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What Are the Common Big Data Challenges & the Best Ways Out?

10/11/2022

What Are the Common Big Data Challenges & the Best Ways Out?

Big data can be defined as data that is too vast or complex to be properly handled by conventional data storage and processing technologies. Note that this is the era of big data. To your knowledge today many organizations leverage big data and obtain significant advantages as well as benefits. This trend is only likely to accelerate in the future. Therefore, if you are not using big data technologies it’s high time you do so. This step will give you an edge over competitors and make your business modern and more profitable. 

More About Big Data

Remember that there is no particular data size that can be classified as Big Data. The classification depends on the respective organization and the experience of data specialists. Big Data has 3 main characteristics referred to as the 3 ‘V’s’.

  • Volume- The data is difficult and too vast for a particular entity to handle.
  • Velocity- It refers to the rapid generation of data.
  • Variety- Data comes in a sizable variety of formats including text, image, audio, video, documents, RDBMS (Relational Database Management Systems), and more.

A quality big data initiative can streamline processes, save money, ensure early delivery of products/services as well as generate innovations. However, organizations encounter obstacles in implementation. We take a look at the different big data challenges and how to resolve them.

  • Security and Privacy

A company’s data may contain business secrets and customer data. If competitors gain access to such data the company will lose business and the trust of its customers. Also, industry regulators may impose fines holding the company responsible for the leak of confidential customer data. A common mistake is that companies delay implementing the needed security protocols. This makes their data vulnerable to cyberattacks which can prove to be prohibitively expensive to fix. 

Solution

Investment in state-of-the-art security technologies is a must. The staff needs to be trained on best security practices. Thus, the security aspect is taken care of. Remember it is not a waste to acquire modern security hardware and/or software. Also, money, time, and effort spent in training your staff on security techniques are not a waste. Rather it is a wise move to save headaches for your organization in the long run. Recruit cybersecurity professionals having a background in protecting big data. Data encryption needs to be rigorously implemented so that malicious entities and competitors are prevented from obtaining your confidential information and data. 

  • Resistance from within the organization

Employees may feel that big data can be handled using existing techniques and technologies. In many organizations, there is a reluctance of staff to adapt to something new. Employees may not want to share their knowledge and experience with machines. They may fear a loss of their job or a decrease in salary as big data software may take over some part of or whole of their responsibilities. As demonstrated several times, it is human nature to distrust something new.

Solution

The management needs to step in to assure employees that they will not lose their respective jobs and there will not be salary cuts. Staff needs to be trained in using the latest big data technologies. This will instill confidence and lead to skill building. Awareness workshops on the relevance and importance of adopting the latest big data technologies should be organized. All staff needs to be encouraged to attend and participate. 

  • Difficulty in Obtaining Staff with the Necessary Experience and Expertise

Generally, big data technology is complex and challenging to master. Also, technology keeps changing and it can be tough to catch up. That is why big data specialists command high salaries. The demand for big data staff is more than the current supply. That is why you might struggle to hire big data experts with the necessary qualifications and skills.

Solution

Consider partnering with higher education institutions such as colleges and universities. They are a useful source of talent and skills. Otherwise, outsource your big data requirements to an established outsourcing firm having trained and experienced big data personnel.

  • Confusion Over Which Big Data Tools to Choose

There are a large variety of big data tools available in the market today. They come with different features and capabilities. If you select the wrong tool you will end up wasting a lot of time, money, and effort. Also, your business will be slowed down giving the advantage to your competitors.

Solution

Don’t try to select the big data tool yourself. Hire a consultant or organization with relevant expertise and experience. Your inputs are invaluable because no one knows your company’s needs better than you. Armed with your input and their vast knowledge, big data experts can identify the big data tool best suited for your specific needs and preferences.

  • Ignorance of Big Data

Many entities don’t realize the significance of big data. As such, they continue to use old and inefficient technologies. They also perceive big data tools as unnecessary and beyond their budget. But the fact is by investing in big data technologies and training on how to use them will result in ramped-up revenues and profits for your business.

Solution

Train your staff in using big data tools. Make them aware of how performance is enhanced by leveraging big data tools. It is recommended you make it mandatory for each person in your organization to attend big data workshops.

  • Poor Data Quality

One common issue is that organization’s data come in different formats and is stored in different places. Also, the sources of data are usually varied. There may be missing or incorrect data. In some cases, there is a duplication of data.

Solution

Data needs to be cleansed before submission to the big data tool. There exist tools to remove duplicate data and add missing data. Incorrect entries can be corrected and human errors spotted. The result is superior data quality that generates profitable and successful outcomes. Unwanted or useless data can be discarded to improve the quality of data.

  • Difficulties in Integrating Data

Data in organizations comes from a variety of sources such as e-mails, social media, the Internet of Things, customer logs, and more. It is difficult and complex to combine data from disparate sources and present it in an easy-to-understand format. This is a common and challenging big data issue. Data integration enables better analysis, quality reporting as well as a convenient use of Business Intelligence.

Solution

The solution is not to try to integrate disparate data manually. There exist several effective data integration tools in the market. Examples include IBM InfoSphere, Oracle Data Service Integrator, and Microsoft SQL QlikView. Research what kind of data you usually receive. Also study the functionality, features, and capabilities of the different integration tools available in the market. Depending on your budget and unique requirements select a suitable high-quality data integration tool.

  • Issues of Data Growth

Data is growing at an unprecedented rate. As such your existing data storage and processing infrastructure need to be expanded.

Solution

State-of-the-art processes are leveraged to manage the increasing volume and complexity of arriving data. Compression brings down the number of bits of the data resulting in decreased size of data. Deduplication eliminates duplicate as well as useless data. Thanks to data tiering data are stored in the most suitable storage space. This challenge can be addressed by converged as well as hyper-converged infrastructure. Employ tools including Hadoop, Spark, Machine Learning, Artificial Intelligence, and others.

  • Near Real-Time Insights

Data gives the ability to organizations to get insights and use them to boost performance and productivity. Sometimes there is considerable difficulty in extracting maximum insights. The data may be scattered and difficult to organize.

Solution

Use ETL and analytical tools to generate timely reports as well as useful insights. Investment in these technologies is a must to achieve handsome results in the present as well as the future.

Conclusion

Data analysts, Data Engineers, and Data scientists are the need of the hour. Do not live in the past and provide your organization with the necessary big data technology and personnel to remain relevant and profitable. The top management should update themselves with the necessary big data knowledge. They can either be mentored by trainers or do research on their own. Remember that big data expert may be pricey but the investment is worth every penny. Today, data governance needs to be taken seriously. There should be a systematic and mature process in place to manage, monitor, store, and process data. The goals ensure data is not confined to silos, is easy to extract, and provides important business insights. Data governance effectively addresses the issues of security, usability as well as accuracy. There is increasing awareness of the significance of data governance nowadays.

About Us

Focaloid is a stellar software development products and services company catering to clients in the US & UK. We have the necessary expertise and experience in big data. For your information, Focaloid has a team of talented and seasoned professionals with extensive expertise in big data. Over time we have established a mature outsourcing model which is productive, efficient as well as effective. You can safely rely on us to deliver outstanding software solutions and services within stipulated deadlines. Contact us at your earliest to know how we can help you. We are committed to superior client satisfaction and mutual growth.

 

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