Benefits of Data Integration You Need To Know

Benefits of Data Integration You Need To Know

Data Integration Benefits You Need to Know

What is Data Integration?

Thanks to Data integration, your company can use data collected from different systems in a unified way. So the unified data transforms into a more valuable asset for your business. Among all the data integration benefits, one of the main ones is helping people inside the company work better and do more for your customers. But when a company doesn’t use data integration benefits, people in the company don’t have the means of obtaining the data from the business’s different unintegrated systems. 

Data integration helps make data collected from different systems become a valuable asset for your business

Clients may receive emails from different areas of the company requesting information that the clients have already delivered. But other areas of the company cannot access the same information because the information systems aren’t integrated. Sometimes unintegrated systems lead to data being shared manually via spreadsheets or emails, which increases the probability of mistakes in the future.

Another of the leading data integration benefits is helping to avoid this kind of problem in modern companies. In this way, information can be shared between ERP or CRM systems and vice-versa. This way, everyone in your company has the needed data to work properly.  Mistakes are eliminated, and the whole business gets the benefit out of the available systems. 

1. Data Lifecycle Management (DML) Best Practices
2. Data management: benefits and keypoints
3. What are OLAP (online analytical processing) tools?

A Short Story of Data Integration

In the past, communicating information within a company, such as purchase orders and invoices, was made traditionally on paper. There were isolated systems in a single company that can produce some batch processing that could send data from one to another through an electromagnetic device or just paper. 

Although Electronic data interchange (EDI) was created in the early 70s, the use within and between companies was not very spread.Technical standards like EDI appeared to facilitate businesses communicating information electronically. EDI replaced paper and used electronic means to share information within companies.

Word of 1990: Data integration benefits

In the middle of the 1990s, the National Institute of Standards and Technology defined Electronic data interchange as the computer-to-computer interchange of strictly formatted messages representing documents. In those years, the different systems inside a company weren’t integrated.

So the 1990s were about breaking down internal walls. Companies were confronting the challenge of integrating and redesigning enterprise processes using ERP (Enterprise Resource Planning) systems. But at that time, enterprises transacted with each other via mail, phone, and fax. These interfaces were cumbersome, slow, labor-intensive, costly, and prone to generating mistakes that caused delay, error, overhead costs, and limited communication. 

With the advent of the internet, more and more organizations were connected. Finally, most or all EDI communications were moved to the Internet. The connection was the solution and the internet-enabled high-quality fast connections with the right amount of data.

World of 2000: Data Integration Benefits

The 2000s were about breaking down external walls by integrating and redesigning inter-enterprise processes using the Internet. A fast, cheap, and ubiquitous communication system. A tool for changing how companies worked together. A catalyst for reengineering inter-enterprise processes. Virtual integration enabled multiple enterprises to work as though they were one through processes that ignored enterprise boundaries.

Different Problems of Unintegrated Data

Independent databases

Enterprises that work together nonetheless use separate databases for operations and decision-making. These databases are separately maintained and therefore inconsistent, and they each reflect only part of the overall situation. 

The consequences of this kind of practice are:

  • Sub-optimization
  • Slow cycle times
  • Reconciliation costs. 
Different problems of unintegrated Data: Database Coordination resolves the problem of separate databases where echa one reflects only part of the overall situation

The solution to this problem is Database Coordination. Here we find another principal data integration benefits when different departments within a company can work collaboratively with shared data.

Innumerable interfaces

Enterprises have many individual and independent interfaces with other enterprises. These transactions are of small scale individually, and collectively they represent a complex system. The consequences are confusion, redundancy costs, and missed leverage opportunities.

The solution for these problems seems to be the combination of multiple interfaces and multiple transactions into one. These practices benefit from reducing transactional overhead, generating consistent interfaces, and economies of virtual scale. These are other kinds of data integration benefits too.

Fragmented Processes

Enterprises are managed as self-contained entities, performing processes that fit entirely within their boundaries. These processes are, in fact, merely fragments of more extensive inter-enterprise methods. The consequences are redundancy, sub-optimization, and unnecessary overhead. The solution for these problems is compression. So, by treating an inter-enterprise process as a single unit, it is best done. 

This practice has different benefits as:

  • Overhead costs are reduced.
  • Improvement of tasks and process performance.
  • Elimination of redundant activities.
  • Strategic focus.

Companies can  improve their performance by:                                    

  1. Streamlining interfaces (connecting)
  2. Sharing information (coordinating)
  3. Aggregating interfaces (combining)
  4. Integrating processes (compressing).

The benefits of these practices can be the elimination of non-value-adding overhead created by enterprise walls and the improvement of their performance by leveraging other enterprises. Putting a Web site in front of lousy processes merely advertises how lousy they are is not the right business solution. Companies need to integrate benefits internally to integrate externally. This way, they are experiencing data integration benefits.

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Data Integration Architecture

According to Philip Russom’s article today, many data integration specialists still build one independent interface at a time, which is inherently anti-architectural. And a common misconception is that using a vendor product for data integration automatically assures architecture.

Data Integration Architecture: experience all the benefits of data integration

But if you don’t fully embrace data integration architecture, you can’t experience data integration benefits. You will not get to know how architecture affects data integration’s scalability and ability to support real-time, master data management, and interoperability with related integration and quality tools. 

Complexity is the main reason why data integration needs architecture. Data integration affects data flow from diverse source systems like operational applications for ERP, CRM, and supply chain, where most enterprise data originates. Through multiple transformations of the data to get it ready for loading into diverse target systems like data warehouses, customer data hubs, and product catalogs. 

