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GoodData Employee
dan.junGoodData Employee
published in Solution architecture - KB articles

GoodData.CN: Data FiltersGoodData.CN

IntroductionOne of the core strengths of GoodData.CN (GD.CN) workspace hierarchies is the ability to create a network of connected workspaces, each outfitted with a uniquely limited version of the same datasets. This action of limiting data is done through applying Data Filters to each child workspace. The benefit of this approach is that your analytic solution can be quickly and easily scaled for a variety of different data privilege levels. It also circumvents the need for costly, partial duplications of your tables on your underlying database. Data Filters can be created using any of the attributes that exist within a given hierarchies’ LDM. The data filter uses the filter value assigned to a child workspace to distinguish what data should be made available in this workspace. The data filter compares the filter value to the values in the specified column in the data source tables. If the filter value matches the column value for some data record in a table, this record is made avail

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GoodData Employee
2 years ago
D
GoodData Employee
dan.junGoodData Employee
published in Solution architecture - KB articles

GoodData.CN: Workspace Provisioning

IntroductionOne of GoodData.CN’s core functionalities is the ability to create dedicated client workspaces based on pre-existing template workspace(s) - a concept we call Workspace Provisioning. In your template(s), you can create a standard LDM with a set of measures, insights, and dashboards to roll out to some subset of your clients’ workspaces. Your clients can then customize their individual workspaces without affecting both the master template, nor any other workspaces. In GoodData.CN, workspace provisioning is best achieved using two features: workspace hierarchies and data filtering. Workspace hierarchies define a “parent” template workspace with some number of “child” workspaces that will inherit features and matching data from the parent. These hierarchies can be multi-level, which offers a lot of flexibility on how analytics can be split up. Data filtering can then be applied to each child workspace to ensure only data specific to that workspace can be analyzed. We’ll go int

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D
GoodData Employee
2 years ago
D
GoodData Employee
dan.junGoodData Employee
published in Solution architecture - KB articles

GoodData.CN: Saving Layouts to Git

With GoodData.CN, users can export a JSON Layout file with metadata on configurations for the LDM, measures, KPIs, Insights, and Dashboards. JSON Layout Example: layout.txt You can update your workspace using the variety of built-in editing tools on GoodData.CN. But to commit such changes to a source control tool like Git, you will need to export the Layout file via API using the following command:curl http://localhost:3000/api/layout/workspaces/<workspace_id> \  -H "Content-Type: application/json" \  -H "Accept: application/json" \  -H "Authorization: Bearer <token>" \  -X GET -o layout.json* Substitute <workspace_id> and <token> with your specific parameters This will create a file “layout.json” in your local directory, which can then be submitted to Git. These layout files can serve as backups for restoring workspace to their previous state.  It is to your discretion on how often this layout.json file should be exported, but we recommend that exporting at lea

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D
GoodData Employee
3 years ago
D
GoodData Employee
dan.junGoodData Employee
published in Solution architecture - KB articles

GoodData.CN: Promoting from Development to Production

Over time, you may want to begin pushing updates to your GoodData workspaces for a variety of reasons (ie. adding new dashboards and insights, updates to the LDM, implementing new GoodData product features, etc). To deploy updates safely, we want to focus on a few key points: The ability to programmatically deploy updates in a timely manner. Testing updates before releasing to Production workspaces. Maintaining backups of Production workspaces, and the ability to easily return to a former state. Minimal downtime and disturbance to clients during production releases.  To account for future updates, we strongly recommend maintaining 3 servers, Development, QA and Production, each running GoodData.CN. This way, Development can be used as a sandbox for creating updates, QA is used to safely test those changes, and Production can maintain a clean, client facing status throughout development. Using JSON Layouts for Workspace PromotionJSON layouts are a solution for quickly submitting c

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D
GoodData Employee
3 years ago
D
GoodData Employee
dan.junGoodData Employee
published in Metrics and MAQL - KB articles

Data Modeling - TimeTutorial

A common analytical use case is to segment data by time. For example, grocery stores may need to keep track of what time produce should be restocked to optimize for consumer purchasing patterns and freshness. For these datasets that will need time analysis, Gooddata recommends adding a separate “Time Dimension” dataset in conjunction with the relevant date dimension (see below). In the above image, we see that the “Stock Time” dimension has a primary key on Stock Time, attributes that split out the Hour, Minute, and Second, as well as a Stock Time in Seconds fact. Please note that the Stock Time Epoch fact is kept out of the Time Dimension since Epoch values typically take into account both Date and Time. Within the time dimension, you can add different attribute splits that will aid your ability to further segment your insights. When deciding on each attribute, please keep in mind the following: Adding attributes for any custom intervals (ie. 5 minutes, quarter hour, half hour, etc.)

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GoodData Employee
3 years ago
D
GoodData Employee
dan.junGoodData Employee
published in Data sources - KB articles

ADD - Deleting Data from WorkspacesF.A.Q.

IntroductionThe x__deleted field is an optional field for any and all source data tables that feed Gooddata’s Automated Data Distribution (ADD). However, even if the field can be used on any source table, its utility depends on whether the correlated datasets are being refreshed as a full batch load or incrementally. Incremental vs. Full LoadFull Load: When ADD is set to refresh a dataset by full load, the dataset will be completely rewritten. If the associated source table has the field x__deleted, then only records where x__deleted = FALSE will be distributed to the platform. Recommendation: If the x__deleted field is excluded, ADD full load of a dataset will still operate normally as if all records are defaulted to x__deleted = FALSE. So, the x__deleted field is often unnecessary for full load datasets, and it’s best to exclude this field from such datasets. Incremental Load: For datasets that are loaded incrementally, the x__deleted field becomes the primary way to delete data reco

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GoodData Employee
3 years ago
D
GoodData Employee
dan.junGoodData Employee
published in Dashboards and Reports - KB articles

Drilling Into Insights

GoodData KPI dashboards can be configured to respond to clicks by redirecting, or “drilling”, into other insights or dashboards. This can be a great tool for providing additional context to the end user. Drill to InsightDrilling into another Insight allows the user to see more granular detail about metrics without having to search around for the information. In the example shown below, the drill feature was used to further expand monthly revenue into how revenue was earned by product category. Also notice that the filters (in this case “Month”) applied to the metric where clicked is also applied to the drill in Insight. Look here for more detailed instructions on Drill to Insight. Drill to DashboardSimilarly to drilling into another Insight, drilling into a dashboard is a great way to provide users a view into further analytics into related data. In the example below, you will see that from a “Customer Trend” insight, a user will be navigated to the Customer details dashboard. Here, th

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GoodData Employee
3 years ago
D
GoodData Employee
dan.junGoodData Employee
asked in Administration

Cloning Entire Workspace between Domains

I’m wondering if it’s possible to do a full workspace clone across different domains? I know it’s possible with partial exports/imports, but hoping that it can be done at the workspace level so I can pull over the LDM, all metrics, and all KPIs more easily.

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GoodData Employee
3 years ago
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