What are the Dos and Don’ts of Big Data Implementation?: Cognitive Market Research

What are the Dos and Don’ts of Big Data Implementation?

Everybody is catching up with technology as data collection and analysis become increasingly common. Businesses are still learning the best ways to use data, despite the fact that many of them are aware of its true importance. What are we permitted to do with all of this data, though, is the real question.

Big data analytics and insights can quickly analyze enormous quantities of data and find underlying connections and trends that the human eye cannot see. All of this happens really quickly. Now businesses have reached the present day, which offers an entirely new world with fresh potential and threats.

Solutions for Big Data Integration to Improve Business Value

The big data platform enhances human abilities in judgment-based tasks and offers insightful knowledge of corporate procedures.

Advances, data collecting and its rapid development, and the cost-effectiveness of data storage are the main drivers of this emerging pattern of depending on technology to support corporate growth. Strategic data collection and analysis are now the main priorities in the company.

Following the data collection, just 26% of businesses are aware of the questions to pose. The main issue is that lots of individuals still need to figure out what they should do with the data, even though business executives let the data guide their decisions. This demonstrates that the installation and analysis of big data still need to be fully integrated. This might be the case since several factors have come to light during this transition in data collection. 

Evaluation of Big Data: What to Consider and What Not to Do

Take a look at this list of things to be mindful of while implementing big data:

The 3 Dos

DO consider the data license terms and any possible effects

This is fundamentally just business. Examine how data is accessible to outsource specific tasks to a service provider for putting the information into perspective. The service you have hired to handle your commercial real estate will need details about your data. It will be necessary to grant a data license, which must specify exactly what data will be made available to them and how the vendor intends to use it.

Accessing data without a license may be considered to be granting an unlimited license. As a result, confidential information that might be important may be "unleashed," and you might be held responsible. There is an explanation why third-party contractors, cloud providers, and outsourcers are always requesting authorization to collect or access customer or client data. It is your duty to use data licensing to secure such information.

DO increase group ability

While building big data infrastructure, numerous organizations and cross-functional stakeholders are almost always heavily involved. As a result, building your data processes throughout those many platforms is reasonable. It is vital to avoid burning bridges in business, just like in any other sector.

It is essential for setting a situation in which you have accessibility to all of the toolsets and procedures available, given the quick growth of big data analysis. The player who has the greatest number of active engagements throughout platforms and mutually beneficial relationships will win the big data game.

DO include every department in the firm in the big data program

Avoiding superfluity, this final DO point brings all the previous ones together and creates an integrated system that will benefit everyone involved. Consistent leadership and transparent management decision-making are components of effective governance.

While protecting all data is nearly unattainable, or at the very least laborious, businesses only require to share data that has built-in security and grant licenses in accordance with those protections.

The 4 Don’ts

DON'T concentrate on specific business unit demands

To execute comprehensive business practices in the modern era, one needs to consider globally while acting locally. Most firms will be able to reduce quantifiable risk as a result, which will instantly have a favorable impact on ROI.

DON'T exclusively rely on technology to achieve your goals

Although technology is accessible, the biggest barrier is still said to be the absence of technology. Open-source systems can be used by businesses for free to try out their functionality temporarily, but this alone won't be a long-term fix until the company is able to secure appropriate funding. They will resort to ROI as the main goal unless it is a company that is entirely analytics-based.

DON'T presume that implementing big data will produce the best results.

In big data analytics, trying to accomplish everything at once will almost certainly lead to failure. Pay attention to unstructured data rather than looking for a large payday. Use or include simpler, easier-to-manage smaller applications. Arrange the implementation procedure gradually. 

DO NOT rely on data scientists to do legal compliance checks for big data analytics.

Even though digital business units are motivated to capitalize on commercial prospects, data scientists solely concentrate on information and reports derived from the data that is currently accessible. Checking whether the relevant rights, consents, or licenses have been documented is not their job or obligation. The majority of businesses aren't adequately interconnected with regulatory and licensing processes.

Conclusion

When thinking about how to integrate big data infrastructure, this would be the ideal approach to put it. The big data platform is not taking away the need for long-term objectives or your company's overall performance from analytics through execution. 

You can adhere to Quality Management Systems (QMS) if you fully integrate the standards set by ISO into your business procedures. Before developing a Big Data strategy, you should consult a professional.

Author's Detail:

Aparna Dutta / LinkedIn

Hello, I am a content writer with 3.5 years of experience. I have experience in various fields of content writing. For example, I have worked in a market research organization where I had to write content related to the reports that the company used to generate to improve their Google ranking. Other than that, I have also worked in website content as well as technical content for print and digital media magazines. Apart from this I am very flexible as a person and can adjust easily.