Since these are various types of applications, database brands, file types, and so on, all these have different data models, so the data must be transformed in the middle of the process. Then there are the interfaces that connect these equally diverse pieces. And the data doesn’t flow uninterrupted, or in a straight line, so you need data staging areas. Simply put, that’s a ton of complex and diverse stuff that you have to organize into a data integration solution to profit from data integration benefits. 

That is why nearshoring a data integration partner will ease the process. Not all vendors are qualified; we suggest this article to find yours.

Goals of Data Integration Architecture:

Data integration architecture imposes order on the chaos of complexity. It makes companies serve from data integration benefits by achieving specific goals:

1) Architectural patterns as development standards: Most components of a data integration solution fall into three broad categories: servers, interfaces, and data transformations. With that in mind, we can think that Data integration architecture is simply the pattern made when servers relate through interfaces. An architectural pattern is to provide a holistic view of both infrastructure and the implementations built on it. 

2) Simplicity for reuse and consistency: When development standards and architectural patterns are applied to multiple data integration projects, the result is simplicity, which promotes the reuse of data integration development artifacts and increases consistency in handling data.

3) Harmony between common infrastructure and individual solutions: For a solution to be organized in preferred architecture, the infrastructure must enable that architecture. Mostly the data integration production server and the interfaces it supports. 

The most common architectural pattern for data integration is Hub-And-Spoke architecture. In this architecture, inter-server communication and data transfer pass through a central hub, where an integration server manages communications and performs data transformations. 

What is the GDPR? 

The General Data Protection Regulation (GDPR) is the most robust privacy and security law in the world that was put into effect on May 25, 2018. This Europe’s data privacy and security law include a significant number of requirements for organizations around the world. 

It imposes obligations onto organizations anywhere, so long as they target or collect data related to the EU people. The GDPR has the power to impose harsh fines against those who violate its privacy and security standards, with penalties reaching into the tens of millions of euros.

Thanks to the GDPR, Europe signifies its firm stance on data privacy and security when more people are entrusting their data with cloud services, and breaches are a daily occurrence. The regulation itself is extensive, far-reaching, and relatively light on specifics, making GDPR compliance a daunting prospect, particularly for small and medium-sized enterprises (SMEs).

It’s worth mentioning GDPR in this context because when you harness the power of data, integrate all your internal databases, and enrich your systems with aggregated and external data, you have to look at the regulations and be compliant.

What is DataOps?

In this article, Andy Palmer tells us that large companies are experiencing a foundational shift in how they view and structure their data. 

Nowadays, organizations capture more data than ever before and store it in an ever-increasing variety of data stores. The accumulation of data over time makes companies struggle to manage that tremendous volume of data. 

For decades, companies’ data environments have been deeply fragmented and virtually impossible to integrate at scale. Indeed, even basic questions about the business, like “Who are my customers?” can’t be answered consistently. This reality is making companies accept that they need to start managing their data as an asset, and It’s time to rethink priorities and start putting the “data horse in front of the analytics cart.”

Data Operations (DataOps) is a methodology for companies where people process data from different business data sources quickly, regularly, and reliable. The concept is that the best way to increase the velocity of new features being delivered in software is by using a continuous build, test, and release process with a strong emphasis on QA automation. 

Companies expecting to compete based on analytics need to empower analysts with easy access to updated unified data logically organized. By implementing a data curation process that is integrated, repeatable, and scalable, it will be possible for a business to serve from data integration benefits, achieving the analytic velocity necessary to create a competitive advantage.

Data Integration Benefits 

According to this article from, Cloud-based integration platforms have started to become quite popular lately. Below you can read about seven main Data Integration Benefits that companies can see once they have switched to cloud-based integration platforms: 

Cloud-based Integration platforms and Data Integration Benefits

1) Easy and fast connections: Developing connections have been a painful task that took a long time, even months sometimes. Point-to-point hand-coded integrations are time-consuming and risky. When you need to integrate data sources internally, you want to ensure that it happens as quickly as possible. Doing data integrations in the cloud seems to be the best new way. It is easy and fast because of the pre-built adapters and connectors that can be easily replicated.

2) Integrate data from multiple sources: When your company uses tons of applications, systems, and data warehouses. Better collaboration must connect all the different data sources to utilize the value of insights. Once all the information is available in a single place in real-time for all the right stakeholders, your company will be able to use the information for improving processes and providing better services.

3) Availability of the data: As Data Silos are not sustainable, companies need to have the data available for all the right stakeholders in one place and in real-time. So, it’s essential to connect all the data sources to obtain all the necessary information in a single place.

4) More insights bring improvements: Once your company has all the data available in one place, you will be able to better utilize the available information. When you can use the data, you will have better intelligence on your operations and customers. You will be able to make better decisions based on the available information and improve your processes.

5) Better collaboration: When your company needs to improve the cooperation internally or with your trading partners, you will do so thanks to the Data Integration Benefits. By automating the flow of information will have a positive impact on how you do business. Your teams and stakeholders will achieve better collaboration because they have more information at their disposal.

6) Data integrity and data quality: Data integrity is an essential element of data integrations. Data integrity is the assurance of the consistency and quality of the data through its entire lifecycle. Using a data integration platform can give your business the ability to define validation rules. You can design processes that check the information and forward the damaged information back to the sender for correction.

7) Increase competitiveness: Having a data integration strategy for your company can help you plan what actions you need to take to improve data accessibility both externally and internally. This way, your company will be able to impact a lot of vital parts of your business. 

Finally, we can say that thanks to these seven Data Integration Benefits, people inside your company will be able to:

  • Work better among them and do more for your customers.
  • Use data collected in a unified way as a valuable asset for your business. 
  • Offer better services to your customers than your competitors.