Over the last few years, the increase in data production rate is tremendous. This gave rise to the term big data which essentially refers to extremely large volumes of data. Today, we are surrounded by so many technology gadgets from the large-scale production machines to compact IoT devices. All of these gadgets produce bulks of data every day. If somehow we can collect and analyze all this data intelligently, we can gain numerous business benefits. However, having said all this, the handling of this data is still an issue that many organizations face. Therefore, in this blog, we will talk about the top 5 challenges that most of us come across while dealing with big data. So, let us begin with it.
Storage
Data production does not guarantee that your data is structured, unstructured, or semi-structured. It is relatively easy to store structured data. However, it is very challenging to store unstructured data in traditional databases. Moreover, as the production rate of data grows, so is the need for appropriate storage space for it. Therefore, the storage and archival of big data is definitely a problem that needs to be addressed in the best possible way.
Security
When organizations start producing enormous amounts of data, their main focus shifts toward its processing and analysis. Meanwhile, they totally tend to ignore its security considering it a secondary task. Because of this, all such organizations face highly destructive security breaches down the lane. Therefore, the security of big data should be given due consideration during its production, storage, as well as processing, and analysis.
Big Data Processing
The larger the volume of data is, the more powerful machines you require to process it. For example, if you have a simple Microsoft Excel sheet data to process, you can easily do it on a laptop with ordinary specifications. On the other hand, imagine that you have a database with millions of records to process at once. For that, you will certainly need a very powerful machine that is capable of handling big data efficiently.
Data Quality Issues
Data quality is another major challenge with big data. You need to ensure that the data you are collecting is actually relevant to you. Moreover, even after the collection of data, you need to be sure of its integrity which should not be compromised at any cost. You should also keep focusing on data cleaning so that you can gain meaningful insights from your data. Otherwise, poor-quality data can lead to flawed business decisions.
Big Data Expense Management
Finally, when you deal with big data, you face crucial cost management issues. The storage, processing, analysis, and security, in short, everything has a cost associated with it. You should be aware of this beforehand so that you do not run out of these resources at a later stage. You should know very well that the cost of dealing with large volumes of data will certainly be more than any regular data.
Concluding Remarks
Big data is indeed a very powerful tool these days. However, dealing with it effectively comes with so many challenges. We have discussed the top 5 of these challenges in this blog. Furthermore, if you ever need to develop your very own big data solution, you can take the services of Folium AI.
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