Largely unstructured and scattered, vast amounts of data are causing increasing problems for companies. Shouldering the burden of such immense data coming in through multiple channels is a problem that needs immediate attention. By 2025, according to the prediction made by International Data Corporation (IDC), global data growth has the potential to reach 163 zettabytes. Thus, the importance and vital presence of data cannot be overstated. Data silos are one of the most common issues that companies with a lack of a centralized approach toward data are facing. Efficient usage of data is achieved through data integration, which essentially collects an organization’s data from multiple sources and integrates it into a unified source.
Data integration ensures that a consolidated and real-time view of the data is available for users to be able to make informed and intelligent business decisions. Understanding and implementing data integration into its core business operations is crucial to any business’s success.
What is data integration?
Data integration is the process of compiling and merging data from various systems into one place to make it ready for processing and generating insights. The integration process begins with the ingestion of data, followed by cleansing, mapping and use of the ETL approach that extracts, transforms and loads data from varied sources into a target system. Through this unified view of an organization’s data, the business applications responsible for analytics can easily access and make sense of the data, no matter the source formatting. The information thus produced after the integration process is completed is exhaustive and stored in a data warehouse.
It is an essential part of the strategic function of any organization which is making use of advanced analytics or wants to create a multi-dimensional view of its customers.
Importance of data integration
Vast amounts of data from many different sources are being collected by businesses for the sole purpose of using it for analysis and thus, more effective decision-making. Also, new data pours in every second so it must be available to users at all times. Data integration makes sure that the current data as well as historic data from legacy stores is available to be utilized and exploited at will. It also ensures that communication between systems is prompt and systemized. Therefore, it is essential that business organizations make data integration a priority to stay relevant in the marketplace.
- Decision-making capabilities improved – Through the application of data integration, the business intelligence tools used by an organization can have easy access to real-time information, presented in a simpler format. This facilitates analytics to garner insights for better decision-making.
- Reduction in errors – Considering that organizations must spend a considerable amount of time and resources on sourcing and correcting errors in datasets, data integration becomes a valuable tool. Access to data coming from different departments or divisions within departments, data integration allows faster identification of errors since the data is pooled in a single location.
- Increase employee efficiency – Companies can save millions of dollars in lost productivity each year by centralizing all their data for employees to have easier access to the company’s most important data. Productivity is reduced in the process of gathering the required data from multiple sources. Thus, data integration will lead to higher efficiency.
- More valuable data – Over time, data integration efforts improve a company’s quality of data. Through the integration of data into a centralized system, errors are identified much quicker. This helps in rectifying quality issues, resulting in better quality decision-making and higher accuracy of data.
- Anticipate future demands – Forecasting of consumer demands becomes easier when businesses have access to historic as well as current data. Data integration tools allow the elevation of the quality of products and help businesses stay competitive in the long run.
Use Cases of Data Integration
There is a wide range of industries where data integration is an integral part of their data management strategy.
- Supply Chain Management – Since there are multiple stakeholders involved, many systems and applications from various stages of the supply chain need to be integrated to make the data sensible. Data integration is crucial for the appropriate management of the supply chain and minimizes the operational costs involved.
- 360-degree view of customers – In order to better understand customer behavior, having a 360-degree view at hand is essential for the marketing department. Collating data of consumers from e-commerce systems, marketing, customer support channels and other applications helps to anticipate demands and increase customer satisfaction.
- Data Quality Management – With data integration, the quality of data can be monitored and assessed for any errors or discrepancies. The reliability of the data increases when the data integration practice includes data cleansing, profiling and validation.
Taking advantage of data integration systems to manage vast organizational data will have a positive impact on the overall performance and efficiency of operations and analytics. Easier and instant access to important data, which is consolidated in one location, would allow employees to respond more promptly to customers and rectify any inconsistency effectively. Companies planning to stay ahead invest in data integration solutions that seamlessly integrate data from any source.