It is imperative to choose the right data integration strategy for your company. The right strategy allows you to obtain the best value from your data, shortens the time to act, lets you see positive results in your bottom line, and enables you to outperform your competition. With a good data strategy, you can keep your finger on every aspect of your business, including the services you provide to your customers. However, choosing a data strategy that is not aligned with your objective or making mistakes in implementing your strategy can be costly and ineffective.
Data integration defined
Data integration combines data from various sources into a unified system or view. The process involves practices, tools, and techniques to normalize the data to access and deliver data across different areas and structure types. Integration steps include cleansing, extraction transform and load (ETL) mapping, and, ultimately, transformation.
1. Not having a comprehensive plan – The entire strategy requires mapping to avoid having to redo any previously spent effort. It is better to spend time in the beginning and have a comprehensive plan than to waste time discovering roadblocks down the line. A thorough plan should include the following.
a. A hands-on business owner overseeing every project aspect, including assembling the most effective team
b. Proof of concept
d. A process for handling bad data
e. Testing at various milestones of the project, not just at the end
2. Choosing the incorrect architecture for the solution – It is essential to know if you need a project-specific or more generalized generic architecture. The project-specific architecture is easier to develop, but a generic architecture is more flexible.
3. Not knowing the end-user – Understand your internal client and help them find the best insights available within your data.
4. Not considering the future – Given the dynamic nature of data, you will need to consider how you need to scale over time as the structures, formats, and data collection may change.
5. Not realizing that an integration project is an ongoing effort – As your data grows, your project and your strategy will need to evolve with it, which can mean that there is not necessarily an endpoint to a data integration project.
Although one may make mistakes over the course of your integration project, do not underestimate the value derived. In the end, you will have more accurate, centralized, and reliable data, which will allow you to outperform your competition and increase your profits.
The added value of data integration
Efficiency – Data is collected and stored in disparate systems interacting with one another. The data only needs to be collected and stored once rather than loaded and maintained in multiple systems, allowing minimal human intervention.
Consistency – Frequently, inconsistencies occur when storing data in different systems. For example, data collected from one source may be formatted differently than from another source, such as names, addresses, currencies, etc.
Accuracy – Automated data collection, storage, and retrieval not only improves data consistency but also minimizes the risk of human error in the process.
More meaningful analytics – To realize powerful data analytics insights, all data must be available for analysis. Missing data and inconsistent data points hinder successful analytics, and, in most cases, the more data, the better.
Having the correct data when you need it – A centralized data system means that available information is at your fingertips in real-time without having to search for the relevant data points. Also, ensuring that you have consistent, accurate, and reliable data allows you to easily transfer the data between businesses, including your vendors and customers.
Choosing the right data integration strategy and having it carefully planned and aligned to you and your customer goals before implementation will shorten your time to act. It makes the best use of your data and adds immense value to your overall business strategy and bottom line, ultimately giving you an essential competitive advantage.
If you are interested in learning more about successful integration strategies, email us at firstname.lastname@example.org.. Intellect Data, Inc. is a software solutions company incorporating data science and artificial intelligence into modern digital products with develops and implements software, software components, and software as a service (SaaS) for enterprise, desktop, web, mobile, cloud, IoT, wearables, and AR/VR environments. Locate us on the web at www.intellect2.ai.