change in REST API Enhanced Bucket Size for Pivot Tables Deprecations Physical Data Model Deprecated New FeaturesGoodData.UI 9.3.0This update includes the following improvements: The headline can now display two measures, enabling comparison customization via the config. We are also introducing client call caching. Python SDK 1.8 Adds the support for dashboard permissions 'share with everyone',  user group names, organization settings and csp directives. Upcoming OpenAPI Specification Change for the Logical Data ModelWe are in the process of implementing a modification to the OpenAPI specification for our Logical Data Model. This change will introduce a new method for defining primary composite keys. PUT operations of the model will continue to support the existing method to ensure backward compatibility. However, GET operations will return the primary keys per the new definition. Please be aware that the GET operation will exclusively support the new format once this update is in effect. This is considered a breaking change to the API.If you use the LDM Modeler, this change will not affect you. However, if you are using the Python SDK or any other tooling which validates the OpenAPI specification, we kindly ask you to make the following preparations for this impending update: Upgrade to the Python SDK version 1.8, scheduled for release on the 2nd of November 2023. For custom tooling that relies on OpenAPI validation, make sure to upgrade it after the change is deployed to ensure your LDM updates continue to function correctly. If you are unsure about the impact or wish to test the changes before the update, reach out to our support team. We aim to release this update by the end of the year. Specific dates will be provided in upcoming release notes, but we recommend updating the Python SDK by the 30th of November 2023 at the latest.Changes in DefaultBreaking Change in REST APIWe have implemented a breaking change in the REST API endpoint /API/v1/actions/workspaces/{workspaceId}/execution/afm/computeValidObjects. Please note that any request utilizing UNRECOGNIZED in the key type will now be rejected. This change is effective from the 2nd of November 2023 onwards.The value UNRECOGNIZED held no significance within this API. If you are currently using it, simply remove it from your requests. This removal will not impact the functionality of the endpoint in any way.Enhanced Bucket Size for Pivot TablesIn response to high demand from our customers, we've adjusted bucket limits: Column Attributes: Remains 20 Row Attributes: Increased to 50 (previously 20) Metrics: Increased to 100 (previously 20) Certain conditions apply, see Pivot Table documentation for details.DeprecationsPhysical Data Model DeprecatedWe've streamlined our modeling processes. Previously, a separate physical data model (PDM) was built atop the data source, while logical data models (LDM) were set for individual workspaces. Now, LDMs will encompass PDM details, centralizing data within a single workspace and simplifying SQL-based dataset interactions. While backend changes impact the REST API's interaction with LDM and PDM, frontend user interactions remain unchanged. Users should transition LDM backups to the new format and cease using the deprecated PDM and its API endpoints.The PDM is scheduled to be completely removed from GoodData on the 30th of November 2023.Learn More:Deprecation of the Physical Data Model

