Megaladata ETL

Extract, Transform, Load
Transform raw data into business-ready insights: gather data from various systems, refine it to meet your specific needs, and transfer it seamlessly into the designated database.
ETL

Source data usually has issues

Problems may occur at various levels: data structure, schema, record, value, features, staging area...
With the low code analytical platform Megaladata you can solve problems of any level without the need to code oruse SQL-like tools. The intuitive user interface provides the opportunity for any transformation.

Megaladata — the best choice for ETL

Megaladata supports dozens of options for the data preparation process, consolidation and integration of data from multiple sources
  • Megaladata ETL: Extract
    Extraction
    Define the necessary subset of the source data: files, databases, web services or business applications
  • Megaladata ETL: Transform
    Transformation
    Convert the extracted data into a usable format determined by business rules
  • Megaladata ETL: Load
    Loading
    Transmit the processed data to your data warehouse or business application

Data Extraction

Data sources can be various: files, spreadsheets, database tables, data pipes, etc. To extract the data, each source needs to be managed and consolidated.
Databases
Oracle, MS SQL, PostgreSQL, ClickHouse, BigQuery, MySQL...
Files
Excel, CSV, XML, Megaladata Data File
Business applications
Creatio, Tableau
Data warehouses
Oracle, MS SQL, Firebird
Web services

SOAP (WSDL), REST (JSON)

ODBC sources
Hive, MongoDB, Amazon Redshift, SQL Azure...

Data Transformation

After extraction, data must be physically moved to the target destination and converted into the relevant format. This stage includes cleaning, joining, validation, generating data features calculated from existing values, and so on. Megaladata offers more than 50 tools for data transformation, based on simple and complex algorithms. Here are some of them:

Data Loading

The final step in the ETL process is making the data presentable to the user. The transformed data can be saved into databases or warehouses, or imported into business applications.
  • Data warehouses
  • Subject-oriented
  • Integrated
  • Time-variant
  • Databases
  • Oracle
  • MS SQL
  • PostgreSQL
  • MySQL
  • Business applications
  • Tableau
  • Qlik
  • Creatio

Low code

Megaladata is not simply a drag-and-drop tool — it is a visual-oriented pipeline editor for comprehensive data processing.

The low code analytical platform Megaladata is designed to make the analytical process an easier and better experience for everyday business users with no need to involve the IT department. This allows companies of any size to maximize their resources and encounter the solutions requires to stay competitive.
Megaladata Low-Code

JavaScript, Python and SQL support

Built-in Python enables easy integration with Pandas, the de-facto standard library for working with structured tabular data, and opens the way for advanced data analysis with a broad variety of Python packages available for free. Within workflows you can use JavaScript code to perform data transformations or create a new data structure. For input/output operations you can also use SQL scripts.

Result

Collaboration between data analysts and IT departments is important for successful digital transformation of any organization, and the low code platform Megaladata can help make this process simpler.
  • Speed
    Solve data preparation issues up to 10 times faster than using traditional methods
  • Simplicity
    Save everyday business users from complex interaction with source data
  • Low cost
    No need for a strong programming background for users decreases the cost of your data analysis
  • Reusability
    Shift from abstract notation and turn your ideas into custom executable components for repeated use

Download Megaladata

Megaladata Community Edition is a free version for non-commercial use