What is Blendata Enterprise

Blendata Enterprise

Streamline big data management, all functions on one platform

Streamline big data management,
all functions on one platform

Streamline big data
management, all functions
on one platform

It is a platform that acts as a medium between data and users to streamline complex data
management through a convenient all-in-one system covering data ingestion, processing,
analysis, and usage readily available for all data missions of the data-driven generation.
It is a platform that acts as a medium between data and users to streamline complex data management through a convenient all-in-one system covering data ingestion, processing, analysis, and usage readily available for all data missions of the data-driven generation.
Key Benefits

Streamlined big data management

Streamlined big data management

It streamlines data management, reduces installation time, and allows you to manage all processes on one platform, from data integration to utilisation. It is both engineering and end-user low-code/no-code solutions without any coding knowledge requirements.

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What
Blendata Enterprise
Do
Blendata Enterprise:
Comprehensive big data
management on one platform
Multiple connectivity
Connect and collect data from all sources including flat files (CSV, JSON, Plain text, Parquet, etc.), databases (Oracle, MS SQL, MySQL, etc.), Cloud and Stream through built-in connectors without coding.

Dynamic data import

Import data from flat files, log databases, or cloud storage automatically through built-in connectors in the following schemes.

  • Scheduled replication (Batch/Stream)
  • Data virtualization
  • Changed data capture

Extract, transform, and load upon import (ETL)

Transforms data upon importing with Spark SQL that comes with various data transform functions to support big data.

Automatic schema creation

The engine of Blendata automatically searches the attributes and creates the schema for all import tables including files, databases, or streaming through Kafka modifiable by the user through GUI.

What Blendata Enterprise Do
Blendata enterprise:
Comprehensive big data
management on one platform
Multiple connectivity
Connect and collect data from all sources including flat files (CSV, JSON, Plain text, Parquet, etc.), databases (Oracle, MS SQL, MySQL, etc.), Cloud and Stream through built-in connectors without coding.

Dynamic data import

Import data from flat files, log databases, or cloud storage automatically through built-in connectors in the following schemes.

  • Scheduled replication (Batch/Stream)
  • Data virtualization
  • Changed data capture

Extract, transform, and load upon import (ETL)

Transforms data upon importing with Spark SQL that comes with various data transform functions to support big data.

Automatic schema creation

The engine of Blendata automatically searches the attributes and creates the schema for all import tables including files, databases, or streaming through Kafka modifiable by the user through GUI.

Customizable user access

Customizable access rights in clear detail covering from data access, visualisation, dashboard, and all functions on the platform.

Global standard data security

Row-level security, table or columnar encryptions and be able to integrate with Key Management System (KMS) externally to enhance the encryptions process (additional option).

Lifecycle Management

Customizable data tiering level whether Hot/Warm/Cold to determine the data compression and data retention category.

Multi-location storage

Support multi-storage location interlinking, multiple-device data tiering.

Advanced data management

Support advanced data management such as data compaction, data compression, data lifecycle management (hot-warm-cold), data skipping, predicated push-down, dynamic partition pruning, and physical file partitioning.

SQL Analytics

Cover data preparations, transformations, correlations, aggregations, and data exploration UI that enables analyzers or engineers to query with familiar grammar, together with ANSI SQL + Spark SQL functions, and allows analyzers or engineers to survey, manage, or schedule processing job for their own data.

Data Preparation Workspace

Offer the same data preparation engine and functions as SQL analysis (data exploration UI) but with a more user-friendly approach to support low-code/no-code data preparations for non-technical users within a matter of seconds.

Notebook Interface

Offer a familiar experience to data engineers and ML developers with a notebook interface that supports all well-known programming languages, such as Python, R, Scala, and SQL.

Job scheduler and chain job setting

Set tasks to run on a schedule with the built-in Job Scheduler function and link all tasks together for complex jobs from the beginning to the end.

Visualization & Dashboard

Transform search and analysis results to user-friendly visualisation that can be dragged and dropped directly on the interface with many presentation charts available which can be categorised on a dashboard right away. It comes with data filtering and drill-down functions that can be created as a big data application ready to be shared among co-workers.

Notification

SQL-based notifications to be made via the web console, email, script, or API (additional option).