Released October 19th, 2023.New FeaturesExplicit Workspace Data FiltersWe've introduced a new panel in the Logical Data Modeller to help you manage workspace data filters. Within the “view details” dialog, a new “Data filtering” tab now allows users to toggle workspace data filters for designated datasets and align them with columns in the source table/view. Instead of merely matching column names, the mapping of these filters necessitates explicit activation and dataset-specific mapping.This enhancement marks the beginning of our vision to make workspace data filters manageable via the application's frontend, moving beyond exclusive API access.Learn More:Set Up Data Filters in WorkspacesEnhanced Metadata in Analytics EntitiesWe have added new metadata to analytics entities - analytical dashboards, visualization objects, dashboard plugins, and metrics. These entities will now include the following fields: createdAt: Displays the creation timestamp. createdBy: Shows the original creator. modifiedAt: Shows the latest edit timestamp. modifiedBy: Points to the last editor. To ensure smooth integration, we're updating the metadata database in this release. It includes adding new fields to related tables. For existing entities, createdAt gets the local time, while other fields (createdBy, modifiedAt, modifiedBy) remain null.Analytical Designer and Dashboards will now list insights by modification date, with the latest on top. Tabs above allow filtering by the current user's creations and all workspace insights. Note that the default tab shows only new insights due to metadata migration not populating createdBy.Learn More:Extended MetadataThemes and Palettes for Individual UsersTheme and color palette functionality was extended to also enable use in userSettings, allowing you to create unique visual styles for individual users and user groups.Learn More:Create Custom Color PalettesCreate Custom ThemesImproved SharingWe have improved dashboard sharing options. You can now effortlessly share a dashboard with all workspace users in a single click. In previous versions, creating user groups with all users was required, which could be cumbersome and challenging to manage. This feature enables granting various dashboard permissions (View, Edit, Share) just like when granting to individual users or user groups.Learn More:Share DashboardsTransposing Pivot TablesWe're giving you more control over positioning attributes, headers, and metrics among columns and rows in pivot tables. You can now easily change the orientation of pivot tables (e.g. show the headers, contents, and totals of columns in rows and vice versa) or put metrics into rows using a simple drop-down selector in the table's configuration.Learn More:Pivot TablesColumn and Row Totals in Pivot TablesWe have expanded the functionality of table totals. You can now use aggregate functions, i.e. both totals (showing the total sum of the whole column or row) and sub-totals (showing aggregates within individual attributes), for both columns or rows. For example, you can generate a column that shows the total sum of values of individual rows.Learn More:Pivot TablesImproved SecurityWe've enhanced GoodData's security features. Administrators in your organization can now limit users from creating user API tokens, ensuring that users must log in via single sign-on (SSO) for each session. In prior versions, users could generate their own API tokens, bypassing SSO after the initial login.Change in Default:By default, only administrators (users with the organization.MANAGE permission) can now create new API access tokens. Existing tokens remain valid.Learn More:Create an API Access TokenIntroducing FlexQueryWe're excited to announce FlexQuery, our newly introduced service that enhances the transformation and caching of data delivered by the SQL Executor Service. Designed with engineers in mind, FlexQuery aims to significantly reduce query times and save on costs by minimizing expensive cloud data warehouse query processing.Please be aware that updating to GoodData.CN 3.0 requires you to follow some specific steps related to FlexQuery.Learn More:Our Vision for the Next Generation of BI and AnalyticsOther Changes We have improved the SQL generated for date range conditions to boost performance. Fixed Bugs IDs that contain the + character should no longer cause issues when being referenced in the url of an API call. We resolved an issue where certain workspace hierarchy permission configurations could result in you being unable to open the metric editor in a child workspace. We have resolved issues with the metric editor in children workspaces. DepreciationsPhysical Data ModelWe've streamlined our modeling processes. Previously, a separate physical data model (PDM) was built atop the data source, while logical data models (LDM) were set for individual workspaces. Now, LDMs will encompass PDM details, centralizing data within a single workspace and simplifying SQL-based dataset interactions. While backend changes impact the REST API's interaction with LDM and PDM, frontend user interactions remain unchanged. Users should transition LDM backups to the new format and cease using the deprecated PDM and its API endpoints.If you have saved declarative workspace definitions in a location separate from the standard storage, which can be used for backups, we advise creating a fresh backup, particularly of the LDM workspace definitions, after a successful upgrade to GoodData.CN 3.0.0. This new backup will include the updated LDM.If you have a workspace declarative model stored externally, i.e. not present in the deployment, upload this model along with the associated data source and its PDM. Then, proceed to download the updated version of the workspace declarative model.Community EditionThe GoodData.CN Community Edition has been discontinued for GoodData.CN versions 3.0 and above. GoodData Community Edition versions prior to 3.0 will continue to function without change.If you're interested in exploring our analytical platform, you can register for a free trial at https://www.gooddata.com/trial/.If you have any questions, please feel free to contact us via https://www.gooddata.com/contact/.Developer ToolsPython SDKPlease update Python SDK to the latest version. Using an older version of Python SDK together with GoodData.CN version 3.0 or higher could cause issues with the Logical Data Model.GoodData.UIThe following updates to GoodData.UI have been released: 9.0.1 This hotfix introduces support for JWT authentication. 9.1.0 Added support for pivot tables, allowing you to transpose column headers to rows for more flexible data analysis. Pivot tables allow metrics to be placed in rows instead of columns. The attribute filter is optimized to fetch element counts only for child filters, improving performance. Because it does not fetch the total count of elements by default, its overhead is reduced. Sdk-backend-tiger now supports the following entity properties: createdAt, createdBy, modifiedAt, and modifedBy for the following analytical objects: insight, analytical dashboard, dashboard plugin, and metric. Sdk-backend-tiger now supports JWT authentication. Added support for Waterfall chart visualizations. The dashboard header element had its z-index changed from 100 to 6000. For reference the z-indicies of the dashboard overlay elements are as follows: Overlays in Dashboard component  = 5000 Overlays in Dashboard header component = 6000 Overlays in Dashboard component in conflict with filter bar = 6000 Upgrade GuideFlexQuery - Caching and Computation Engine UpgradeStarting from version 3.0, the default caching and computation engine of GoodData.CN has undergone significant changes, introducing a new set of services in the deployment. These changes include: quiver-xtab: This service is responsible for processing computations. quiver-cache: Manages the storage of both raw and result cache data (data extracted from data sources and subsequently transformed into reports) as well as label elements (data for filters). Until version 3.0, all the caches were stored in redis. etcd: This database supports synchronization between the quiver-* services. Note that quiver is an internal name for FlexQuery.As raw, result, and label element data caches are no longer stored in redis (only their metadata still are), we recommend reviewing your redis memory utilization and adjusting your memory resources as needed. If you prefer to continue using the old caching flow, you can use the Helm chart options deployQuiver: false and useInternalQuiverEtcd: false. However, note that this option will be deprecated in the next release.Managing CachesThe new caching system, by default, stores caches in the quiver-cache service only. When the service's file storage is fully utilized (set to 1GB by default), it triggers the eviction of the least recently used caches to maintain file storage within its limit. The service offers several configuration options for managing caches: quiver.storage.cache.diskSize and quiver.storage.cache.diskCacheSize allow you to adjust the maximum internal storage size in the service. quiver.limitFlightCount defines the maximum number of caches that can be held in the system. Note that increasing this value may decrease performance. durableStorageType define durable caches and ensures their durability even after quiver-* services restart. Note that every change of durableStorageType requires wiping etcd, which holds storage configuration from the last time. You can achieve this by running etcdctl del --prefix <deployment_namespace_name> on one of the etcd PODs. Use one of the following values: "" (no durable storage): All caches are held by the quiver-cache POD. "S3": Durable caches are stored in the defined AWS S3 bucket (see below). "FS": Durable caches are stored on storage defined by storageClassName, which must support the ReadWriteMany access mode.  s3DurableStorage.s3Bucket: The AWS bucket name for storing caches. s3DurableStorage.s3BucketPrefix: Custom bucket prefix. s3DurableStorage.s3Region: The AWS region (the default is "us-east-1"). s3DurableStorage.s3AccessKey: AWS access key ID of the IAM account with access to the S3 bucket. s3DurableStorage.s3SecretKey: AWS secret access key of the IAM account with access to the S3 bucket. s3DurableStorage.authType: Authentication type ("aws_tokens" | "aws_default" | "none," default is "aws_default"), respecting AWS credentials provider chain. We recommend implementing monitoring, alerting, and regular defragmentation of etcd.For a comprehensive list of configuration options related to the new caching system, see the Helm Charts Options section of our documentation.Check That the Physical Data Model Removal Was SuccessfulWith the deprecation of the physical data model, updating to GoodData.CN 3.0 now triggers an automatic enhancement of your logical data models (LDMs). This enhancement adds new data types, paths to tables, and references to workspace data filters. Our aim is to ensure that your LDMs operate seamlessly even after the physical data models are phased out from GoodData.What should you do?The update is automatic, but we recommend you check the logs after starting your metadata-api service. Look for the following lines: action=polling detail=ENABLE_PDM_REMOVAL_DEPRECATION_PHASE stateChange=offToOn state=start action=polling detail=ENABLE_PDM_REMOVAL_DEPRECATION_PHASE stateChange=offToOn state=success These indicate the update was successful. Ensure the following line is NOT present in your logs:action=polling detail=ENABLE_PDM_REMOVAL_DEPRECATION_PHASE stateChange=offToOn state=errorIf this error occurs, delete your metadata-api pod, and after its automatic start check the logs again for this error. If the error persists, please reach out to GoodData support for help.Please note that this update is a one-time process and will not recur on future pod restarts once successfully completed.Upgrade GoodData.CN to 3.0To upgrade Helm chart, follow the general upgrade guide.

