Big Data Challenges and Best Ways to Solve Them

Before jumping down the mountain, you should know how deep it is, what safety measures you need to take, and most importantly, your chances of survival. This sort of knowledge can help you to come up with the right strategy and be prepared for your adventure ahead. 

Similarly, before going for big data, each business owner has to ensure that they have all the knowledge to deal with the challenges ahead. For each decision maker, our big data experts have curated 5 major challenges and provided the solutions as well. This information will help you tame the giants of big data without taking any unnecessary risks. 

Lack of Understanding of Big Data 

It is very common among businessmen and decision makers to have very little information about big data. Most people don’t know what big data is, what the benefits are, and how to make the proper use of it. Without having a basic understanding of big data, it is very risky to adopt it and you may end up losing a healthy amount of time and your valuable resources. Similarly, if all the employees are not certain of big data benefits, they might oppose it and impede the company’s progress. 

The Solution

The best solution to this challenge is to create awareness. How can you do it? Simple! It should be first understood and accepted by the top management and then down the ladder. The IT department can play a vital part in this quest. Through the help of the IT department, numerous training and workshops can be organized to educate the workforce about the benefits it will offer. However, this should not be done forcefully because it may have an adverse effect. 

Managing Data Quality  

It would not take too long for you to come across the problem of data integration because the data you have comes from an extensive range of sources and that too in different formats. Each type of industry will have a new type of data from diverse sources. For example, eCommerce companies have to generate data from their website, call-centers, social media, and surveys. The format of data will obviously be different and matching or synchronizing it is going to be difficult. Moreover, it is also not certain that the data generated or acquired from the sources are reliable. Big data is not always 100% accurate. Period. It may contain wrong or misleading information and duplication as well. In most cases, the inferior of the data brings useful insights and what we consider superior may offer no utility whatsoever. 

The Solution

The ideal solution is data cleansing and for that purpose, your data needs to have a proper model. Once you are able to achieve that, you can focus on other things like comparing the data to the single point of truth, match the records, and merge them accordingly if they belong to the same entity. 

Growing Costs of Big Data 

There is a very common misconception that big data adoption comes with no expenses, after all, it is just data. Wrong! Big data adoption requires lots of finances. If you prefer to use on-premises big data solution, you will have to bear the costs of new hardware, hire new staff (highly paid) like developers and administrators, energy expenses and so on. On top of that, even though the frameworks are open-source, you will still have to pay for the setup, development, configuration, and maintenance of the software. 

For cloud-based big data solutions, you need to hire staff and pay for cloud services, design, development, implementation, maintenance, and whatnot. In either case, you will need to incorporate room for future to plan in time if the big data growth gets out of hand. 

The Solution 

The ideal solution to manage the finances effectively is to prioritize your company’s specific technological needs and business goals. If your organization is not very flexible, you can go for shared resources as well as cost less. For example data lakes and optimized algorithms. These can make things work for you in a comparatively low budget. 

Uncontrollable Data Growth

As the name suggests, the biggest challenge associated with big data is its continuous growth that often at times, gets out of hand. Growth is beneficial but it altogether increases the analysis process. The reason for incorporating big data is to mine it, derive useful information about important business processes, and come up with the best suggestions that help in taking decisions. It is expected that by 2020, the total amount of data will be good enough to fill a stack of tablets that may reach from the earth to the moon 6.6 times. Enterprises and large organizations have liability for more than 85% of that information. 

Today, most of the data that exists is unstructured. After all, who has the nerve and energy to structure it properly? Even if someone tries, it is impossible because it exists in different forms like images, videos, documents, and more. 

The Solution

Since you are focusing on big data relevant to your industry, you can still use data filtration techniques on a regular basis. The data filtration techniques will allow you to maintain only relevant and actionable data while the rest of it would be deleted making space for you to store other relevant information. You can also take the help of administrators who will maintain a regular check on the data growth. 

Data Security 

Big data comes with bigger security challenges. A lot of enterprises claim that they face trouble with security, which is the biggest challenge for them as compared to other data-related issues. The data that comes into enterprises is made available from a wide range of sources. Some of these sources can be trusted while others cannot. The reason is pretty simple; they don’t comply with the organizational standards. 

Big data projects should give top priority to the security holes. It is smart to plan for security beforehand than going crazy when a security breach takes place. 

The Solution 

In order to not compromise your security, you should put your security in the first place. While designing and implementing the project, make sure that the security measures are adequate to cope with any threat coming your way in the future. There are different security testing tools available in the market today that can be of great value. 

Conclusion 

Since we have discussed the top challenges of big data and their solutions, it is now mandatory to give a befitting solution that covers everything. Try to find the right firm that gives you a proper roadmap of the big data project and how it will be implemented across your organization. In this manner, if you need expert help, reach out to us. Our Big Data experts will not only help you but give you the best solution tailored for you. 

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