摘要: Data have been an essential part of business for so many years. Manufacturers, retailers, and marketers depend on data to develop products and design strategies used in daily business operations. Handling simple data could be easy for businesses as they can be stored, analyzed, and presented using spreadsheets or text processors.However, the rise of big data has brought about the need for better data management amongst businesses.


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▲圖片標題(來源:BDAN)

The field focuses on extracting and analyzing data that would otherwise be difficult to handle using conventional data handling tools. Because big data is a new concept to many businesses, managing isn’t as simple as any data set. Moreover, the technology of handling the data is quite expensive for most startups. This has led to many businesses outsourcing big data management to managed IT solutions.

Managing Big Data

Big data may be a new concept for many businesses, and, therefore, they might find a problem trying to manage it. However, with the proper guide, a business that uses big data to make decisions on its daily activities can still be successful.

These are some of the important tips for managing big data for businesses:

1. Collect More Data

Due to the challenge and the novelty of big data, some people may argue that collecting more data could be a problem to handle. However, big data doesn’t necessarily mean it has to be handled by human beings. In fact, big data is essential in machine learning, a component of artificial intelligence, meaning the whole process of big data management can be handled by AI programs.

Therefore, businesses should seek to collect more data even if it isn’t currently used; it’ll be significant for future references. With more data, businesses can design better ML models that are important in decision-making. It gives the company a broader reference point rather than just one point.

2. Structure The Data To Fit Different Applications

Analysis conducted on a single project through big data won’t cover all other projects regardless of how diverse your data is. Therefore, when you collect the data, you need to structure and store it to be used at any point, such as to analyze different projects or develop new algorithms. Just like the diversity of the data, the applications are also diverse, and your team will learn about more applications and uses of the data as they grow.

When storing the data, you can structure them in a format accessible for the team to use whenever required. You can also store them in their raw format as long as they’re secure and untampered with, so that they’ll be organized when being used for a project.

3. Use Cloud Storage And Backup

With many companies providing software as a service, it has become easier to store, retrieve, and manage big data. Cloud services provide a less costly option in data management. You don’t have to worry about shopping for the right on-premise storage devices and updating them frequently with the latest technology. Moreover, you don’t have to get experienced staff to work in your office to manage the data.

With a reliable SaaS company, your data will be secure and managed by more experienced professionals in data management. With features such as backup, you won’t have to worry about losing your data forever as you can always retrieve them.

4. Ensure Data Security

Data security is one component that can’t be compromised in data management. Client information need to be protected, and there are regulations governing data security, and businesses have to comply with them. Moreover, protecting your data means that you protect your company against financial losses. Data experts are also more willing to use your data to develop different models if they know you comply with data governance regulations.

Using software as a service and conducting security assessments are ways that you can use to boost data security. You can also train your staff or use AI automation to eliminate risk points in your IT system.

5. Improve On Data Integration

Data integration is important, especially if the data is stored in different programs or places. Also, when more than one team member or an application tries to access the data, there could be a problem if the data isn’t synchronized. Therefore, you need software that allow data to communicate without any problem.

Conclusion

As much as big data may seem too complicated to handle, the management tips mentioned above will help you handle, manage, and benefit from big data. With options such as outsourcing data management, adopting it shouldn’t be a problem as you don’t need any special storage equipment.

As AI and machine learning become integral in business operations, many businesses will adopt big data. The sooner you learn to manage it, the better.

轉貼自: BDAN

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