Why Data Integration Is Fundamental
Data integration is fundamental when companies use more than one system. Data integration is the process of transferring data located in various data sources to other data targets. Data integration and collaboration between data systems and processes is vital because it allows processes to work faster and be more reliable and robust.
Data integration is fundamental when companies use more than one system. Data integration is the process of transferring data located in various data sources to other data targets. Data integration and collaboration between data systems and processes is vital because it allows processes to work faster and be more reliable and robust. The alternative is manual re-keying of large amounts of data which is practically impossible at this phase of our economy. By integrating systems like Enterprise Resource Planning (ERP), Material Requirements Planning (MRP), Supply Chain Management (SCM), Quality Management System (QMS), and the like, a company can reduce a lot of unnecessary errors.
Data integration can make companies competitive. Consider a company using Salesforce.com for CRM, MS Dynamics Great Plains for accounting, PayPal for receiving payments. The company sales team feeds the data into the CRM solution as sales information. The data then has to be converted into Invoices in MS Dynamics GP upon sales completion. The generated invoices will be paid for by the customers using PayPal. The payments from PayPal then have to come back into the MS Dynamics GP accounting system. In this scenario, three different systems are involved in the process and people may manually create the customer information, invoices, payments and other information in the systems. This can limit the growth of the firm compared to competitors. Full data integration is possible and can give a competitive advantage to a firm that is fully integrated.
Needed in Projects
Data conversion and integration is a significant requirement when a company is moving to a new system. The project would need existing and historical data to be pushed in to the new system. A typical example would be, companies using QuickBooks Desktop for accounting who want to migrate to any other accounting systems such as Netsuite, Xero, or other systems. In this case, the existing accounting and historical data should be moved to the new accounting system as a pre-condition to going live. Getting this wrong would add a lot of risk to the project itself. A good data integration tool can help the systems integrator reduce the risk of this aspect of the project dramatically.
A solid data integration tool can keep the data in sync accurately.
Not Doing Data Integration is Risky
Data integration is a risk often overlooked by companies when they initiate a new project. Their focus will be on the new system’s feature functionality and they would pay less importance to the initial data conversion or the subsequent continuous data integration process.
Some of the risks can include:
- Missing historical data
- Poor quality of source system data
- Undocumented adjustments and changes to data
- Poor definition of requirements related to data
- Not sizing the data conversion and data integration part of the project
- Lack of clarity of responsibility for data integration and data conversion
- Effort and budget runs over estimates
Software projects fail frequently and more than 31% of projects get cancelled outright. A large number of projects go over budget. Many of the reasons for failure get directly assigned to the Systems Integrator. As is, obvious data integration can underlie many of the failure reasons.
In order to avoid these risks, a good data integration solution is necessary. Select an affordable yet powerful data integration solution such as www.www.qxchange.com.