Top 5 Ways to Overcome Data Management Challenges in 2020 with Big Data

Big data is on the course of transforming big data experts working in startups and big organizations. This blog aims to throw some light on the top 5 ways to overcome data management challenges in 2020 with big data.

 

Learning Of Blog

• Introduction
• What is Big Data?
• Ways to Overcome Data Management Challenges with Big Data
• Conclusion

 

Introduction

Seeing the popularity of big data certifications, big data is no longer an unknown terminology. Businesses now focus on making data-driven decisions, reaping the benefits of this technology and growing their profits.

 

In the past few years, almost 90% of the total data we have today was generated by us. Most of this data is in unstructured form – meaning that it is generated from smartphones, IoT devices, cloud computing, applications, etc. which cannot be processed by traditional business intelligence tools.

 

Everyone has heard about big data at one point of time or the other. It is present everywhere, but apart from the IT community, no one can tell what big data is and how it benefits in overcoming data management problems. Before proceeding, let’s take a look at the definition of big data.

 

What is Big Data?

In simple terms, big data is the processing and analysis of large volumes of data. It focuses on analyzing complex information that cannot be processed using standard business intelligence tools.

Ways to Overcome Data Management Challenges with Big Data

 

Large data sets of complex information are more readily available today than ever. With the popularity of the internet, cloud computing, mobile devices, GPS, etc., the collection of complex information is far easier. Let’s look at the top 5 ways to overcome data management challenges with big data.

 

 

• A better understanding of customer data

 

 

Most marketing strategies fail because they deliver irrelevant content to their customers. With the integration of proper market research and data science with marketing strategies, companies are able to achieve better results from their marketing campaigns.

 

The technical term used to process and analyze large data sets is data mining. Precise analysis of customer data can reveal a lot about their behavior, likes, and buying habits. Data miners can quickly identify purchase patterns with the help of data. For example, an e-commerce platform can determine if a female buyer is pregnant and design a marketing campaign around the same, offering exclusive offers on products like belly bands, body care kits, and the like to all the pregnant ladies.

 

 

• Increased data processing speed

 

 

We have seen many technological advancements in the last decade, increased automation, smart speakers, IoT, 5G, and the like. All these technologies focus on speeding up the processes in their respective fields.

 

If we talk about speeding up the process of building mobile/web applications, developers need a faster way to process and analyze data; the best method is big data. It analyzed vast volumes of data at lightning speed when compared to traditional data analysis methods.

 

 

• Revamp Products

 

 

Companies and marketers often fail to collect honest feedback data from their existing customers. Feedback data is necessary to test the value of your products in the customers’ life. With big data, it becomes easier to collect and process customer data. The best part is that you can gather meaningful insights from social media data, the type of reviews posted by the customers, new features they wish your product should have, and the like. Such feedback is valuable to re-develop the products according to the customers’ needs.

 

 

• Data Safety 

 

 

One of the most significant challenges of data management is data safety. Big data tools are practical in mapping the data across the company, helping to identify all the internal threats. This will help in protecting sensitive data and preventing data breaches because of carelessness.

 

That’s why companies are prioritizing on using big data to ensure the security of data. This has also increased to demand for big data training courses among IT professionals.

 

 

• Build New Sources of Revenue Generation 

 

 

One of the key reasons to implement big data tools by companies is to analyze the market and create new sources of revenue generation. Businesses can analyze the trending data quickly, collaborate with other companies, and eventually come up with new methods to generate revenue.

 

Conclusion

There’s no denying that big data will be extensively used in 2020 and the coming years. It’s the magic wand that can achieve goals for almost every industry. In order to get the most out of it, companies need to find the best big data certification courses and train their employees. People looking for a switch to data analytics can also opt for big data online training so that they can learn at their own pace.