New FeaturesImproved HeadlineWe have substantially expanded the functionality of headlines. You can now compare numbers, define how the comparison should be calculated, or customize the formatting and visual aspect of the headline.Updating this feature updates your existing visualizations which use headlines. However, the new version is predefined to replace the previous one identically and without introducing any breaking changes in your visualizations and dashboards. Learn More:Headline

New FeaturesImproved HeadlineWe have substantially expanded the functionality of headlines. You can now compare numbers, define how the comparison should be calculated, or customize the formatting and visual aspect of the headline.Updating this feature updates your existing visualizations which use headlines. However, the new version is predefined to replace the previous one identically and without introducing any breaking changes in your visualizations and dashboards. Learn More:Headline

We’re constantly making GoodData better! End of Life: CSV UploaderWe’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.End of Life: CSV UploaderThe CSV Uploader functionality will be removed on October 5th, 2023. Please take note of the following important information regarding this deprecation:Are you affected? Check if you have the "Load" section enabled. Verify if you have any datasets listed within the "Load" section. If any datasets are present in the Load section, you must either delete them or convert them into standard datasets visible in the model. Follow the steps listed in the Use CSV Uploader for Ad-hoc Analysis article.What will happen if you do not switch to a different method of loading data The Load section will be removed together with the CSV Uploader functionality on October 5th, 2023. The datasets that were not modified will remain accessible as metadata objects and you can still make them visible in the model. However, loading data into these datasets will not be possible. Reports created using these datasets may continue to function as non-production datasets will still be selectable in the analytics designer, but loading new data will be disabled. Note that these datasets may be removed in the future without further notice. All associated objects, such as metrics, reports, and dashboards built using these datasets, will also be deleted if removed.

New Features Improved Sharing Improved Security Important - Update Python SDK Performance ImprovementsNew FeaturesImproved SharingWe have improved dashboard sharing options. You can now effortlessly share a dashboard with all workspace users in a single click. In previous versions, creating user groups with all users was required, which could be cumbersome and challenging to manage. This feature enables granting various dashboard permissions (View, Edit, Share) just like when granting to individual users or user groups.Learn More:Share DashboardsImproved SecurityWe've enhanced GoodData's security features. Administrators in your organization can now limit users from creating user API tokens, ensuring that users must log in via single sign-on (SSO) for each session. In prior versions, users could generate their own API tokens, bypassing SSO after the initial login.Change in Default:By default, only administrators (users with the organization.MANAGE permission) can now create new API access tokens. Existing tokens remain valid.Learn More:Create an API Access TokenImportant - Update Python SDKUpdate Python SDK to the latest version. Using an older version of Python SDK could cause issues with the Logical Data Model.Performance ImprovementsWe have improved the SQL generated for date range conditions to boost performance.

We’re constantly making GoodData better! Performance ImprovementsWe’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.Performance Improvements We have improved the SQL generated for date range conditions to boost performance.

We’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.

We’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.

We’re constantly making GoodData better! New Features Transposing Pivot Tables End of Life: CSV UploaderWe’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.New FeaturesTransposing Pivot TablesWe're giving you more control over positioning attributes, headers, and metrics among columns and rows in pivot tables. You can now easily change the orientation of pivot tables (e.g. show the headers, contents, and totals of columns in rows and vice versa) or put metrics into rows using a simple drop-down selector in the table's configuration.Learn More:TablesEnd of Life: CSV UploaderThe CSV Uploader functionality will be removed on October 5th, 2023. Please take note of the following important information regarding this deprecation:Are you affected? Check if you have the "Load" section enabled. Verify if you have any datasets listed within the "Load" section.  If any datasets are present in the Load section, you must either delete them or convert them into standard datasets visible in the model. Follow the steps listed in the Use CSV Uploader for Ad-hoc Analysis article.What will happen if you do not switch to a different method of loading data? The Load section will be removed together with the CSV Uploader functionality on October 5th, 2023. The datasets that were not modified will remain accessible as metadata objects and you can still make them visible in the model. However, loading data into these datasets will not be possible. Note that these datasets may be removed in the future without further notice.

