It’s incredible how quickly data can now be gathered. Given the volume of data available, big data is expanding more quickly than ever and fueling several profitable ideas across a wide range of sectors. Let`s find out what the Big Data Challenges are.

The best approach to managing the massive quantity of data requires storing, analyzing, and processing the enormous amount of data storage. This is one of the key big data challenges. 

When working with big data services, there are several important challenges to face. Let’s examine them more closely:

Main Big Data Challenges To Face In 2022

1. Lack of Professionals

Companies require qualified data specialists to manage these contemporary technologies and huge Data tools. To work with the technologies and make sense of enormous data volumes, these experts will include data analysts, data scientists, and data engineers. Any company may have difficulties due to a shortage of big Data specialists. This frequently occurs because, while data handling tools have advanced quickly, most professionals haven’t.

Solution

Businesses are spending more on the hiring of qualified experts. To get the most out of the current employees, training programs must also be offered to them. The purchase of information analytics products driven by artificial intelligence/machine learning is another crucial action performed by enterprises. Professionals with a rudimentary understanding of data science but no data science expertise frequently recommend these Big Data Tools. This action enables businesses to significantly reduce their hiring costs.

2. Lack of understanding of Big Data services

Companies’ efforts to use Big Data fail due to a lack of knowledge. Employees might not be familiar with the definition, sources, processing, and storage of data. Data experts may be aware of what’s going on, but others may not have a clear picture. Employees might not preserve the backup of sensitive data, for instance, if they don’t comprehend the value of knowledge storage. They were unable to effectively store data in databases. Because of this, it is difficult to get this crucial data when needed.

Solution

Its lectures and workshops must be given at workplaces for everyone. All employees who routinely handle data and are a part of big data initiatives must be put through military training programs. The company as a whole has to instill a fundamental comprehension of knowledge ideas.

3. Data Growth Issues

The effective storage of these huge volumes of data is one of the most urgent problems with big data. Companies’ data centers are storing an ever-growing amount of knowledge. These data sets become more difficult to manage when they expand rapidly over time. The majority of the information is unstructured and is derived from text files, movies, audio, and other sources. This implies that it will be quite hard to find those data within the database.

Solution

The three contemporary techniques that businesses use to manage these massive data sets are considered to be compression, tiering, and deduplication.  

By using compression, data may be reduced in size overall by lowering the number of bits. 

The elimination of redundant and undesired material from a knowledge set is known as deduplication. 

Companies can store data in several storage levels thanks to data tiering. It guarantees that the data is kept in the ideal location for storage. Depending on the volume and relevance of the data, the data tiers are frequently flash storage, public cloud, and private cloud. 

Businesses are also selecting Big Data technologies like Hadoop, NoSQL, etc.

4. Poor Selection of Big Data Tools 

Companies frequently struggle to choose even the simplest tool for large projects with analysis and data storage. Which data storage technique is simpler, HBase or Cassandra? Is Hadoop MapReduce adequate for data analytics and storage, or will Spark be a much superior choice? Companies are troubled by these inquiries, yet they are occasionally unable to look for solutions. They discover that they frequently make poor choices and choose the wrong technologies. As a result, it becomes a time and money-consuming activity.

Solution

You should look for skilled experts who are far more knowledgeable about these tools. Searching for a professional consultancy firm is another option. Consultants and advisers will provide the quickest and most effective techniques and recommendations to help to resolve the situation your firm is currently facing. You’ll be able to choose the most accessible instrument for you, following their guidance.

5. Data Integration

In a business, information is gathered from a variety of sources, including social networking sites, ERP software, customer logs, financial reports, emails, PowerPoint presentations, and employee-written reports. It could be difficult to structure reports after combining all of this data. This is a zone that companies usually ignore. This is unfortunate, as data integration is quite useful and essential for analysis, reporting, and business intelligence.

Solution

Companies must get the right tools to address their Data Integration issues. The following list includes some of the simplest data integration tools:

1. Talend Data Integration
2. ArcESB
3. IBM InfoSphere
4. Xplenty
5. CloverDX

6. Securing Data

One of the intimidating issues of working with big data is protecting all these massives of information. Unprotected data might serve as a potential source for hostile hackers, thus not securing your information is not a wise decision. 

Solution

To protect their data, companies are hiring cybersecurity experts. Data encryption is one of the additional security measures employed. Segregation of data Control of identity and access Implementation of endpoint security usage of security solutions like IBM Guardian and real-time security monitoring.

Examples of Big Data Challenges in Different Spheres

Main Challenges in Security Management

Security problems and assaults are ongoing, and they might target many Big Data components, such as the data source or stored data. Here are a few such problems:

• Vulnerability to the creation of false data;
• Granular access control issues;
• Data Sources;
• Real-time data security and protection.

Top Challenges in Cloud Security Governance

Some of the challenges that Cloud Governance features help us in tackling are:

• Performance Management;
• Governance Control;
• Cost Management;
• Security Issues.

What are the challenges in the healthcare industry?

Doctors will be able to identify the patterns in the data that have yet to be discovered via analysis of healthcare data. The following are the difficulties with big data application in the healthcare sector:

• Enhance the precision of diagnoses;
• Prescribing preventive medicine and health;
• Providing results in a digital form;
• Using predictive analytics to uncover previously hidden patterns;
• Providing monitoring and treatment in real-time.

Conclusion

You can see that there are answers to the numerous big data problems that businesses are constantly dealing with. The secret to assuring the execution of appropriate solutions, even though these difficulties may occasionally change, is to bear in mind the objectives and technical requirements of the business. Big data is here to stay, and organizations should start looking for answers to the problems it brings with it right once.