Article

Johnny Morgan
Johnny Morgan 8 March 2017
Categories Data & Analytics

Are Your Big Data Decisions Up-To-Date With The Latest Trends?

Big data has been getting bigger with each passing year and the predictors suggest that the year 2017 will retain the trend. Let’s look at some big data trends that will be hot versus those that will be not.

Over the years, we have seen big data emerge as a solution for enterprises and also as a point of research that has attracted many technologies. It would be safe to say that big data will continue to evolve because it is being embraced by more and more organizations either to streamline their operations or to develop solutions that cater to big data needs. But, the question is what will big data trend in 2017. This is the question that will be answered in this blog. Let’s look at some big data trends that will be hot versus those that will be not.

                                     

1. Standard vs. Customized:

Big data will no longer be accepted as a one-solution-fit-all technology. Companies have moved on from the thought that it is just a storage solution. Now, the need is more driven using data in comparison to just creating a repository. Companies are after trends that make big data processing faster and reliable. This requires a quick processing and quick analysis that can be used to make data-backed decisions which will be meaningful to the entire organization. This should not be a difficult decision for business owners because customization certainly has immense benefits in comparison to the cost involved.

2. Hadoop vs. Others:

Hadoop has been a popular services big data management platform for a long time and it has enjoyed this importance all the while because of a variety of reasons including features and also lack of substantial competition. There has been a debate about whether companies will still rely on Hadoop or move on to other ecosystems. But, I feel that although the rise in competition is inevitable this year, Hadoop will continue to be a popular choice because it has established itself as a trustable platform. There are other popular choices like Apache Spark which has moved away from Hadoop ecosystem and established itself as easy to use to platform. Big data developers and consultant are getting familiar with the updates.

3. Cloud vs. Data Center:

Some companies have for long been reluctant to use cloud-based big data platforms for security reasons. The year 2017 can possibly put an end to the debate by declaring cloud-based solution as the most viable and feasible winner. The acceptance of cloud-based systems by some forerunners have motivated others to follow. This has also prompted big data service providers to create custom solutions which will further motivate the companies to aim for the cloud. The other motivating reason would be the cost involved in maintaining a data center that is not even half-effective as a cloud ecosystem.

4. Business Intelligence vs. Deep Learning Algorithms:

Business intelligence and deep learning are a subset of artificial intelligence which is already hot this year. Artificial intelligence has been used to make all kinds if imagination a reality and this same technology is now used to make the most out of the data sets. On one hand, business intelligence Software can make predictions and analysis of the basis of the data stored on servers, deep learning algorithms can be used to derive meaning out of data sets that are diverse without a practical human training or set. While, each BI and DLA have its set of pros for different business, the choice needs to be made based on the business and the kind of interpretation required.

5. Internet of Things and Metadata:

You would notice that there isn’t a versus here between IoT and Metadata because this does not involve a decision but an awareness of how your organization would benefit from the two. IoT does not need an introduction but yes, if your company uses IoT then, you should be prepared for the surge in data that needs to be maintained. A good way of making use of this data is to employ metadata catalogs that can segregate your data on common grounds and make data easy to manage and analyze. There are many platforms that can help you use metadata catalogs efficiently.  

Many Big Data services-providers and service-takers revolve around big data for solutions. Business that provide big data services have to constantly update themselves with the new technology and the business that make use of big data services have to choose the right solution wisely considering the business needs and not relying on what is trending. But, this does not mean that there is no need to be aware of the trends. Awareness regarding the enhancements will help you migrate to a better solution for better business operation. Let us know what you think will trend in the coming year and also which trend have you been watching out the most for.

Azana Baksh
Azana Baksh

Johnny, big data is here to stay. We definitely are seeing an increase in activity with companies responding to the impact big data has made on their business. For companies of any size, getting meaningful insights from data analytics is an important priority. HPCC Systems (hpccsystems.com) is one other open source big data platform with built-in analytics libraries for Machine Learning to help extract useful insights from data. Designed by data scientists, HPCC Systems represents more than a decade of internal research and development in the big data analytics field.

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