Regardless of how much more affordable data storage has become in recent years, the continuous growth of data volumes is a persistent problem. Organizations need to be able to process and store every bit of data that is created on a personal and organizational level every day.

Big data is almost always a stream. Even if the aim is to analyze data by batches, the business needs to collect it in a stream format. This means that efficient streaming infrastructure should be in place in order for businesses to be able to process data in near real-time.

Nobody except specifically defined users should have access to sensitive data, and setting up the most effective security protocols can be somewhat challenging. Businesses need to find a way to protect transaction logs and data, secure framework calculations and processes, and secure and protect data in real-time, to name but just a few challenges.

Data comes from different sources and in different formats. The challenge for businesses is to integrate the data so that it can be used and analyzed in an acceptable format. Businesses also need to find a solution to merge data that is not similar in source or structure and to do so at a reasonable cost and within a reasonable time.

Before businesses can analyze their data, they need to clean up the existing data and prepare it for further use. Data may be siloed or outdated and validating the data format can be a time-consuming process, even more so if the database that a business uses is large.

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