Today, data is an essential asset for every organization, and businesses generate a massive amount of data daily. Therefore, they are required to process that data in a proper format. But do you know what data processing is?

The process of extracting useful information from raw data is known as data processing. The process includes three steps:

• Input
• Processing
• Output

Key challenges faced by companies during data processing:

There are various challenges that companies face while processing the data. Here is a list of such challenges and their solutions:

1. Data collection: Data collection refers to collecting the exact or correct data for input, and companies face a lot of difficulties when it comes to collecting accurate data. For example, if the data collection agent is going to collect data from door to door, it becomes hard to trust the authenticity of the data collected.

Solution:

To overcome this challenge, you need to bring in some useful data collection techniques which are mentioned below.

• Questionnaire
• Direct observation
• Focus group session

2. Data duplication: Same entries may be presented several times if the data is collected from different sources. And because of this duplicate data, incorrect results may be produced.

Solution:

Use deduplication technology to identify duplicate data and remove redundant data easily.

3. Inconsistency of data: When there is no guarantee that the collected data is complete or filled correctly, that data is considered inconsistent. The data may clash with each other if the raw data is collected from autonomous data sources.

Solution:

You are required to keep a check on the data completeness. And to achieve the desired results, it is essential to see the inconsistent field and figure out the errors to achieve database consistency.

4. Diversity in data: The data that is collected from different sources can comprise of multiple varieties. The data can vary from source to source and application to application. As a result, most of the data is unstructured and doesn’t fit into a spreadsheet or a database. This data can be in the form of text, images, audio, and video, etc. But, sometimes we have to process different forms of data together to get the desired result.

Solution:

You can use different techniques to resolve and manage various forms of data, which are as follows:

• Indexing
• Data Profiling
• Metadata
• Universal format conversion

5. Integrating data: Challenges to integrating the data are increased because of the increased number of data formats. Data integration displays the data in a unified manner by combining it using different sources.

Solution:

To overcome this challenge, you need to follow these techniques:

• Consolidate your data
• Federation
• Data Propagation

6. Data volume and its storage: The volume of the data is increased when it comes to processing big data. Due to this, it becomes difficult to store and manage this massive amount of data. Moreover, when we take a backup of our data for protection purposes, the amount of data maximizes which requires more storage space.

Solution:

To overcome this issue, here, we have some possible approaches:

• Object storage
• Distributed nodes
• Scale-out NAS

7. Poor description and metadata: If the data is not in a proper format and is without the meta description of the storage; without adequate documentation, it is challenging to extract the correct data from the database.

Solution:

• Use the NoSQL database for data storage.
• For querying purposes, de-normalize the database.
• For complex data management tasks, use a stored procedure.

8. Data security: Data security is the most crucial part of the business world. Hackers can steal your confidential data or even delete it from the database that you acquired after a long struggle, and it costs a lot to regain it.

Solution:

• Keep your passwords strong
• Provide your associates with limited access to your data
• Backup your data
• Use data encryption

Conclusion

These are some of the biggest challenges that data processing firms are facing today. If you want to manage and process your data efficiently, it is critical to adopt some authentic data management solutions or hire a skilled and experienced professional to get the desired results.