One of the most crucial steps for any company in making accurate and sound decision-making lies in its data. Data is of no use if it can't be handled and goes unutilized. For better data insights, companies need to diligently integrate, manage, and analyze the data that aligns best with their business goals. Here comes the concept of data integration. Data integration gives a holistic and unified view of data by combining it from different sources and keeping it in one place. What does this ultimately lead to? This unified data can lead to better decision-making, providing a complete understanding of business operations, customers, and market trends. Here is a list of widely used Data Integration techniques that can offer better data analytics for better decision-making ETL (Extract, Transform, Load) ETL is the most opted-for technique preferred by companies. It extracts data from various sources, transforms it, and loads it into the targeted data warehouse. Companies can adopt a real-time or batch ETL approach. The former allows the transformation and load of data as soon as it becomes available and the latter processes data in batches and then loads it as per a predetermined schedule. EDR (Enterprise Data Replication) Within a company's IT infrastructure, Enterprise Data Replication (EDR) is a technique that involves the continuous and real-time copying of data from one location to another. Enterprise Data Replication ensures data warehousing across heterogeneous systems with consistent and correct information. EII (Enterprise Information Integration) Often, companies waste too much time understanding and accessing the right data. Instead of spending too much on the right data source, companies can employ a virtual data layer. Through the virtualized data layer, all data of different interfaces and formats and even of heterogeneous sources gets collected in one centralized system allowing it to be accessed by anyone from anywhere. Change Data Capture (CDC) Tools CDC tools replicate changes made to other systems while simultaneously capturing changes made to databases. This helps preserve data consistency between several systems. CDC tools resolve the problem of bulk data updating and inconvenient batch processing by making real-time changes to data in the target repository. Furthermore, CDC is a perfect tool for the cloud, as it can move data across a wide area network. Conclusion It is now quite clear that integrating data is the first step to unlocking its full potential. When companies have all the data located in one place, it becomes convenient to get better and more accurate data insights, which further helps with decision-making. have now been widely adopted by a majority of industries, including healthcare, retail, telecommunications, and many more to improve business operations. Data integration techniques

Unique Techniques to Integrate Enterprise Data

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

A Subreddit Where Only AI Chatbots Can Post

Setting up Data Streams Using NiPyAPI: UI-Free Guide

The Noonification: How Often Do NFTs Pass The Howey Test? (1/13/2023)

03/09/2018: Biggest Stories in the Cryptosphere

The Noonification: Immigrant Teens Are Working Dangerous Night Shifts in Factories (11/21/2022)

The Noonification: How to Implement a Merkle Tree in Solidity (11/12/2023)

A Subreddit Where Only AI Chatbots Can Post

Setting up Data Streams Using NiPyAPI: UI-Free Guide

The Noonification: How Often Do NFTs Pass The Howey Test? (1/13/2023)

03/09/2018: Biggest Stories in the Cryptosphere

The Noonification: Immigrant Teens Are Working Dangerous Night Shifts in Factories (11/21/2022)

The Noonification: How to Implement a Merkle Tree in Solidity (11/12/2023)

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps