Big data has cemented its place as an essential practice in business processes in an amazing way. Organizations are beginning to brainstorm on how they can use extremely large data sets to understand their customers and improve efficiency. In 2016, this technology revolved around the Hadoop system, which made data retrieval and analysis so rigid. In 2017, data analysis will move beyond the basics and explore new avenues to gain insights from a large pool of information. Here are top five trends to expect throughout the year.
Increased demand for smart machines
Businesses will have access to loads of information originating from different sources composed of proprietaries and third-party platforms. There will be increased need for enough resources to mine these rich repositories of data and get insights that could make a significant impact on growth. Businesses will have to code and analyze the complex data in an aggressive yet efficient manner. As a result, most of them will resort to smart machines to enable them decode the complex data and present it in a concise and cost-effective way.
Big data tools will hit the web
There will be increased demand for data processing and storage from local platforms and cloud applications as businesses begin to grow their customer base and assets. Top developers will come up with a large number of free data platforms designed to streamline the storage and processing pathways. Such tools will make organizing and synthesizing data simpler through a self-service platform. Users will no longer require wires, racks, servers or networks. Instead, they will use the self-servicing tools to store and compute how much data they need from the information warehouses in minutes.
There will be increased use of cloud computing
Companies are beginning to realize the importance of an elastic infrastructure for large volumes of data. They have discovered that the main factor affecting the rate of data analysis success is not all about Spark or Hadoop but an infrastructure that can keep up with the all the potential dynamics. The cloud will become a popular driver for data deployment. It will foster a good environment for developing and processing data generated outside the networks of the information warehouse. Throughout 2017, companies will see the integration of data storage and analytics, giving birth to a new platform optimized for storing, sorting and managing data ecosystems.
Deep learning will continue to evolve
Deep learning is a set of techniques based on neural networking controlled by machines. It will enable computers to recognize essential items in large quantities from unstructured and binary data. Computers will then deduce relationships without requiring any specific models or programmed commands. Deep learning will feature algorithms derived from the AI industry, which emulate the human brain’s power to observe, analyze and make decisions. It is primarily based on large amounts of unlabeled data. This makes it suitable for extracting meaningful representations from a huge pile of information.
The Internet of Things
The market for Internet of Things is growing at an incredible rate. This growth has been accelerated by the increasing demand by companies to derive value from all data they produce and store. As a result, billions of devices linked via IoT connections will generate colossal amounts of data. This will lead to a new form of hybrid architecture to capture, test and analyze data coming from IoT devices and produce a continuous stream of information. Business will have no any other choice but to bring the two concepts together in order to gain more meaningful insights.
The five trends discussed above are key indicators of a new era in big data. Business should adopt them and make the necessary changes in order to stay competitive and profitable in 2017.
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