Data science

What is Data Integration?

Data Integration is the process of unifying data from multiple sources into a single, centralized location. Data Integration tools are must to transfer the data from various sources to the destinations. The final destination must be flexible enough to handle a wide range of types of data in potentially enormous quantities. Its primary objective is to produce consolidated datasets that are clean and consistent, as well as to fulfill the information needs of various end-users within an organization. Data Integration ultimately enables analytics tools to produce effective, actionable business intelligence, done as it is often a prerequisite to other processes such as analysis, reporting, and forecasting.

 

Different Data Integration Technologies

Extract, Transform, and Load (ETL): In this process, data from various source systems is collected, transformed, and loaded into a target destination such as Data Warehouse or Database.
Extract, Load, and Transform (ELT): In this process, data is imported into a big data system, typically a Data Warehouse, and transformed afterward for specific analytics purposes.
Change Data Capture (CDC): It is a process that detects data changes in databases in real-time and applies them to a Data Warehouse or other repositories.
Enterprise Data Replication (EDR): It is a real-time data consolidation method in which a dataset is moved from one Database to another having the same schema to maintain the information synced for operational and backup purposes.
Enterprise Information Integration (EII): EII is a technology that enables developers and business users to treat multiple data sources as if they were a single database and present the incoming data in new ways.
Data Virtualization: Rather than putting data into a new repository, in this process, data from disparate systems is virtually merged to provide a unified view.
Streaming Data Integration: It is a real-time Data Integration method that constantly integrates and feeds diverse streams of data into analytics systems and data stores.

 

Advantages of Data Integration in Business

It helps enhance collaboration and unification of systems.
It saves time and boosts efficiency.
It also reduces errors and repetitive work.
It helps deliver more valuable data to the Business.
It helps in making seamless and fast connections.
All the data is available to the stakeholders in one place and in real-time.
It helps achieve Data Integrity and improves Data Quality.
It helps in increasing the competitiveness of the Business.

 

Key Data Integration Tools
Here are a few Data Integration tools that you can leverage based on your unique requirements:

 

Hevo Data

A fully managed No-code Data Pipeline platform like Hevo helps you integrate and load data from 100+ different sources to a Data Warehouse/Database or a destination of your choice in real-time in an effortless manner. Hevo with its minimal learning curve can be set up in just a few minutes allowing the users to load data without having to compromise performance.

Here are a few salient features of Hevo:

Connectors: Hevo supports 100+ integrations to SaaS platforms, Files, Data Warehouses, Databases, Analytics, and BI tools. It supports various destinations including Google BigQuery, Amazon Redshift, Snowflake, Firebolt Data Warehouses; Amazon S3 Data Lakes; and MySQL, MongoDB, TokuDB, DynamoDB, PostgreSQL databases to name a few.
Real-Time Data Transfer: Hevo provides real-time data migration, so you can have analysis-ready data always.
100% Complete & Accurate Data Transfer: Hevo’s robust infrastructure ensures reliable data transfer with zero data loss.
Support and Training: The Hevo team is available round the clock to extend exceptional support to you through chat, email, and support calls. Hevo also has several helpful videos on their channel to help you understand its basics.

 

Matillion

Matillion is known as a Cloud-based ETL platform that enables your data journey by extracting, migrating, and transforming your data in the Cloud. This helps extract actionable insights from the data and make better decisions.

Here are a few key features of Matillion:

Connectors: Matillion integrates with 60+ data sources across categories like Social Networks, Finance, Erp, Crm, Databases, Internet Resources, Marketing Communications, Files, and Document Formats. For a new use case, customers can request Matillion to build a new data source.
Transformations: Matillion provides support for post-load transformations through its Transformation components. Any user can create a Transformation Component by point and click selection or by writing SQL queries. The point and click selection allow you to drag any component onto Matillion’s visual workspace at a specific point in the Data Pipeline.
Support and Training: Matillion provides support through an online ticketing system that can be accessed in two ways: its support portal or by email. Documentation is based on articles that can be accessed through the support portal. Matillion doesn’t offer training services for its platform.

 

Fivetran

Fivetran provides automated Data Integration that is built on a fully managed ELT architecture. Fivetran’s idempotent core architecture makes it resilient to data failures and data duplication while minimizing computational costs.

Here are a few key features of Fivetran:

Connectors: Fivetran provides connectors for various data sources. It supports 150+ connectors, consisting of SaaS Data Sources, Databases, Data Warehouses, File-based Data Sources, etc.
Transformations: Fivetran doesn’t transform data before loading. Fivetran has started offering support for post-load transformations through copy-and-paste SQL only recently.
Support and Training: Fivetran provides in-app support along with comprehensive documentation of its services. However, Fivetran doesn’t offer any training services for the platform.

 

Conclusion
This blog talks about Data Integration and its benefits for Businesses. It also gives a brief overview of different Data Integration tools.

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