Guest Post: The benefits, issues and 2019 predictions for Big Data

They say “go big or go home”, but that theory doesn’t work for the enormous amounts of constantly-collected data that inundates businesses day-to-day. It’s not the amount of data that’s important, it’s what organizations do with it that matters.

Big Data isn’t the wave of the future – it’s now and it’s constantly evolving. We are on a never-ending quest for data for an obvious reason: it’s the commodity that sparks digital inspiration. This technology keeps on providing more customizable experiences and helps predict the best possible outcomes for businesses and their clients. In fact, by the end of 2021, it is estimated that 70% of enterprises will implement AI. Since Big Data is more than a trend and can’t be ignored, we suggest making it work for you. Consider what is coming next: What are the benefits and deficits to encounter in 2019? Are we going to witness the big return of data lakes and private cloud storages? Is the process ever going to gain transparency? Here are the Big Data trends to follow to make your data flow seamlessly…

How Big Data can optimize your business processes in 2019

Some say that data is the new fuel and currency of our time. Whatever parallel you want to use, the principle behind it is the same: data is the most valuable asset you can have in your business. But only if you use it the right way. The benefits of applying Big Data information to your company are enormous. The sooner you implement those principles to your company, the better the benefits will be. Some of the major advantages of data solutions are:

  • Automated learning and improved business intelligence – Everything is running faster and business intelligence, which was limited, is now evolving.
  • Better insights into customer habits – You can learn a lot about your customers, which can be a tremendous help if you’re running an e-commerce website. It could minimize the number of abandoned carts on your site.
  • Reducing your costs – With valuable insights, you will know when the ‘’right time’’is  to make important purchases, move forward with staffing decisions, and adapt new procedures. adopt
  • Sparking innovation – Thanks to Big Data, we now have a more predictive approach to know exactly what type of products customers are expecting. Customers’ needs are met in ways like never before due to the innovation available to us through these large data streams.

What are the issues with Big Data?

Big Data sounds pretty miraculous, but like anything, there is always a downside. Migrating to cloud computing means more diligence is needed with sensitive data. Data breaches are a severe problem today. If you are using a public cloud – there is always a security risk hidden somewhere.

A data breach could happen in numerous types of ways: hacked accounts lost laptops or hand-held devices, or losing a password to any one of your dozens of accounts. Data and identity theft can happen in the blink of the eye if you are not careful. Other types of threats include hijacking accounts and data loss. Data breaches can hurt businesses and consumers in a variety of ways. They are a costly expense that can damage lives and reputations and take time to repair.

Keep in mind that most employee-related incidents are not malicious. In order to protect the personal data of your customers and your own important documents, think about distributing content leadership roles. To protect your most sensitive files and valuable documents, consider using automatic redaction software.

Also, one of the most important issues businesses can encounter is how fast a data stream can be processed. Due to the enormous volume of data that has been collected by different sources, consistent timing and fast response to events are crucial. It is hard to keep up the pace of handling all the raw data. Integrating the assets of Big Data into your company will probably inspire a complete evolution of organization by embracing brand new tools.

What are the predictions for 2019?

Just when we thought we’ve seen everything, it turns out the wheels of change are still turning. This year we will witness some new changes and some other comebacks. What we can expect?

  • Can Big Data become little data again?

Not little, but let’s just say a slimmer version…and that is not necessarily a bad thing. We don’t think that enterprises will simply reject the huge amounts of data they have been carefully collecting. But, this could happen in a reasonable manner because of the practicality of storing huge amounts of data. Not all collected data is important and we must learn how to use it better and remove the sluff along the way.

  • Data lakes are coming back

The previous adoption of data lakes turned out to be a little messy. But data scientists and experts are ready to take another deep dive. Data lakes are slightly different from data warehouses. Data warehouses are constructed of structured data, whereas lakes consist of raw and unstructured data, ready to be explored. Data lakes act as a storage space for data so engineers and IT teams can easily access it for future use. With data lakes, businesses can easily access vast amounts of data and do an ad-hoc analysis.

  • Hybrid Environments

Cloud environments are finally properly governed and safer for use. With hybrid environments that will gain more popularity in 2019, you will have the best of both worlds: public cloud services combined with a private cloud. By allowing workloads to move between private and public clouds as computing needs and costs change, hybrid clouds give businesses greater flexibility and more data deployment options.


2019 will be the year where more small businesses figure out how to use Big Data and larger companies will figure out how to clean and utilize the nonstop data flow more effectively. (Cleaning data quickly and efficiently should become a prioritized task, we predict.) Regardless of how accurate our Big Data predictions might be, the only thing that is certain about the latest trends of 2019 is that it’s going to a memorable year for the field of Big Data and for every related domain that links to the field.

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