Why Data Standardization Remains Important in 2019

Businesses have begun to invest more strategic and financial resources in data standardization and for very good reasons. As organizations invest in newer software and enterprise tools, standardizing datasets into recognizable formats on multiple platforms is inevitable.

With the first half of 2019 almost coming to a close, data standardization is evermore relevant and important. As more businesses begin to implement newer software programs and continue to discard older tools, databases need to be cleansed and standardized.

In the coming few months, we expect to see more businesses feel the pinch of not standardizing their data.

Let us take a look at why standardizing data continues to remain a crucial aspect of business strategy.

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‍1. Data literacy is a huge issue

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‍While advanced technologies are already in place in most organizations, staff and employees are often not trained in their usage.

In fact, Gartner predicted that close to 80% of businesses will start implementing data literacy programs by 2020.

This results in staff making multiple entries and duplicating datasets. Worse, they may continue to use legacy tools and store data in non-compliant formats. This is one of the reasons why data standardization is not only a tactical process but an opportunity for your staff to learn how to store and manage your data.

Data standardization is a valuable opportunity for your staff to learn new skills related to data formats and standardization.

Training staff to enter data correctly and making sure that their past data mistakes are cleaned is the perfect step towards data success.

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‍2. Artificial Intelligence errors will continue to mount

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‍Many businesses have begun to implement artificial intelligence in varying degrees. Some have begun to use chatbots while others have begun to toy with natural language processing.

Many more are considering experimenting with textual analysis and emotion recognition. AI tools are not always perfect and their errors will continue to mount. From AI World Cup 2018 predictions gone wrong to Google Photo confusing a skier with a mountain, the Internet is rife with AI-related errors.

In such a scenario, data needs to be as error-free as possible for your AI tool to perform well. Standardization of your data has both direct and indirect benefits for your AI tool's performance.

While artificial intelligence continues to help businesses grow, it is also important for you to eliminate situations which might force AI to make errors.

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‍3. Regulatory compliance requires more thorough data management

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‍Studies show storing data in incompatible formats results in data corruption, security threats and data theft as well. With GDPR, HIPAA and other regulatory compliance bodies requesting stringent data management practices, it is imperative for you to store data in recognizable and verifiable formats.

Compliance requires you to store data in secure formats on even more secure platforms. You can start standardizing your database and make it secure and easy to manage, which will help you to comply with regulatory bodies.

Businesses that maintain data accurately and in the right platforms were shown to comply with regulations more effectively.

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‍4. Newer enterprise programs continue to be implemented

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‍All indicators point towards more businesses opting for implementation of automation tools such as ERP and HRMS. These tools often need to be integrated with each other in order to avoid duplicate entries and synchronization of data.

Data standardization enables you to store all your databases on multiple enterprise tools in formats that are easily recognizable to software programs. This helps you to avoid error messages, missing libraries and incorrect business insight.

Businesses cannot predict which new enterprise software will be implemented. Keeping data in recognizable formats will help protect yourself from future trouble.

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‍5. Business insight depends on data recognition

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‍Business insight depends on how accurate your databases are. In addition, it also depends on whether the said database can actually be recognized by your analytics tool. In order to ensure that you are able to derive insights from your analytics tool, you need to ensure that all your databases can be recognized by it instantly.

Data is stored on multiple software programs and they all need to be stored in mutually compatible formats. Data standardization helps you to ensure that all your databases can be immediately processed by analytics tools, so that your business insight is accurate and useful.

When analytics tools are able to discern different formats in which you have stored data, they will be able to provide analysis that will have a positive effect on our business.

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‍Data standardization will remain relevant for a long time

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‍As you can see, the importance of data standardization's not going to diminish anytime soon. On the contrary, businesses will need to invest more in data standardization to manage their databases efficiently.

Taking a good look at how data is being store maintained is just the beginning. Seeking a professional database audit is another crucial step.

Here are the top reasons why data standardization will continue to remain important in 2019 and beyond:
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• Provides an opportunity for your staff to learn to save data in the correct formats.

• Avoid AI errors that have already begun to mount.

• Comply with data regulations and enhance the transparency of databases.

• Make existing data compatible with newer software programs you might implement.

• Derive richer and more accurate business insight.