Businesses Around The World Rely Heavily On Big Data To Guide Their Decision-Making Process And Assist In Day-To-Day Operations.

On the other hand, the lack of observation and verification of cloud data is one of the main concerns of companies that use the cloud. This makes data management essential for leading companies.

The inaccuracy of the data, which costs $ 15 million a year, was reported by Gartner in a 2017 review of market data quality. The author of this report noted that low data quality harms some businesses. That’s why businesses have taken steps to ensure that their cloud data is accurate, so they have benefited from checking the accuracy of the data as a valuable asset to generate revenue.

Accuracy and visibility

Ability to view data

A new study of dimensional research, based on responses from 338 IT professionals, found that less than 20% of IT professionals believe they have full and timely access to data packets in the public cloud. The situation is somewhat better in private clouds, with 55% of them visible.

Identified. The survey authors said that the results show that companies have less visibility in their public cloud environments and the tools and data provided by cloud providers are not enough. They address some of the challenges that can be met, including the inability to track or detect problems with program performance and monitoring and delivery against service-level agreements, and delays in detecting security breaches and exploits.

Some of the findings related to cloud visibility from the survey:

• 87% of respondents expressed concern about the inability to view cloud data.
• 95% of respondents said that vision problems caused problems in the network.
• 38% also mentioned the inability to see as one of the important factors in interrupting applications, and 31% in interrupting the network.

Organizations can not lose this position because organizations are engaged in digital conversion efforts and continue to turn to cloud infrastructure. Achieving superior program performance, achieving SLAs, and minimizing the time required to diagnose and correct security issues.

Data accuracy (quality)

Before you start capturing data sets, it is important to understand what data quality refers to. According to Gartner’s research, data quality is examined from several different dimensions, including:

• The existence (does the organization have data to start with?)
• Validity (Are the values ​​acceptable?)
• Consistency (when the same data is stored in different places, do they have the same values?)
• Integrity (how accurate are the relationships between data elements and datasets?)
• Accuracy (Do the data accurately explain the object’s properties for modeling?)
• Communication (Is the data suitable for goal support?)

Data availability and security are important, but the accuracy of the information and how it is evaluated and consumed can easily play a role. Inaccurate data offer little value to businesses, but at the same time, ensuring this accuracy cannot be costly to operate, even as operating environments and architectures continue to evolve and become more complex.

Accuracy of cloud data

Challenges of cloud data management:

• Store and use data volume storage without shredding systems
• Optimal maintenance of databases to ensure the performance of applications and their availability
• Adhere to more instructions, enforce modern security procedures and access control measures

Some data management experts argue that 100% data quality is not achievable in the cloud, especially when data from different or incompatible formats are transferred from one database to another. This file can also be corrupted due to human error, failure to update it, and software bugs.

However, even if you can not achieve 100% data quality, you should focus on achieving as much as possible.