New Features Transposing Pivot Tables Column and Row Totals in Pivot Tables GoodData.UI 9.1.0 Bug Fixes Depreciations Physical Data Model Depreciated New FeaturesTransposing Pivot TablesWe're giving you more control over positioning attributes, headers, and metrics among columns and rows in pivot tables. You can now easily change the orientation of pivot tables (e.g. show the headers, contents, and totals of columns in rows and vice versa) or put metrics into rows using a simple drop-down selector in the table's configuration.Learn More:Pivot TablesColumn and Row Totals in Pivot TablesWe have expanded the functionality of table totals. You can now use aggregate functions for both columns or rows, i.e., both totals (showing the total sum of the whole column or row) and sub-totals (showing aggregates within individual attributes). For example, you can generate a column that shows the total sum of the values of individual rows.Learn More:Pivot TablesGoodData.UI 9.1.0This update includes the following improvements: Added support for pivot tables, allowing you to transpose column headers to rows for more flexible data analysis. Pivot tables allow metrics to be placed in rows instead of columns. The attribute filter is optimized to fetch element counts only for child filters, improving performance. Because it does not fetch the total count of elements by default, its overhead is reduced. Sdk-backend-tiger now supports the following entity properties: createdAt, createdBy, modifiedAt, and modifedBy for the following analytical objects: insight, analytical dashboard, dashboard plugin, and metric. Sdk-backend-tiger now supports JWT authentication. Added support for Waterfall chart visualizations. Bug Fixes We have resolved issues with the metric editor in children workspaces. DeprecationsPhysical Data Model DeprecatedWe've streamlined our modeling processes. Previously, a separate physical data model (PDM) was built atop the data source, while logical data models (LDM) were set for individual workspaces. Now, LDMs will encompass PDM details, centralizing data within a single workspace and simplifying SQL-based dataset interactions. While backend changes impact the REST API's interaction with LDM and PDM, frontend user interactions remain unchanged. Users should transition LDM backups to the new format and cease using the deprecated PDM and its API endpoints.Note: This change was supposed to be released in the August 24, 2023 release but has been postponed due to unforeseen technical challenges. The current plan is to implement this change on the 11th of September 2023 for all instances of GoodData Cloud.Learn More:Deprecation of the Physical Data Model

We’re constantly making GoodData better! Data Warehouse JDBC Driver 3.6.0 Available We’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.Data Warehouse JDBC Driver 3.6.0 AvailableWe have released version 3.6.0 of the Data Warehouse JDBC driver. Download it from https://secure.gooddata.com/downloads.html.NOTE: We strongly suggest upgrading to JDBC Driver 3.6.0 as soon as possible. Older versions will be deprecated on 24 February 2024.If you are a white-labeled customer, log in to the Downloads page from your white-labeled domain: https://my.domain.com/downloads.htmlWhat's new in this version? Complex types compatible with Vertica JDK 11 are supported.

New Features Explicit Workspace Data Filters Enhanced Metadata in Analytics Entities GoodData.UI 9.0.1 Bug Fixes Depreciations Physical Data Model Depreciated New FeaturesExplicit Workspace Data FiltersWe've introduced a new panel in the logical data modeler to help you manage workspace data filters. Within the “view details” dialog, a new “Data filtering” tab now allows users to toggle workspace data filters for designated datasets and align them with columns in the source table/view. Instead of merely matching column names, the mapping of these filters necessitates explicit activation and dataset-specific mapping.This enhancement marks the beginning of our vision to make workspace data filters manageable via the application's frontend, moving beyond exclusive API access.Learn More:Set Up Data Filters in WorkspacesEnhanced Metadata in Analytics EntitiesWe have added new metadata to analytics entities - analytical dashboards, visualization objects, dashboard plugins, and metrics. These entities will now include the following fields: createdAt: Displays the creation timestamp. createdBy: Shows the original creator. modifiedAt: Shows the latest edit timestamp. modifiedBy: Points to the last editor. To ensure smooth integration, we're updating the metadata database in this release. It includes adding new fields to related tables. For existing entities, createdAt gets the local time, while other fields (createdBy, modifiedAt, modifiedBy) remain null.Analytical Designer and Dashboards will now list insights by modification date, with the latest on top. Tabs above allow filtering by the current user's creations and all workspace insights. Note that the default tab shows only new insights due to metadata migration not populating createdBy.Learn More:See the Extended Metadata section for further details.GoodData.UI 9.0.1This hotfix introduces support for JWT authentication.Bug Fixes We have added a new property called oauthSubjectIdClaim to the organization API entity that lets you map your claim to a custom property of the ID token sent to GoodData. This should resolve issues with, for example, using Azure Active Directory as your OIDC identity provider. IDs that contain the + character should no longer cause issues when being referenced in the url of an API call. We resolved an issue where certain workspace hierarchy permission configurations could result in you being unable to open the metric editor in a child workspace. DeprecationsPhysical Data Model DeprecatedUpdate: Due to unforeseen technical challenges, the deprecation of the PDM has been postponed to the next release. We apologize for any confusion and inconvenience this may cause.We've streamlined our modeling processes. Previously, a separate physical data model (PDM) was built atop the data source, while logical data models (LDM) were set for individual workspaces. Now, LDMs will encompass PDM details, centralizing data within a single workspace and simplifying SQL-based dataset interactions. While backend changes impact the REST API's interaction with LDM and PDM, frontend user interactions remain unchanged. Users should transition LDM backups to the new format and cease using the deprecated PDM and its API endpoints.Learn More:Deprecation of the Physical Data Model

