Big Data Challenges and Ways to Get Over Them

Big Data is one of the most promising technologies for businesses that have to deal with vast volumes of information and need to process them quickly and easily without investing too much time and effort from the side of their employees. Today it is possible to automate all the related processes successfully. Intending to have more accurate data for making business decisions and using them as an additional competitive advantage, many companies today turn to professionals for getting Big Data development services. Thanks to a comprehensive approach to introducing the relevant toolset, businesses can efficiently store, process, and manage data.

It is essential to analyze all core Big Data challenges before developing a company’s strategy related to data. In this article, we are going to explain the most prevalent challenges of Big Data analytics. However, it shouldn’t encourage you to introduce new approaches to working with information. Otherwise, it should help you face difficulties and avoid their negative impact.

Advantages of using Big Data solutions

Here is just a quick reminder of the benefits you can enjoy when you have efficient tools for working with your data:

• Big Data solutions help increase the accuracy of your business decisions and, consequently, help optimize your business processes;
•  With Big Data, you can better focus on your ongoing business needs, detect any possible issues, and timely deal with them;
•  You can reach higher customer satisfaction and loyalty as you can understand your customers’ profiles, personal demands, and preferences;
•  With good data analysis, you can better manage your pricing policy;
• As a result, you can observe sales growth and increased profits.

Challenges of Big Data and solutions for businesses

If you have decided to start using Big Data tools, it will be sensible to consider the following issues combined with possible methods to get over them. Let us also highlight that we can provide only a very general picture of the situation. If you face some issues with the efficiency of implemented solutions and do not know the exact reasons, we recommend you have a consultation with our specialists. Only precise analysis of each case can guarantee 100% success in solving problems.

Data sets are too large

One of the most severe problems with big data is when the storage and tools can’t deal with growing sets of information. Quite often, it may happen so that initially, everything is okay, but it’s crucial to bear in mind that the volumes of data will grow exponentially with time. And it will become challenging to find necessary info and files.

The best solution that we can offer in this case is to create a unified data architecture and ensure solid governance of data. Moreover, such tiering, compression and deduplication methods will also help you handle huge data sets.

Your data are unstructured

Partially this issue is related to the one that was mentioned above. A poor data structure can also lead to situations when you won’t be able to find something that you need, and some critical information can be just lost. The key factors that can lead to such situations are keeping data in numerous formats and storing duplicated content.

The primary advice that we can give here is to ensure data consolidation. It can be helpful to create a data set where you will be able to sort and structure all records and delete all the files that are duplicated.

All info is stored in separate databases

Storing data in silos is also one of the most widely spread Big Data issues. When you have many separate databases and even can’t ensure their communication with each other, you should understand that as a result, your different teams have access to different pieces of data and can’t have a whole picture at once.

In this case, it is crucial to either reorganize your databases differently or organize their stable interaction so that all team members can get the most significant value from the data and efficiently use them to make decisions and prepare their business reports.

There is no coordination of the work with Big Data

It is quite a typical situation when a company has decided to introduce Big Data solutions. Still, there are no tools (and people) to manage the processed data and the received results.

The solution to this problem is relatively simple. First, you can hire a Chief Data Officer. This person will be responsible for enterprise-wide data governance and manage all the processes related to data integration, security, monetization, and data strategy. It will also be a good idea to establish so-called Big Data centers of excellence that are the teams that have a task to ensure fully functional processes related to the use of Big Data to achieve the set business goals.

Your company doesn’t have specialists with relevant skills

 Another challenge you may have when you are just planning to introduce Big Data tools is the lack of experts who have the knowledge and skills to deal with the set tasks.

If you do not have in-house Big Data scientists, developers, and analysts, you can find a software partner that will provide you with such specialists. However, it is also important to ensure that the specialists you want to hire have experience working with appropriate tools and programming languages.

Your data analytics tools do not address the key task

Before building and implementing any business software (this principle is true about any product), you need to set the goals that should be solved clearly. If you want to start using a product just because you want to do it (and it’s the only reason for that), that’s not the right approach. You spend your time and money but do not get any valuable results in such cases.

And there is only one solution here. First, you need to review your business strategy, clarify the core points, and better understand what new tools or functionality of the existing tools can deal with the set task.

There are issues with timely data updating

If you want to reach your business goals and ensure the efficiency of Big Data solutions, information should be updated regularly; otherwise, the analytics will be inaccurate. Yes, you can use historical data in some cases, but due to quick changes in market tendencies and customer preferences, some data should be analyzed practically in real-time.

To overcome this issue, you need to introduce tools for data filtering, Big Data slicing, and fast processing of the relevant data. In other words, the processing cycle should be shortened. Also, it is necessary to ensure automation everywhere where it is possible.

The solution is integrated incorrectly

If the software has been integrated in the wrong way, it can negatively impact your business processes. For example, wrong integration can lead to data losses, leakage, and desynchronization of databases. In addition, if you try to use incompatible software together, the general data structure can become too complex, and the system will be too difficult and expensive to support and maintain.

The best way to overcome possible negative influences and consequences is to ensure the integration of all separate subsystems via APIs and automate the general control of the system. Though such tasks may lead to significant investments, they will help reduce your expenses on system maintenance and avoid further issues in the long term.

There are also some Big Data risks and challenges typical for particular business domains and industries. Below you can find just a few examples.

• Healthcare: timeliness, longevity, and privacy of data that should be taken into account while organizing work with them; necessity to ensure integration of multi-sourced data;
• eCommerce: work with data received in different formats and from many different channels;
• Manufacturing: necessary to develop solutions for estimating the impact of decisions and build infrastructure to support continuously growing databases.

Wrapping up

Big Data analytics is one of the most promising business growth and expansion tools. However, it’s important not to forget that their use and application may be associated with some issues and pitfalls that greatly decrease their efficiency and reduce their real value for your business.

But when you have a good understanding of Big Data issues and challenges that you can face on the way to the digital transformation of your business, you have a great chance to deal with them properly. At Geomotiv, we are always open to cooperation and will be happy to provide you with assistance to overcome issues with Big Data. Just contact us and tell us what problems you have noticed, and our experts will analyze your case. And if you are just considering the option of building software to deal with your business needs, we will be happy to become your long-term IT partner.