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Have You Solved All These Big Data Issues? Featured

Have You Solved All These Big Data Issues? Olav Ahrens Røtne

Big data is a unique technology both in terms of its size and scale. With the advancement of machine learning and data science, big has a potential of impacting live and operations in different industries, in unprecedented levels and scope. Over the past decade, the amount of data generated by different industries has increased substantially. While more data can create an opportunity for businesses, it can also mean more problems if not well used. Here are some of the big data problems that must be solved to get the most:

  • Lack of understanding

Companies seek to leverage big data to improve their performance in different areas of their operations. Unfortunately, most companies do not even know the basics of what big data actually is, its benefits and infrastructure required, among other things. With the lack of a clear understanding, big data adoption projects risk failing. Companies may waste hundreds of thousands or millions of dollars in resources and valuable time on things they don’t know. On the other hand, failure of employees to understand the value of big data can lead to resistance of big data projects that might in turn impede the progress of your organization.

  • Confusion on big data technology choices

With the rising number of big data technologies, it is easy for you to get lost on which technology can best fit into your operations. Choosing between speeds Hadoop MapReduce or Spark can be a challenge, and so is the case selecting the best option for storage of data between Cassandra and HBase. Finding answers to these questions can be difficult, and it can be easy to choose poorly. Therefore, you need a clear view of each of these technologies before selecting. This can be achieved by seeking the help of professionals. Make use of the understanding of your in-house experts such as the CTO or even hire a consultancy firm to ensure you get this right.

  • Too much expenses

Big data projects are expensive and include paying lots of money. This can even be harder if you choose on-premise solutions. You will have to part with money for hardware, new staff (administrators and developers), and software. On-premise solutions also mean more power consumption, configuration, maintenance, setup and development of new software. On the other hand, if you elect to go with the cloud-based option, you still need to get professionals and pay for cloud service providers, setup and maintenance. A solution to some of these challenges entails choosing depending on the technological needs and avoiding unnecessary costs that may strain your budgets for no reason.

  • Data quality management complexity

Big data comes from diverse sources. This creates a big integration challenge since data that need to be analyzed originate from different sources and are in different formats. For example, data may come from social media, website logs and call-centers, among others, and the formats will differ greatly. This can cause problems such as duplication and can contain contradictions that may hamper decision-making. The solution to this can be to compare data from a single point of truth while matching and merging records if they relate.

  • Big data security

Security is a big challenge in big data that needs to be addressed accordingly. It is always difficult to come up with solutions to be implemented starting from storage, encryption and backing up of data. Take some steps such as automation of security updates, backups, and installing regular operating system updates. Also, use firewalls to ensure no unwanted persons can access sensitive information.

In summary, in the modern data-driven environment, you must never under-estimate the importance of proper management of data. Always be proactive and up-to-date with the current trends in technology if you are to compete favorably. By doing so, you will conveniently solve big data problems effectively.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

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