Please note: The release date for this update has been moved to Monday, 28th of August, 2023. New Features New Visualizations: Pyramid and Funnel Charts, Dependency Wheel, Sankey Diagram and Waterfall Chart JWT Authentication Database Credential Encryption VS Code Extension (Beta) GoodData.UI SDK 9.0 Python SDK 1.4 & 1.5 Bug Fixes Get the Community Edition Upgrade Guides Upgrade etcd Implement Data Source Credentials Encryption Upgrade GoodData.CN to 2.5 Please note: The release date for this update has been moved to Monday, 28th of August, 2023.New FeaturesNew Visualizations: Pyramid and Funnel Charts, Dependency Wheel, Sankey Diagram and Waterfall ChartWe have added 4 new types of charts to help you visualize your data: Pyramid charts are great at showing hierarchical structures and relative proportions. Funnel charts are best used to show the progressive stages of a process. Dependency wheels can easily represent the relationships among multiple entities. Sankey diagrams highlight the flows of values from one category to another. Waterfall charts illustrate the total effect of positive and negative values on a starting point. Learn more:Pyramid ChartsFunnel ChartsDependency Wheel ChartsSankey DiagramsWaterfall ChartsJWT AuthenticationIn our ongoing efforts to bolster security and ease of use, we're introducing JWT authentication as an alternative to plain API access tokens. JWT authentication should provide a seamless login process and enhanced security, and this new method supports easy integration with other systems using our React SDK and iframe embedding options.Learn More:Set Up JWT AuthenticationDatabase Credential EncryptionWe have added support for encrypting your data source credentials. Encrypt your database passwords and OIDC client secrets and make them usable in GoodData.CN by adding the corresponding keyset and secret values to the GoodData.CN helm chart.Learn More:Encrypt Data Source CredentialsVS Code Extension (Beta)We are happy to announce that we’re rolling out beta for a new VS Code Extension and its complementary CLI.This is a big step forward toward seamless integration and better developer experience.Here are some of the new plugin's key benefits: Automation: Smooth deployment, epic quality control, and must-have test automation for modern software solutions. Collaboration: Teamwork made simple with collaborative GitHub or GitLab. Governance: Analytics as Code ensures secure and backtrackable solutions with revertible iterations. GoodData.UI SDK 9.0GoodData.UI now supports React 18 and there is new Accelerator Toolkit: @gooddata/app-toolkitOverall, GoodData.UI SDK 9.0 is mainly focused on adding supported technologies and improving migration.Please note that there is now also a hot fix 9.0.1 now available that enables integration with JWT authentication.Breaking changes: Moving strictly to ECMAScript Modules IE11 is no longer supported. Dashboard Plugins Lifecycle introduction @gooddata/catalog-export configuration changes. Namespaces Removal Python SDK 1.4 & 1.5The new versions 1.4 and 1.5 some QoL features. This version is tied to the latest version of GoodData.CN (2.5) and GoodData Cloud.New features in Python SDK 1.4: PDF, CSV, XLSX export support Added dashboard permissions support User Data Filters support Quality of Life changes: Unified API clients - gooddata-api-client Added support for Python 3.11 Breaking Changes: Dropped support for Python 3.7 New features in Python SDK 1.5:Support for JWT authentication.Bug Fixes We have added a new property called oauthSubjectIdClaim to the organization API entity that lets you map your claim to a custom property of the ID token sent to GoodData. This should resolve issues with, for example, using Azure Active Directory as your OIDC identity provider. IDs that contain the + character should no longer cause issues when being referenced in the url of an API call. Get the Community EditionPull the GoodData.CN Community Edition to get started with the latest release:docker pull gooddata/gooddata-cn-ce:2.5.0Upgrade GuidesPerform the following tasks in sequence to upgrade from GoodData.CN 2.4 to GoodData.CN 2.5.Upgrade etcdThere is a major upgrade to the etcd subchart that requires some manual preparation. Execute the following commands, substituting your own values for the NAMESPACE and RELEASE:NAMESPACE='gooddata-cn' RELEASE='gooddata-cn' kubectl -n ${NAMESPACE} label pod ${RELEASE}-etcd-0 app.kubernetes.io/component=etcd kubectl -n ${NAMESPACE} label pod ${RELEASE}-etcd-1 app.kubernetes.io/component=etcd kubectl -n ${NAMESPACE} label pod ${RELEASE}-etcd-2 app.kubernetes.io/component=etcd kubectl -n ${NAMESPACE} delete statefulset ${RELEASE}-etcd --cascade=orphanImplement Data Source Credentials EncryptionThe new version of GoodData.CN comes with the Data Source Credentials Encryption feature. Before you go on to upgrade your Helm chart to the GoodData.CN 2.5 version, ensure you: Add to your Helm chart options: metadataApi.encryptor.enabled (bool) If you do not want to use the encryption feature, set this to false and proceed to the Helm chart upgrade. Otherwise set this to true and continue to the next step.Be aware that once you enable encryption, your credentials become irreversibly encrypted! Prepare a Tink keyset. See Data Source Credentials Encryption documentation for details on how to create and manage the Tink keysets. (Optional) Create a secret out of your Tink keyset. Add to your Helm chart options one of the following: metadataApi.encryptor.existingSecret (string) OR: metadataApi.encryptor.keySet (string) Add the keyset OR the secret with the keyset to metadataApi.encryptor.keySet OR metadataApi.encryptor.existingSecret respectively. Proceed to the Helm chart upgrade. Upgrade GoodData.CN to 2.5To upgrade Helm chart, follow the general upgrade guide.

