Data is increasingly becoming the digital currency of businesses. To stay competitive and optimize processes and applications, information must be collected, evaluated, and used. This is where Data Integration comes into play as a solution. It ensures that information is not scattered across different business units, but is centralized and always available.
Data integration is about combining diversified data from different sources into one clear picture. Data Integration facilitates the evaluation and use of corporate data to achieve business goals and optimize business processes.
Implementing Data Integration Will Ensure Data Integrity And Consistency
Integrating data sources with existing systems is part of the daily routine of almost every company. It plays a particularly important role in the digitization of business processes.
Businesses get a lot of valuable data from their websites, social media channels and email marketing campaigns. The goal is to get a 360-degree view of customers and learn as much as possible about them.
In Data Integration, Companies Aim To Provide The Following:
Business Intelligence (BI)
Business intelligence is the process of evaluating existing business data and making informed, market-oriented business decisions. BI is the final step in the data integration process where all existing data is standardized and systematically processed.
Master Data Utilization
Customer data arrives at a company through various channels such as sales, marketing and customer relationship management (CRM). Therefore, it is important that all data is created in a consistent way and is available to all business units. This ensures that everyone knows exactly which customers they are working with.
A data warehouse is a collection of data used by employees to visualize, evaluate, and use company data. For this purpose, data is stored centrally and created in a consistent manner. A data warehouse ensures that all business units have access to one system and one repository of information.
Different Ways To Create Data
There are several ways to retrieve data from a data warehouse:
Uniform Access Integration
Used to visually standardize data records. The information remains in its original location but is displayed in a uniform way on the front panel.
Manual Data Integration
Data is manually collected by staff and transferred to the data warehouse. This process is time consuming and only suitable for small businesses with small data sets.
ETL (Extract, Transform and Load)
ETL (extraction, transformation, loading) is a sub-process of data integration. In this process, data available in a source system is extracted and transformed so that it can be loaded into a data warehouse.
Middleware-Based Data Integration
This form of data integration is best suited to the use of legacy databases and systems. It acts as a middleware adapter that enables the use of this data in modern applications.
Unlike uniform access integration, in this approach data does not remain at the data source but is copied to a single data warehouse.
The Goals Of Data Integration Are:
Digitization of sales means that companies have more data. Data comes from a variety of sources, including customer surveys, questionnaires and sales data, each with different characteristics. Some of this data includes traditional business data:
- Product Data
- Market Data
- Customer Data
- Sales Data
- Safety Data
- Environmental Data
Because this data is used in different ways by companies, it is typically stored in different places. Over time, so-called data silos are created, where a company’s data resides in different places but is not linked together. This makes it difficult to evaluate and use the data for business purposes.
This is where data integration comes in, combining business data from different sources into a single entity. The result is a high level of data integrity and consistency, meaning that the data is accurate or reliable.
Here Are Some Of The Benefits Businesses Can Gain From Data Integration
Data Integration brings many benefits to enterprises:
- Data is centralized and standardized, so there is no separate data.
- Data integration can save your company a significant amount of time and resources.
- Using complete and accurate data reduces the likelihood of errors and poor decisions.
- Data integration ensures reliable, understandable and meaningful information and business decisions.
- Workflow can be improved by ensuring that all departments are using the same data sets.
- Your business achieves a high level of data completeness or consistency, and the information available is accurate and complete.
Here Are Some Of The Challenges That Companies Face In Managing Their Data
Companies face many challenges when consolidating data. First and foremost, they need to understand how to leverage existing data sets and integrate existing systems. They also need to evaluate information from different data sources, such as cloud, video, and sensors, which require different approaches. Real-time data analysis is becoming increasingly necessary.
In addition, there is a need to differentiate between internal and external sources as each data set has different characteristics and presentation formats. Data integration systems need to constantly improve and adapt to market changes.
Data Integration Is An Ongoing Process
Data integration doesn’t stop there. New data and new systems are constantly appearing in the market. Therefore, the concept of data integration must be improved to ensure that data sets are continuously collected, analyzed, and used.
We also need to encourage employees to integrate data effectively to avoid data silos and to ensure consistency and integrity.