Name: Data Pipelines In Minutes Using Data Movement Wizard In Diyotta
Uploaded: 2020-06-04T19:29:42.000Z
Duration: 2 min 26 s
Description: Learn how to create multiple data pipelines from Oracle tables to Snowflake using Diyotta's Data Movement Wizard!

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Vertical-Specific

Find top rated software and services based on in-depth reviews from verified users. 400+ software categories including PaaS, NoSQL, BI, HR, and more.

Domo

Oracle Data Integration Platform Cloud (DIPC)

Oracle

IBM DataStage

Azure Data Factory

Microsoft

SQL Server Integration Services

Matillion

Oracle Data Integrator (ODI)

Informatica PowerCenter (legacy)

Discontinued Products

Talend Data Integration

Qlik

SolarWinds Task Factory

SolarWinds

dbt Labs

Talend Open Studio

Fivetran

Matillion is a data pipeline platform used to build and manage pipelines. Matillion empowers data teams with no-code and AI capabilities to be more productive, integrating data wherever it lives and delivering data that’s ready for AI and analytics.

Basic

Advanced

Developer: For Individuals

Astera Data Pipeline Builder is a no-code solution for designing and automating data pipelines. It allows users to read and write data across various file formats, databases, and applications. Users can execute ETL and ELT pipelines manually, schedule automated reruns, or integrate them into broader data management processes.

Centerprise Enterprise

Astera Data Pipeline Builder (Centerprise)

Diyotta

Data integration involves combining data residing in different sources and providing users with a unified view of these data.

Data Integration

CloudSync Product Demo

The Bulk Data Migration is an ideal solution for all, including the users who do not wish to indulge in any major data transformation during the data migration process. In 5 easy steps, a user can define the source location of the data, select the elements which they wish to migrate (a user can specify the tables and fields to be migrated), and provide the destination credentials. The tool has the in-built smarts to suggest/flag the table size through which a user can know which tables migration they may want to stagger versus running with the migration in parallel.

Modern data integration principles were created because of traditional data integration solutions’ architectural and scalability constraints. Diyotta’s MDI suite delivers fast, scalable, and efficient modern data integration solutions.

Diyotta & IBM Deliver Joint Big Data Solution To A Large Telecom Customer

Get the most out of your BigQuery data warehouse by connecting to all your data, no matter where it resides, in motion or at rest, stored on-premises or in the cloud.

Get the most out of your Redshift data warehouse by connecting to all your data, no matter where it resides, in motion or at rest, stored on-premises or in the cloud.

Get the most out of your Snowflake data warehouse by connecting to all your data, no matter where it resides, in motion or at rest, stored on-premises or in the cloud.

DIYOTTA 4.0 IS THE BENCHMARK FOR MODERN DATA INTEGRATION.

Learn how to create multiple data pipelines from Oracle tables to Snowflake using Diyotta's Data Movement Wizard!

Data Pipelines In Minutes Using Data Movement Wizard In Diyotta

Data Source Connection

Ability to connect to multiple data sources

Connect to traditional data sources

Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications

Connecto to Big Data and NoSQL

Ability to connect to non-traditional data sources like Hadoop and other big data technologies, and NoSQL databases

Data Transformations

Data transformations include calculations, search and replace, data normalization and data parsing

Simple transformations

Simple data transformations are calculations, data type conversions, aggregations and search and replace operations

Complex transformations

Complex data transformations are data normalization, advanced data parsing, etc.

Data Modeling

A data model is a diagram or flowchart that illustrates the relationships between data

Data model creation

Ability to create and maintain data models using a graphical tool to define relationships between data

Metadata management

Automated discovery of metadata with ability to synchronize and share metadata with other tools like Master Data Management

Business rules and workflow

Ability to define and manage business rules and workflows

Collaboration is enabled by a shared repository of project information and metadata

Testing and debugging

Tool to debug and tune for optimal performance

Data Governance

Data governance is the practise of implementing policies defining effective use of an organization's data assets

Integration with data quality tools

Integration with tools for cleansing, parsing and normalizing data according to business rules

Integration with MDM tools

Integration with master data management tools to ensure data consistency across the organization

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