The Solutions Managing Your Piles of Data

Sometimes companies and organizations have amassed too much data that they are not able to manage it. This big data can present a big challenge to a company such that they are not able to secure their data. This could lead to leakage, phishing, stealing, and all sorts of corruption to the company data. We can define big data as any sort of data that is too large for an organization to process it using conventional tools such as excel spreadsheets, text processors, or even PowerPoint.

Are there data mapping tools that an organization can use to manage their large data pools? What kind of tools are these, and what procedures can an organization use to acquire these tools?

When it comes to data mapping tools, there are some things one needs to consider. You could be interested more in cloud-based tools since they are fast, scalable, and reliable. Even though the functionality of the data mapping tools does not necessarily have to depend on the needs of an organization, consider the following factors:

Should have Wide format support

The tools you use to process and manage your data should be able to support basic files such as delimited text files, XML, Excel, Word, EBCDIC, and other commonly used file formats. Consider tools that can handle common formats used in your environments such as SQL Server, DB2, Oracle, Sybase, and others. Such a tool could be more useful if it can also handle enterprise software such as SAS, SAP, Microsoft CRM, and so on.

Intuitive and automated

These are designed to save time by automating repetitive tasks. They also cater to the risks of human error and have drag-and-drop functionality. This ensures users can match fields quickly and therefore no coding is needed for this purpose.

Workflow and scheduling

This is another important feature of a good data mapping tool that you can use. The tool you choose should map workflow and schedule mapping jobs that are triggered by a calendar of events.

Tips to help you better manage your data

1.   Determine your goals

You need to set goals in your data collection. As such, to manage your large pool of data, ensure that you are collecting the right data and using it for the right purpose.

2.   Secure your data

Ensure that your large data pools are properly secured. Implement suitable firewalls, permission control for members, spam filtering, and malware scanning for better security.

3.   Protect the data

Other than artificial intruders or threats to your data, ensure that your data is protected from natural elements such as heat, extreme cold, humidity, and so on. This means your data storage tools should be protected from these elements.

4.   Follow audit regulations

In case an audit of the data would be required, ensure that this can be availed at any time. Regardless of whether the data managers are on the go, data audit should always be possible.

5.   Data should easily integrate

What this means is that your data should be able to integrate with the many solutions you have as a company. Your data sets should easily synchronize so that more than one team member can access and work on the data seamlessly.