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Business Analytics & Data Visualization

Gain insight into your data

For most customers, the wide variety of reports and dashboard analytics offered in RamBase are more than enough to operate their businesses. Then there are business leaders that need to gain deeper insights into their data for better decision-making and communication. Business analytics and visualization tools can be the logical next step for these companies. 


What are Business Analytics and Data Visualization?

The definition of analytics is the systematic analysis of data or statistics, and it's used to discover, interpret, and communicate meaningful patterns in data. When we talk about business analytics, we mean using statistical methods and technologies to analyze historical data to gain new insight and improve strategic decision-making for a business. 

Presenting information can be an art form and research shows that the human brain is more adept at understanding visual graphics than numbers. Data visualization means turning raw data into visual representations, often in the form of charts and graphs. The great thing about data visualization is that people who are not trained in analytics or have prior knowledge of your data will understand the patterns faster and easier.  

API Resource Center

Have an idea for how to use the RamBase API to develop your idea? Jump straight to the developer tools in our API resource center.


External Data Platform

To get started using your RamBase data for custom business analytics and data visualizations, you need to decide what external data platform you want to use. Depending on what you need to report, the data platform can take many forms.

  • The simplest data platform can be extracting data to an Excel document
  • Another alternative can be using more advanced data platforms like Power BI

Using an external data platform gives you more options to customize your analytics and visualization output to your specific business needs.


Data Extracting Solutions

Data is extracted via an ETL process (Extract, Transform, Load) which enables data to be extracted from the RamBase service, transformed or processed, and finally remodeled to fit the desired analysis platform.

The ETL process is not limited to retrieving data only from RamBase. Data can be extracted from multiple sources and consolidated into one centralized location, resulting in a broader basis for data management strategies.

RamBase currently provides the following three options for extracting data from the system:

  • API-based
  • File-based
  • Database mirroring

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. 


Getting started

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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.


Getting started


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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. 


Getting started



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