Algolytics Technologies Documentation
  • End-to-end Data Science Platform
  • ABM
    • Introduction to ABM
    • Repository
    • Classification - adding, running and deleting projects
    • Approximation - adding, running and deleting projects
    • Models and variables statistics
    • Model deployment
    • ABM API
    • Data scoring
    • Adding, running and deleting projects
  • Event Engine [user]
    • Engine description
    • How the engine works
    • Events
    • Aggregate module
    • Metadata
    • Components of metadata
    • Off-line processing and modeling
    • Examples of API operations
    • Visualisation
  • Event Engine [administrator]
  • Scoring.One
    • Engine description
    • Panels overview
    • Implementation of scoring models
    • Creating and testing a scenario
    • SCE Tracking Script
  • Advanced Miner
    • Documentation
    • How to install license key
  • DataQuality [web app]
  • Algolytics APIs
    • DQ for Python API
    • Scoring Engine WEB API
    • ABM Restfull API
    • Other APIs
  • Privacy policy
  • GDPR
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On this page
  • Introduction to working with data in ABM
  • Uploading files
  • Importing files
  • Step 1: Choosing a file for import
  • Step 2: Entering file settings
  • Step 3: Naming the table with source data
  • Step 4: Summary
  1. ABM

Repository

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Last updated 4 months ago

Introduction to working with data in ABM

In the ABM Repository, you can store all the files you want to use in your projects and files with scoring results (generated automatically by ABM).

All files for modelling and scoring need to be to the ABM server. They are transferred securely using SSL protocol and stored in the . The current ABM release allows you to upload .csv files (other formats are planned).

If you want to use a particular file for modelling you also need to . From then on, the imported data becomes one of the tables (with the name given to it by you) in the ABM database. This will make all the tasks performed on this data more efficient. You will be able to use this particular table in other projects, too.

To access the Repository, choose the Repository icon from the left menu. There are three bookmarks available.

You can execute the following actions:

  • Uploaded files

    • Open: in order to open a selected file, click its name

    • Import: in order to import data to ABM’s database, click the Import icon

    • Delete: in order to delete a selected file, click the Delete icon

  • Files imported to database

    • Delete: in order to delete a selected dataset, click the Delete icon

  • Scoring results

    • Open: in order to open a selected file, click its name or the Open project icon

    • Delete: in order to delete a selected file, click the Delete icon

Uploading files

Before you start to build your predictive models, you need to upload a file with the source dataset:

  1. Go to Repository by clicking the Repository icon from the left menu and choose the Uploaded files bookmark

  2. Click the Upload button

  3. Click the Browse for files button and select the target file from your computer

  4. Upload the file with the Upload button

  5. After selecting your file, wait until it’s uploaded

Importing files

You can import a file to the ABM internal database in two ways: from the Repository level or while adding a new project.

Importing files from Repository

  1. Go to Repository by clicking the Repository icon from the side menu and choose the Files imported to database

  2. Click the Import button and follow Steps 1,2,3,4 described below

Importing files while adding new project

The importing files process is divided into four steps:

Step 1: Choose uploaded .csv file

Step 2: Enter import settings

Step 4: Check if the information provided is correct

Step 1: Choosing a file for import

Select a previously uploaded file from the list (or if it’s not on the list, upload it now):

  1. Click Browse for files button and select the source file from your computer

  2. Upload the file with the Upload button

  3. After selecting your file, wait until it’s uploaded

Choose the Next button.

Step 2: Entering file settings

  • Columns separators. For instance, if columns in CSV file are separated by a comma (e.g. name, email, age), write , in the first field

  • Decimal separators. For instance, if a decimal character is a dot (e.g. 4.25) in CSV file, then write . in the second field

  • Text separators. For instance, if a quotation mark is used to indicate the beginning and end of the text (e.g.’Baker Street 221b’), write ‘ in the third field

Then choose the Next button to proceed or the Back button if you want to change the previous settings.

Step 3: Naming the table with source data

Enter a name for the table in the ABM database where your source data will be stored. The table name should include only letters (a-z, A-Z), numbers (0-9), dashes (-), underscores (_).

Then choose the Next button to proceed or the Back button if you want to change the previous settings.

Step 4: Summary

The last thing you have to do is to check the correctness of the information shown in the Summary.

Then choose the Finish button or the Back button if you want to change the previous settings.

It is also possible to upload a file during the first step of the process or during the process. In both cases, follow steps 3-4 described above.

It is also possible to import files to the ABM internal database during the first step of . Click the Add new data button and follow Steps 1,2,3,4 described below

Step 3:

File encoding. Choose the character encoding used in your file. If you need to add specific encoding to the list, contact us at

Now you are ready to ! Go to Homepage and click the Add new project button.

adding a new project
importing files
adding new project
Name the table in the ABM database
abm_support@algolytics.com
add new project
uploaded from your computer
Amazon Elastic Compute Cloud
import it from server to ABM internal database