Business Analytics & Data Visualization

API over public internet endpoint

This method uses the RamBase REST API which has many endpoints for retrieving data entities and sets for analytical purposes. The RamBase REST API is implemented with paging support for retrieving data sets. To use this method the external data platform needs to have the capability for paging (or looping) through a data set. 

How it works

Each call to the API endpoint will return a specific number of data elements (a «page») and instructions for how to retrieve the next «page» of the set. When no more data is available, the result will indicate that no more pages are available. 

Most modern ETL tools and services have this capability, for example, Azure Data Factory. ADF will typically be part of a data platform set up in Azure. There are many other options to go for.

The RamBase REST API has endpoints for curated sets of data. These can be viewed as "standard reports" by a RamBase user. These sets are very efficient as input to external analytical workloads, as much of the work of piecing together the data has already been done internally in RamBase. 

Scheduled exports of CSV-files 

This method is for those scenarios where extracting data through APIs is not favorable, and file transfer is the preferred solution. Sometimes the client will have an existing BI solution that only allows for more simple extracting formats: this method enables file transfer with RamBase and requires less programming. 

How it works

The file export process can be triggered manually or scheduled at regular intervals or times. 

The typical use of this method is to push data from standard reports (examples) or "curated sets" of data for external processing. The RamBase application can create and send files in CSV format to external file services like FTP servers, cloud storage services, and email accounts. 

There is also the option to push these data sets to external SQL database tables. In this case, the SQL database tables will mimic the CSV file in its layout, and the scheduling process will be as for files.

Mirroring of business data

This method copies the tenant's production database to a mirror database. The replicated data is updated continuously, meaning you can work with nearly real-time data. Companies will choose this method because of the many possibilities raw data output represents and when they already have the infrastructure in place. 

How it works

The mirror database tables provide an almost real-time update on changes to the production database which means you can support custom querying against the raw data model of RamBase. Knowledge about the basic structure of the raw data model of RamBase is needed to be productive with this solution.  

Microsoft SQL Server database or an Azure SQL database is required as an external database, to support this method. For both options, specific RamBase IP addresses must be safelisted, and access must be provided through firewalls. 

Credentials with DDL rights must also be provided. Scaling resources for the external database may need to be tuned to meet certain minimum performance levels.​

To increase productivity, RamBase provides a set of database views that simplifies some of the low-level challenges of working directly with the basic RamBase data model in queries. These views are replicated from the production database as well.