We’re constantly making GoodData better! End of Life: CSV UploaderWe’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and made improvementsto underlying processes. We are preparing for new features in the upcoming releases.End of Life: CSV UploaderThe CSV Uploader functionality will be removed on October 5th, 2023. Please take note of the following important information regarding this deprecation:Are you affected? Check if you have the "Load" section enabled. Verify if you have any datasets listed within the "Load" section. If there are any datasets present in the Load section, you must either delete them or convert them into standard datasets that are visible in the model. Follow the steps listed in the Use CSV Uploader for Ad-hoc Analysis article.What will happen if you do not switch to a different method of loading data The Load section will be removed together with the CSV Uploader functionality on October 5th, 2023. The datasets that were not modified will remain accessible as metadata objects and you can still make them visible in the model. However, loading data into these datasets will not be possible. Note that these datasets may be removed in the future without further notice.

New Features JWT Authentication VS Code Extension (Beta) New FeaturesJWT AuthenticationIn our ongoing efforts to bolster security and ease of use, we're introducing JWT authentication as an alternative to plain API access tokens. JWT authentication should provide a seamless login process and enhanced security, and this new method supports easy integration with other systems using our React SDK and iframe embedding options.Learn More:Set Up JWT AuthenticationVS Code Extension (Beta)We are happy to announce that we’re rolling out beta for a new VS Code Extension and its complementary CLI.This is a big step forward toward seamless integration and better developer experience.Here are some of the new plugin's key benefits: Automation: Smooth deployment, epic quality control, and must-have test automation for modern software solutions. Collaboration: Teamwork made simple with collaborative GitHub or GitLab. Governance: Analytics as Code ensures secure and backtrackable solutions with revertible iterations.

We’re constantly making GoodData better! GoodData.UI SDK 9.0 We’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.GoodData.UI SDK 9.0GoodData.UI now supports React 18 and there is a new Accelerator Toolkit: @gooddata/app-toolkitOverall, GoodData.UI SDK 9.0 is mainly focused on adding supported technologies and improving migration.Breaking changes: Moving strictly to ECMAScript Modules IE11 is no longer supported. Dashboard Plugins Lifecycle introduction @gooddata/catalog-export configuration changes. Namespaces Removal

