Data connections allow you to access your data wherever it is.
There are many systems that contain data and each one works differently. In Biuwer we have a catalog of connections where you can find those data connection types that are supported natively by the platform.
Biuwer is a business data analytics platform and therefore most connectors correspond to SQL or NoSQL databases. However, you can also upload your data stored in files with a CSV or Excel extension and we are also continuously working on expanding the catalogue of connections, especially with cloud applications. If you have any specific requirements, please don't hesitate to contact us through the online support.
Connections that my Organization has defined appear on the following screen.
My connections in the Data Center
From the "My connections" menu, we can see the most relevant information regarding connections, shown in a list:
Name and description given to the connection
Number of Datasets associated with the connection
Number of Data Models associated with the connection
Connection creation date
From the screen we can perform the following operations:
Search and filter connections using different criteria
Sort connections using different criteria
Add a connection
Access the editing details of a connection
Test a connection
Disable a connection
Perform a reverse engineering over a connection
Delete a connection
Available options about a data connection
You can directly access the "Connection Catalog" to create a connection from the left side menu of the Data Center or by clicking the "Add" button in the upper right corner of "My Connections" list.
All possible technologies you can connect to, available in Biuwer, are shown in this catalog, and they are searchable by name and category.
Connection Catalog in the Data Center
When you click on one of the options shown, depending on the technology you will be asked to configure some details or others.
For example, to create a new connection to a PostgreSQL database you need to configure the following parameters:
Creating a new PostgreSQL connection
You can check if the connection parameters are correct by pressing the "Test Connection" button, before saving the connection.
In order to ensure access to your databases, you will need to make sure your server is configured to allow the Biuwer IP address to connect. You can find this IP address in the connection creation page.
The available options in the connection catalog that allow you to upload data contained in CSV or Excel files to Biuwer use a file importer.
Importing data contained in a CSV file
To select the file to be uploaded to Biuwer, you can either drag it from a local file browser or click on the box. As soon as the file is selected, you can process it by clicking on the "Process file" button. This reads the contents of the file and detects the columns, their data types and formats, using the default settings.
As every data file is different, it is most likely that you will need to make some adjustments and try out various settings among those available in the file importer.
Available options to import data from CSV files
You can set up the following:
Character assigned to quotes (in text type fields)
If the first row of the file contains the name of columns
If you want to omit the first N rows of the file
What is the format of dates within the file
What is the format of boolean-type fields in the file, that is, what value corresponds to True and what value corresponds to False.
What is the number format (thousands character and decimal character)
Before proceeding with the import by pressing the upper right "Import" button, you can adjust any of the above parameters. With each change the file will be reprocessed and you will be able to:
View a data preview (first 30 rows are shown).
Select all or some of the fields. This is important because if the file contains, for example, 20 fields but only 12 of them are to be analysed, the 8 that are not of interest may not be selected and will not be uploaded to Biuwer.
For each selected field, Biuwer auto detects and sets its data type and whether it is a Metric or a Dimension type field.
Dimension type fields. They are used for those descriptive fields or those containing categorical information, by which we will be able to make an analysis or filter. For example, dates, product categories, customers, products, geographical locations, etc.
Metric type field. They are used for those numerical fields (most of them) that contain values to be counted, summed, added, etc. For example, sales amounts, number of hours spent, account balances, purchase costs, etc.
Sometimes it can be interesting to apply a numerical analysis to fields of type Dimension, for example, to count how many products or customers you have. This can be done interactively in the Data Card Editor or by creating a specific Metric type field for those cases, in addition to the corresponding Dimension field (this last option is not the most recommended way, in order to maintain Datasets as simple as possible).
This tool allows users to easily define Datasets in Biuwer. It has been created to make it as quick and efficient as possible to create and maintain datasets and all data fields to be analysed over time.
Reverse engineering is only available on certain Data Connections that allow it, as it consists of Biuwer connecting to the database system or remote API and scanning which data entities exist, how they are called, which fields they have and what types of data they are.
To configure reverse engineering, you can access directly from the "Reverse Engineering" menu, available in the left side menu of the Data Center, or from the list of connections or dataset tab, in its fields tab.
To configure reverse engineering you must select a connection and if that connection has containers, select one or more of the available containers, before clicking on the "Read Datasets" button. Results are presented visually in a list of data entities, with their fields and data types.
Reverse engineering facilitates the management of datasets in certain compatible connections
On this screen, before you import datasets into Biuwer by clicking the "Import" button in the upper right-hand corner, you can do the following:
Select datasets you are interested in using with Biuwer. Use individual selectors or "Select all" or "Deselect all" buttons.
In turn, by opening datasets, the fields you can select are displayed, with their original data type (in the remote database or API) along with the data type in Biuwer and the field type (Dimension or Metric).
Certain types of data are not supported by Biuwer. For example, complex data types, such as user-defined data types in origin, binary fields, value arrays, other complex structures, etc. If you have a field data type that is not supported and you need to analyse it, please contact support to help you.
Types of data not supported by Biuwer in reverse engineering
When importing Datasets from reverse engineering:
New Datasets that do not already exist in Biuwer will be created, with the selected fields and the specified configuration.
Datasets that already exist in Biuwer will be modified, modifying fields that have been selected that already exist, or adding the new fields.
The proper use of reverse engineering of data can greatly facilitate the evolutions we may have over time in our data sources, such as new tables, new views, new fields, changes of names or changes of data types.
When changes may occur in a data source (fields are deleted, data types are changed, etc.) and these changes are not reflected in Biuwer, errors can occur when making data queries. We recommend that you keep track of your changes to avoid these errors.
When Reverse Engineering is launched from the Fields tab of a Dataset, the screen will appear already configured with the data connection and the selected dataset is displayed.
Reverse Engineering on a dataset
In this case, only if there have been changes in source data fields or in their data types, we will be able to select them to update the dataset in Biuwer. Otherwise, as shown in the image, we will not be able to select any field to add or modify to the dataset.