Introduction

The process of combining and collating data from multiple sources into a unified, single view is referred to as Data Integration. The process starts with the ingestion process. It includes several steps like ETL Mapping, cleansing, and transformation. The process finally enables analytic tools to provide actionable, effective business intelligence.

  1. Data Integration Meaning
  2. Data Integration Techniques
  3. Benefits of Data Integration Services

1. Data Integration Meaning

The client sends a request to the master server for data in a standard data integration process. The master server then takes the needed data from external and internal sources. Data extraction is done from several sources and is then combined and consolidated into a cohesive and single data set, served back for the client use. In a nutshell, it is the best data integration meaning understood in simple words. Read this post to understand the benefits of data integration and how it can help your business. 

What is Data Integration?

Today, data integration has become very common, and many people have questions about what is data integration? This commonly used industry term refers to the need for combining data into a single unified view from multiple separate business systems. It is also referred to as a single view of the truth. The combined data as a unified whole is stored in a data warehouse, a central data repository.

The process can be understood with the help of an example. The data integration for a customer requires information extraction from diverse business systems like accounts, sales, and marketing. It is then brought together into a single customer view and utilized for reporting, customer service, and analysis. A variety of data integration tools are used for this purpose. 

2. Data Integration Techniques

Experts use a variety of Data Integration Techniques to complete the process with the utmost efficiency. Some of the techniques used are-

  • Data Consolidation- It is the process of combining and consolidating data from multiple sources to create a centralized data store or a repository. This single, unified data is used for various purposes like data analysis and reporting. 
  • Data Federation- It is one of the data integration techniques wherein consolidated data is used. Access to consuming front-end and users’ applications is also simplified. Data is distributed with distinctive data models, and the same is integrated with a virtual database featuring a single data model. 
  • Data Propagation- It is another data integration technique where data is sourced from an enterprise data warehouse. This data is then transferred after the required transformations to different data marts.

Many companies and enterprises look for high-end data interpretation services. It is imperative to look for a company known to provide affordable and flexible data integration solutions. It is a better alternative to traditional commercial solutions that costs a fortune. Moreover, it also requires reengineering of existing IT systems. Thus, it is better to start small with little or no cost and gradually build high-end data integration services at a pace and in the direction where the organization works best. Using the above-mentioned types of data integration, companies can work with greater efficiency and productivity. 

3. Benefits of Data Integration Services

Data Integration has a lot of benefits. Here are a few of the most important and impactful benefits of data integration.

  • Increase your Salesforce ROI

Companies facing issues like the inability to manage accounts with Microsoft Dynamics and customer relationships can use data integration to integrate two systems. It can help the company direct resources where it is required and facilitate growth. 

  • Easy and Fast Connections

Some time back, developing connections was nothing less than a daunting and time-consuming task. In this age of globalization, relying on data integration, it is easy and fast to internally integrate data sources.  

  • Error Elimination

Data Integration also helps in eliminating errors in data sets. It is particularly useful for Business Intelligence. Manual data integration can result in many errors, but automated data integration eliminates the chances of such mistakes resulting in accurate decision-making. Real-world data integration examples can understand the significance of data integration. In the retail space, performance is tracked based on having all employees’ data in one place. It empowers stores to measure labor hours, manage inventory, sales, and more across several outlets and channels. d

  • A Great Time-Saver

Another amazing advantage of data integration is that it helps the decision-maker have data at his fingertips before answering a business question. It is possible to even when data has to be sourced across multiple teams, apps, and systems. Thus, it helps save a lot of time. 

  • Leveraging Modern Technology

These days, modern applications are designed and developed to work with the cloud. It also includes applications used for business practices like data analytics. Today, with the cloud becoming vital for use with data warehousing, data analytics, master data management, and reporting, the significance of data integration has increased substantially. 

After understanding the importance of data integration, it is important to decide which data integration approach works best. As per statistics, most businesses use as many as 900 apps besides many other on-premise systems to store data. It means the company needs proper data integration systems in place to ensure adequate storage. There are many data integration approaches used in Business Intelligence. Some of the most common ones are data consolidation, data warehousing, data virtualization, and data federation to overcome data integration challenges. 

Data Consolidation- This approach helps to source data from numerous isolated systems. It combines data in a data repository and creates a unified version. It helps to reduce several detached data storage systems and convert it into an understandable format. 

Data Warehousing- It provides agile access to data in today’s highly competitive environment. Data warehousing arranges data in a way that helps in delivering fast, relevant, and fast data insights refining business performance. 

Data Virtualization- This approach enables the user to view data in a suitable place. It provides integrated, real-time data from diverse source systems. It helps improving business intelligence making it easier to manage. Here, the users access a virtual structure and find data in one place. 

Data Federation- It uses a virtual data store to construct a shared data model to combine data from multiple sources. Data can be accessed from a single point and enforces strict data models. 

As per the data integration definition, all these approaches serve a similar purpose. Businesses can help combine their data scattered among several teams, apps, and systems and bring them together as a unified whole using the best data integration tools or data integration software.

Conclusion

Using data integration, enterprises can bring a marked improvement in Business Intelligence. Choose the best tools and systems to get the best advantages of data integration. 

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