New Features Introducing SQL Datasets Convert Between Regular Datasets and SQL Datasets Drill from an Attribute New Embedding Dialogs and Embedding Options Embedded Dashboard Iframe Authentication Single Value Selection Attribute Filters Workspace Object ID Generation and Custom Prefixes Workspace Object Identifiers Entity API for Workspace Data Filters Support for More Databases Customize the First Day of the Week Continuous Line for Combo, Line, and Stacked Area Charts Rename Dashboard Filters Streamlining Property ID Generation GoodData.UI SDK 9.0 Python SDK 1.4 Bug Fixes and Other Changes Revised API Error Responses Limitations Deleting Objects with Identical IDs Get the Community Edition Upgrade Guides Upgrade Docker Community Edition to 2.4 Upgrade Docker to 2.4 Upgrading from a Version 2.2 or Older Upgrading the Apache Pulsar Helm Chart New FeaturesIntroducing SQL DatasetsYou can now create the equivalent of views (virtual tables) directly in the logical data model using SQL datasets. The dataset is created based on a custom SQL query that you define.With SQL datasets you can rapidly create new ‘virtual views’ without having to modify the original database, which may not always be possible.Please note that at this moment this is a beta feature, and we discourage you from using beta features in production environments.Learn More:Create SQL DatasetsConvert Between Regular Datasets and SQL DatasetsYou can now freely map your datasets back and forth between regular datasets (tied to a specific table or view in your database) and SQL datasets (our version of virtual tables).Please note that at this moment this is a beta feature, and we discourage you from using beta features in production environments.Learn More:Create SQL DatasetsDrill from an AttributeYou now have the ability to add drill interactions to both metrics and attributes; previously only drilling from metric was supported.Learn more:Drilling in DashboardsNew Embedding Dialogs and Embedding OptionsWe have revamped the embedding dialogs in the dashboard and visualization editors. With a couple of mouse clicks you can copy code snippets to embed: A dashboard as a React component, a Web Component or an iframe A visualization as a React component or a Web Component. Learn More:Embed Visualizations Using IframesEmbed Visualizations Using Web ComponentsEmbed Visualizations Using React SDKEmbedded Dashboard Iframe AuthenticationWhen embedding a dashboard into your web application via iframes, you can now authenticate users using the API authentication token.Learn More:Embed Visualizations Using IframesSingle Value Selection Attribute FiltersAttribute filters in dashboards allow you to filter data using any combination of selected attributes. However, there may be instances when you want to restrict dashboard users to filtering by only one attribute value at a time. To address this need, we are introducing a single value selection option for attribute filters. This feature ensures that users can select only one value at a time when applying filters.Learn More:Use Attribute Filters on DashboardsWorkspace Object ID Generation and Custom PrefixesIn our ongoing effort to simplify working with workspace hierarchies, we are introducing the ability to set custom prefixes for individual workspaces. These prefixes will be automatically applied when the server generates an identifier for analytical objects, allowing you to easily identify the workspace from which specific metrics, visualizations, and other analytical objects originate.Also, the server will now automatically generate an ID for new objects when no explicit ID is provided. If a custom prefix has been set for the workspace in which the object is being created, the prefix will be automatically added to the object ID.Learn More:Workspace Object IdentificationWorkspace Object IdentifiersWe are changing how object IDs work in workspace hierarchies. Objects inherited from parent workspaces will no longer contain prefixes in their object IDs, instead the objects have metadata describing their origin that is accessible via the workspace object API. This should make for a less ambiguous and robust system going forward.However this could be a breaking change for some of you, especially if you are using: Dashboard plugins GoodData.UI Iframes We have prepared a short article on what exactly the changes are and how you can address any problems that this change might cause. Please read the article here.Learn More:Workspace Object IdentificationEntity API for Workspace Data FiltersYou can now set workspace data filters directly using the /api/v1/entities/workspaces/<child_workspace_id>/workspaceDataFilterSettings/<object_id> entity API endpoint. This update offers a faster alternative to using the declarative API for the entire workspace, while also mitigating the risk of parallel overwrites when multiple users modify workspace settings simultaneously.Learn More:Set Up Data Filters in WorkspacesSupport for More DatabasesYou can now create a data source out of the following databases: Microsoft SQL Azure SQL Synapse SQL Learn More:Create an Azure SQL Data SourceCreate a Microsoft SQL Server Data SourceCreate a Synapse SQL Data SourceCustomize the First Day of the WeekYou now have the choice to set Monday as the start of the week in GoodData, instead of the default Sunday. This setting impacts date pickers in the user interface and weekly data analysis, allowing for a more tailored experience that fits your needs.Learn more:
Change Date FormatContinuous Line for Combo, Line, and Stacked Area ChartsYou can now choose to create a continuous line graph even if some of its values are missing.Learn more:Combo ChartsLine ChartsStacked Area ChartsRename Dashboard FiltersIf your attributes filters have long or technical names, you can now change their names on Dashboards in the filter configuration while editing the dashboard. The name of the filter is changed only on the particular dashboard and is not propagated to other dashboards.Learn More:Use Attribute Filters on DashboardsStreamlining Property ID GenerationColumn names with specific GoodData-compatible prefixes (such as cp__, a__, f__ and so on) will no longer contain these prefixes in the generated dataset property identifiers. This should make it easier for you to work with these properties when writing in MAQL.Learn More:Prepare Your DataGoodData.UI SDK 9.0GoodData.UI now supports React 18 and there is new Accelerator Toolkit: @gooddata/app-toolkitOverall, GoodData.UI SDK 9.0 is mainly focused on adding supported technologies and improving migration.Breaking changes: Moving strictly to ECMAScript Modules IE11 is no longer supported. Dashboard Plugins Lifecycle introduction @gooddata/catalog-export configuration changes. Namespaces Removal Python SDK 1.4The new version 1.4 includes new documentation for GoodData Pandas and some QoL features. This version is tied to the latest version of GoodData.CN (2.4) and GoodData Cloud.New features in Python SDK 1.4: PDF, CSV, XLSX export support Added dashboard permissions support User Data Filters support Quality of Life changes: Unified API clients - gooddata-api-client Added support for Python 3.11 Breaking Changes: Dropped support for Python 3.7 Bug Fixes and Other ChangesRevised API Error ResponsesIn this release, we focused on enhancing the error responses from various API services by validating and fixing incorrect error codes and messages. The goal was to provide users with clearer and more informative responses, particularly when encountering errors. Large OIDC ID tokens should no longer trigger the TooLongHttpLineException. We fixed an issue that made it impossible to set dashboard permissions using the /actions/workspaces/:workspaceId/analyticalDashboards/:dashboardId/managePermissions API endpoint. You can now import declarative layouts via PUT API calls even if they contain invalid objects. Similarly you can export declarative layouts together with any invalid objects that are stored within using GET API calls. This should provide some additional flexibility when you are reusing older backups or when you are debugging. We have resolved issues with broken analytics in children workspaces during the declarative PUT LDM process. To simplify log analysis, all logs now return durationMs instead of duration. This is because duration contained a formatted duration that machines could not process. This could be a breaking change for you if you have automated processes built on top of the log output. We have replaced the demo schema in the PostgreSQL database embedded in the AIO image with the new ecommerce_demo schema. As a result, the credentials for connecting to the sample databases have been updated accordingly: demo is now ecommerce_demo for PostgreSQL, and GOODDATA_DEMO_SCHEMA is now ECOMMERCE_DEMO_SCHEMA for Snowflake. GoodData.CN's next release, expected in September 2023, will be labeled as version 3.0.0. This indicates the inclusion of multiple major updates.  LimitationsDeleting Objects with Identical IDsAs a result of discontinuing object ID prefixes, two objects can share an identical object ID. For example, you might have had a workspace with the metric revenue and an inherited metric parent_workspace_id:revenue. But since prefixes are no longer supported, you cannot directly reference the parent_workspace_id:revenue object; both objects will have the ID revenue. In such cases, we apply the “parent wins strategy”, where requesting the conflicting object ID revenue will return only the highest object in the workspace hierarchy.Objects created in version 2.4.0 and newer are correctly deleted if their parent object (with the same ID) is removed. If you migrate objects created in an older version to version 2.4.0, removing their parent object will not affect them and such objects will not be deleted. However, in such cases, requesting the conflicting object ID still returns the highest object in the workspace hierarchy.Get the Community EditionPull the Docker Community Edition to get started with the latest release:docker pull gooddata/gooddata-cn-ce:2.4.0Upgrade GuidesUpgrade Docker Community Edition to 2.4Suppose you are using a docker volume to store metadata from your Docker Community Edition container. Download a new version of the Docker Community Edition docker image and start it with your volume. All your metadata is migrated automatically.Upgrade Docker to 2.4To upgrade the Helm chart, follow the general upgrade guide.Upgrading from a Version 2.2 or OlderAs a result of the discontinued object ID prefixes we recommend you check API for conflicts of duplicate objects if you are upgrading your deployment from an older version to version 2.3 or 2.4.To check for conflicts, use the API endpoints /api/v1/actions/workspaces/<parent_workspace_id>/overriddenChildEntities and /api/v1/actions/workspaces/<parent_child_id>/inheritedEntityConflicts. See List and Resolve Conflicting Object IDs for details.Upgrading the Apache Pulsar Helm ChartBefore upgrading the GoodData CN helm chart, you must upgrade the Apache Pulsar helm chart to version 3.0.0. It is necessary to update your customized-values-pulsar.yaml file. Refer to the new example values in the installation article and make sure that you uncomment the following two sections in both the zookeeper and bookkeeper keys:securityContext: fsGroupChangePolicy: "Always"Change other site-specific parameters (like setting a proper storageClassName) and perform the helm upgrade:helm repo update apachehelm upgrade --namespace pulsar --version 3.0.0 \ -f customized-values-pulsar.yaml \ pulsar apache/pulsar --wait --timeout 10mWait for the upgrade to finish and check the results:kubectl -n pulsar get podNAME READY STATUS RESTARTS AGEpulsar-bookie-0 1/1 Running 0 28mpulsar-bookie-1 1/1 Running 0 28mpulsar-bookie-2 1/1 Running 0 28mpulsar-broker-0 1/1 Running 0 28mpulsar-broker-1 1/1 Running 0 27mpulsar-recovery-0 1/1 Running 0 28mpulsar-zookeeper-0 1/1 Running 0 28mpulsar-zookeeper-1 1/1 Running 0 28mpulsar-zookeeper-2 1/1 Running 0 28mIf all pods are running, proceed with the GoodData CN helm upgrade.

We’re constantly making GoodData better! GoodData.UI SDK 9.0 Python SDK 1.4 We’re constantly making GoodData better!In this release, we have addressed and fixed some bugs and improved underlying processes. We are preparing for new features in the upcoming releases.GoodData.UI SDK 9.0GoodData.UI now supports React 18 and there is a new Accelerator Toolkit: @gooddata/app-toolkitOverall, GoodData.UI SDK 9.0 is mainly focused on adding supported technologies and improving migration.Breaking changes: Moving strictly to ECMAScript Modules IE11 is no longer supported. Dashboard Plugins Lifecycle introduction @gooddata/catalog-export configuration changes. Namespaces Removal Python SDK 1.4The new version 1.4 includes new documentation for GoodData Pandas and some QoL features. This version is tied to the latest version of GoodData.CN (2.4) and GoodData Cloud.New features in Python SDK 1.4: PDF, CSV, XLSX export support Added dashboard permissions support User Data Filters support Quality of Life changes: Unified API clients - gooddata-api-client Added support for Python 3.11 Breaking Changes: Dropped support for Python 3.7

New Features Column Totals in Pivot Tables Selectable First Day of the Week Other Changes Upcoming Upgrade to Vertica 11.1.1 and the Latest CentOS New FeaturesColumn Totals in Pivot TablesWe have expanded the functionality of table totals. You can now use aggregate functions horizontally. For example, using this new feature, you can generate a column that shows the total sum of values of individual rows.Learn More:TablesSelectable First Day of the WeekYou can now set either Sunday or Monday as the first day of the week.Learn More:Change Date FormatOther ChangesUpcoming Upgrade to Vertica 11.1.1 and the Latest CentOSWe are starting to gradually upgrade the versions of Vertica and CentOS used by our data warehouse. The whole process should be finished in a few weeks and requires no action on your side.We will be posting further announcements to update you on the state of the upgrade.Learn More:New Features in Vertica 11.1. 

New Features Entity API for Workspace Data Filters Other Changes Revised API Error Responses Bug FixesNew FeaturesEntity API for Workspace Data FiltersYou can now set workspace data filters directly using the /api/v1/entities/workspaces/<child_workspace_id>/workspaceDataFilterSettings/<object_id> entity API endpoint. This update offers a faster alternative to using the declarative API for the entire workspace, while also mitigating the risk of parallel overwrites when multiple users modify workspace settings simultaneously.Learn More:Set Up Data Filters in WorkspacesOther ChangesRevised API Error ResponsesIn this release, we focused on enhancing the error responses from various API services by validating and fixing incorrect error codes and messages. The goal was to provide users with clearer and more informative responses, particularly when encountering errors.Bug Fixes We have resolved issues with broken analytics in children workspaces during the declarative PUT LDM process.

New Features New Visualization: Waterfall Chart End of Life CSV Uploader New FeaturesNew Visualization: Waterfall ChartWe have added a new type of chart to help you visualize your data. Waterfall charts are useful for illustrating the total effect of positive and negative values on a starting point. They are commonly used to show financial data, such as changes in revenue, expenses, or profit. For example, a waterfall chart can show the breakdown of a company’s net profit, starting with the initial value and then displaying additions and deductions to arrive at the final value.Learn More:Waterfall ChartsEnd of LifeCSV UploaderThe CSV Uploader functionality will be removed on October 5th, 2023. Please take note of the following important information regarding this deprecation:Are you affected? Check if you have the "Load" section enabled. Verify if you have any datasets listed within the "Load" section.  If there are any datasets present in the Load section, you must either delete them or convert them into standard datasets that are visible in the model. Follow the steps listed in the Use CSV Uploader for Ad-hoc Analysis article.What will happen if you do not switch to a different method of loading data The Load section will be removed together with the CSV Uploader functionality on October 5th, 2023. The datasets that were not modified will remain accessible as metadata objects and you can still make them visible in the model. However, loading data into these datasets will not be possible. Note that these datasets may be removed in the future without further notice.

New Features New Visualization: Waterfall Chart New FeaturesNew Visualization: Waterfall ChartWe have added a new type of chart to help you visualize your data. Waterfall charts are useful for illustrating the total effect of positive and negative values on a starting point. They are commonly used to show financial data, such as changes in revenue, expenses, or profit. For example, a waterfall chart can show a company’s net profit breakdown, starting with the initial value and then displaying additions and deductions to arrive at the final value.Learn More:Waterfall Charts