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McKinsey famously said that “APIs are the connective tissue in today’s ecosystems [of technologies and organizations] … and have now become a significant engine of business growth.”
Introducing the Sisense Data Model APIs
The new Sisense Data Model APIs extend the capabilities provided by the Sisense REST APIs. Builders will be able to programmatically create and modify Sisense Data Models using fully RESTful and JSON-based APIs.
You may be asking “What’s a Sisense Data Model, exactly?” Great question! The Sisense Data Models refers to the data model schemas of Sisense ElastiCube and Live Data Models. These models are crafted by data teams to facilitate the analytics needs of internal stakeholders and customers, like dashboards and embedded analytics.
Automate your data workflows
The Data Model APIs’ most powerful functions help you automate key workflows. For example:
- Create and duplicate data models: Programmatically copy and paste your data models, or create one from scratch with predefined rules.
- Modify source connections and schema structure: Change the underlying data sources to switch tenants or environments or change, remove, and delete entities within the data model schema to manage change.
- Move data assets across environments: Import and export data models and data across environments.
- Start and schedule data loads: Create and orchestrate custom data loads and live model publish schedules to meet every need.
Data Model API key use cases
What can we do with the Data Model APIs and why are they important? Let’s look at a few popular use cases to understand how the Data Model APIs can be used.
Automate deployment of new customers
If you provide analytics to your customers and host single-tenant or hybrid Sisense Data Models (one ElastiCube per customer), then you might be duplicating data models for each customer. Instead of manually saving a copy, making changes to the data models, and running builds, the Data Model APIs could help you programmatically automate this process.
Automate dev-to-prod flows
Software development best practices require teams to have at least a development environment and production environment. Having a dev environment to build and test in before pushing to production has many benefits, but it also means that teams end up moving assets between these environments a lot. The Data Model APIs can programmatically automate these asset movements, saving you time and effort.
Schedule custom data loads
Sisense provides UI-based custom data load schedules, but if you need a more granular schedule that is based on a specific workflow or trigger, the Data Model APIs now allow you to do so at the code or script level.
Create data models from predefined rules
What if you have a database and use certain rules to custom build a data model? For example, create a particular table, create another table, create this relationship, create a custom SQL table, and so on… all to build a custom data model. The Data Model APIs provide endpoints to build an entire data model from scratch and modify them.
Automate Change Management
Here is another very manual, very granular scenario: you have 50 similar data models from data source A. After some time, a name changed in data source A, how do you go through and update the 50 data models? This can be a painstaking and time-consuming process to do manually. Again, here the Data Model APIs can help automate that change.
Automate Disaster Recovery
Finally, let’s talk about a disaster scenario: The worst has happened and all your machines have crashed. The Data Model APIs can help restore the data environment rapidly and programmatically.
API-Driven automation helps you scale
But what does all this mean and why should you care?
Quicker time to value
The biggest advantage to API-driven automation is that you can bring your products to market faster with shorter deployment lifecycles. With one click of a button, you can have an entirely new deployment spun up with the data models and dashboards ready to go in minutes.
Humans are prone to errors, especially when it comes to manual tasks. Second, not setting up automated disaster recovery and tests increases the risks of long outages. Automating workflows can reduce these chances of error and improve system resilience.
Enhanced User Experience
Ultimately, the Data Model APIs enable builders to handle custom and complex data workflows which ultimately enhance the end-user experience with shorter wait times for insights, fresher data, and minimal interruptions to the experience.
Learn about the Sisense Data Model APIs
The Data Model APIs can handle a wide variety of tasks for you.
To get an in-depth look at them, join us at our demo-focused webinar “Hands-on with the new Sisense Data Model APIs: Automate Your Data Workflows” on March 11th, 2020 at 11 AM Eastern Time.
Shruthi Panicker is a Sr. Technical Product Marketing Manager with Sisense. She focuses on how Sisense can be leveraged to build successful embedded analytics solutions covering Sisense’s embedding and customization capabilities, developer experience initiative and cloud-native architecture. She holds a BS in Computer Science as well as an MBA and has over a decade of experience in the technology world.