If your IT department is struggling with data management, it is no exception. Virtually every business today faces the challenge of how to take advantage of ever-increasing volumes of data without increasing the size and cost of the IT department.

Of course, there are still suitable solutions to the above challenge. Here are four steps IT can take to manage business data more effectively.

Have an overview

The prerequisite to solving a problem is that you must understand the problem. Similarly, you need a comprehensive and in-depth view of the amount of data your business holds.

If you don't have a clear understanding of which data is important, and therefore need to prioritize resources, and which are not, funds for data storage and analysis will be wasted.

You can use specialized software, based on metadata, to determine elements such as when a particular data file was last opened, when it was changed, by whom, by what application, etc. Data that is not accessed or modified after a certain time (1 month, 1 year…) should be identified as low priority data and transferred to low cost and performance storage systems.

Before embarking on other information management issues, it is imperative that you get an overview of how data is handled across the enterprise rather than just on individual systems. .

Integrated storage solutions

According to a survey conducted in 2016, the majority of large corporations in the US are currently using more than 20 different data storage solutions. Even smaller businesses are running multiple storage systems at the same time. As businesses grow, the scale of these systems also expands and consumes a large amount of money on both infrastructure and software.

Besides, the difficulty in moving data back and forth between these storage systems also leads to the situation that important data is not stored in high-performance systems.

Enterprises can avoid this problem by virtualizing data with specialized software, thereby creating a common namespace for all data storage systems. As such, applications can access any data no matter where it is stored.

With virtualization, the control path and data path are separated. As a result, you can easily control any fragmented data in various systems.

In addition, data can also be moved quickly between storage systems without affecting the operation of the software that is using that data. Thus, important data can be prioritized to high-performance servers or storage solutions, while low-priority data is moved to cost-effective servers or storage solutions. lower performance and lower performance. In addition, you will also avoid the data migration process that is a lot of work.

Data storage in the cloud (cloud) or object storage (object storage)

Adding data storage solutions in the cloud or object-oriented storage is one of the ways businesses can cut IT costs. The biggest challenge is how to integrate the cloud storage solution with other enterprise data storage solutions.

One thing to keep in mind when bringing enterprise data to the cloud is to make sure you can easily migrate it back to on-premises storage systems at the file level when needed.

In general, bringing data to the cloud is less expensive than the reverse process. Data when put into the cloud is often deduplication. If you want to get the data back into the on-premises storage systems, you need to reverse this process and reconstruct the data chunks (also known as rehydration). Without careful consideration, the cost advantage of cloud technology can disappear.

Automate data management

The final step to perfecting the enterprise data management process is automation. Some hosting providers may offer this capability for individual solutions or for their entire ecosystem of solutions. If you want to automate all data management activities on multiple storage systems, you can look to metadata management software (metadata engine).

With the explosion of machine learning technology, the application of artificial intelligence to information management is no longer a distant idea. In the near future, the software can recognize patterns, for example, which data is used the most at the end of each month or quarter, and can automatically move that, if pre-configured, to specific dates. High performance storage system.

The source: blog.trginternational.com