The more businesses use data to underpin every decision and strategy, the need to process, store, manage and share it among employees in the right way becomes more critical. And it’s not only about having the data stored for anyone to look at it, the data needs to be accurate, high-quality, up-to-date and ready to be analyzed and interpreted.
To achieve this, companies need to have a data integration strategy and management in place, as data integration combines and merges data from several sources to give the user a combined and unified view of it.
But to build a robust data integration strategy, the company must understand the type of data they have access to, which integration cases they must address and what will be the best tool and solution to integrate their data across their platforms.
And to start building a good data integration strategy, it’s important to consider the core tenets of it, to ensure that the company will implement a successful process that will cover all their needs.
The Core Tenets of a Data Integration Strategy
Data integration is not only a process of extracting pieces of data to show to the final user, it’s also about transforming the data before the company can load it to its destination – a process known as ETL (extract, transform, load).
ETL is a proven method used to combine the extracted data to the information and format the business already uses every day, so they can see the consolidated data in their preferred format.
To achieve the status of a data-driven organization, how the data integration strategy is built will be determinant to the company’s ability to make fast decisions and gain market insights ahead of its competitors.
1. Ability to Change the Data Scale
Data is always growing and by looking at the amount of information produced by the past years, it is clear that the next ones will also face a huge growth in data production. So the company needs to be prepared for a significant increase in their workload.
Scalability needs to be part of the data integration strategy so the teams working with data can be able to handle the inevitable increase in data loads.
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This growth can vary depending on the company, the market and the tools available, so preparing for it will also be different, but the best way to be ready is by considering the scalability of the data in 1, 5 and 10 years.
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2. Anytime and Anywhere Access
2020 showed companies that the possibility of adopting remote working conditions went far beyond giving their employees a computer and a chair. It’s also necessary to create accessible data integration platforms and resources.
The difficulty to access the routines of data integration remotely should not be a problem with the right infrastructure and security measures in newshunttimes place. So the company must consider in the strategy the need to upgrade tools, software, and hardware and check all the conditions to make anytime and anywhere access possible.
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3. Type of Data and User Access
Understanding the types of data being used by the company are important to build the strategy on the data that needs to be integrated currently and have a plan for the data that may be needed in the future. Mapping the type of data will avoid excessive costs and solutions that won’t support future data.
The fastest way to address this is by conducting a simple data audit to see who needs access to the data. Only a few portions of users require access to all the data, so having this control will help with the strategy and the security.
4. Adaptable Processes
Adaptable and agile processes should also be a top priority to the data integration strategy. A future-ready approach is what makes companies successful when adopting new technologies, data sources and formats from the market.
Being flexible is what avoids excessive spending on new resources in order to accommodate new technology. The data integration strategy should allow the company to bring new solutions faster than their competitors without major disruptions to their processes and workload.
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5. Understand the Business Value
No strategy will work without the company understanding which value it will bring to them. Mapping how data integration will benefit the data management – in the short and long term – and having clear metrics for each goal the solution can achieve.
From better efficiency and productivity to better decision-making, visibility and even bottom-line impacts should all come from data integration.