Businesses in modern times are starting to adapt to various types of technology to get more benefits in deciding strategies to advance their business. Data integration technology has become increasingly popular in recent years. In this article, we will try to discuss Data Integration further.
What is Data Integration?
Data integration orData Integration is a process of combining data from various sources into one. The process of integration and combination of this data starts from a data collection process to cleansing, and ETL mapping, as well as data transformation. The purpose of data integration is to produce an effective business intelligence process resulting from the analysis process.
Data integration usually involves several elements such as data sources, data storage servers, and clients that access data from data storage servers. In the process, data integration starts from a user request (client) to the data storage server. The information is then compiled in a data set for further examination after being extracted from its original source.
What are the Benefits of Data Integration?
The next logical inquiry is, “Why do businesses need data integration?” What advantages do we stand to gain? We will elaborate on some of its possible uses in order to address this inquiry.
Data from a wide variety of sources is constantly being produced by every company and business. Data from various marketing tools, such as customer relationship management, website analytics, and others, must be integrated. Data from all of these sources needs to be combined so that it can be analyzed using data analytics software, which will then yield insights that can be used to inform business strategy.
All of these operations function more quickly, effectively, and smoothly when data is integrated. One of the advantages of data integration is illustrated here. Other advantages include the ones listed below.
1. Improving the System for Collaborating Between Divisions
Every company has different functions, divisions, and tasks. With an integrated system, data will become easier to access for certain projects. Besides being accessible to anyone in a company with data integration, we can also secure data using several data network security techniques that are usually available in these tools.
Data can be improved across an organization in accordance with the specific requirements of each department. Here is where the company reaps the rewards of improved data processing efficiency.
2. Reducing Data Errors
Redundancy in data processing makes the analysis results not optimal. With manual data collection, we often experience data duplication which cannot be avoided, especially if data collection is done from various sources. Not to mention the data analysis process itself will be more precise if the data collection is really complete. One of the benefits of data integration is ensuring that the data collected is completely complete and accurate without duplication of data.
Data Integration solutions are able to synchronize data from various sources so that data storage can be done automatically from anywhere and at any time. Data changes can be saved in real time, and data can be viewed in real time too.
3. Generate More Valuable Data
Data integration strives for quality data that is more valuable to businesses so that it can be used to make strategic business decisions. Standard practice for data integration platforms and solutions is to employ a wide range of data processing techniques to prevent deterioration in data quality and enhance accuracy during the integration process.
Application of Data Integration in Business
The data integration solution is a versatile solution in meeting business needs according to needs. Some examples of using data integration tools are as follows:
1. Utilization of Big Data
Keeping huge data sets creates extremely complex issues. Websites with millions of users, such as Facebook and Google, constantly analyze user data. “Big data” means a huge database. Due to the ever-increasing availability of data, data integration is becoming increasingly crucial to the efficient operation of any modern business. The integration of data is obviously crucial for utilizing Big Data, or large amounts of data.
2. Creation of Data Lake and Data Warehouse
The application of Data Integration, especially for large companies and enterprise businesses, one of which is used to create a data warehouse or data lake solutions, which also combines data sources into a relational database.In order to conduct analysis more rapidly and accurately, data queries can be applied to the data stored in the data warehouse. Some examples of companies utilizing data integration for data warehouses are Microsoft Azure and AWS.
3. Simplify Business Intelligence (BI)
Data integration is a platform that is able to provide an integrated view of data from various sources so as to simplify the analysis process for Business Intelligence. Companies and businesses can quickly understand, view available data sets to immediately take action according to current business conditions.
ETL and Data Integration
ETL or Extract, Transform, Load is a part of the data integration process where data is taken from data sources and sent to a data warehouse or data store. This procedure is automated, running in the background to reliably generate data for use in business intelligence and analysis at all times.
Challenges For Data Integration
The data integration process that takes data from several data sources and transforms it into structured data certainly has quite high technical challenges. Even though the data integration technique has a high level of effectiveness, there are some obstacles and challenges that must be faced.
Some examples of common challenges below are often faced by data integration tools and solutions:
- How to Get Quality Data: Data is essential to any business. When putting into practice data integration for business, users must have a clear idea of what information needs to be gathered and analyzed. They need to understand the source of the data and the frequency with which it must be updated.
- Retrieving data from the old system: efforts to carry out data integration, of course, include transferring data from the old system to the new system. Here we often lose certain data ranges so it is very difficult to get data from the old system to switch to the new system.
- Retrieving data from a new device: It’s inevitable that as new technologies emerge, so too will the variety and complexity of the data they collect. Information collected by Internet of Things gadgets, sensors, etc. is not always in a usable format. Data integration is difficult because it requires sifting through numerous data sources and potentially re-entering some of the data.
- External Data: Data retrieved from external sources may not be of the same type as internal data owned by a company. This will be a challenge in itself.
Data Integration Process in Business
Many organizations use the same procedures and approaches to data integration. Some illustrations:
- manual data integration processes is a process of collecting data from various data sources manually. This process is very inefficient because we ourselves do the cleaning and combining data to be stored in a data warehouse.
- Middleware data integration is a technique using a middleware application that functions as an auxiliary means for normalizing data.
- Application-based Integration is an integration process where the software performs the process of searching, retrieving, and integrating data automatically according to our needs.
- Uniform access Integration refers to a subset of data integration that focuses on making data appear uniform across different data sources.
- Common Storage Integration is a technique frequently employed during the archival process. Information gathered at the source is kept in a centralized database and presented in a unified format.
Data Integration Implementation for Your Business
After becoming well-versed in data integration, you’ll want to apply what you’ve learned for the benefit of your company. Data Integration makes it simple to implement unified data integration. A thorough business plan can be informed by data gathered from across your organization.