Want to become an expert in Big data analytics, or a Data Scientist, or Big Data architect and don’t know about the future of big data, well you have landed on the right page.
IT industry has seen an immense growth and impact of Big data and its capabilities. The coming years are yet to see a huge advancement and revolution in the field of data science and analytics. With the upcoming tends and application of Big Data the prediction of its future speaks for itself.
We shall now discuss in details some of the latest predictions made by top industry experts about Big Data.
#First Prediction – Need for Real-Time Analytics
In the earlier times organizations focussed on generating relevant data either weekly, monthly or annually but with rising competition and ever-changing stream of data, organizations are required to prioritize real-time data streaming inevitability to step above the competition in 2019. The live data streaming capabilities helps the organizations to analyse the data once it becomes accessible. Real time analytics considerably improves the entire process of data analysis and permits major data science industries to know about the data trends the moment they happen. Real time analytics and live data streaming technology helps greatly within the field of Artificial Intelligence and Machine Learning by accurately updating the user with accurate predictions about the market by efficiently and instantly analysing any frequent changing patterns within the real-time data stream.
#Second Prediction – Source of Innovative Revenue Stream
Since industries are giving a lot of significance to mature and reliable data sets, availability and accuracy of data has successively set its roots as a crucial factor for market prediction. It has also been predicted that in the coming years data will be responsible for generating revenue by offering data as a service. In which case the data sets will be used to derive insights and generating recommendations for third parties.
#Third Prediction – Increased requirement of Cloud and Big Data
Industries are experiencing ever-growing collection of data sets, with the hope to reduce cost and increase efficiency within the data analytics process. Leading to which combination of big Data and cloud Computing have become a perfect combination for the businesses over the industry. It has also been predicted that the global spending on big data solutions via the cloud will grow up to 7.5 times faster than on-premise solutions as it is cost-effectiveness, together with wide availability, and easy accessibility
#Fourth Prediction – Growth in Artificial Intelligence
With the growth and transformation of Artificial Intelligence, IT industry has nearly transformed inside out ever since the commencement of the concept. Industries are adapting and implementing artificial intelligence and its enhancement through big data at a growing rate, which might be inevitable transformation to lay down its initial roots. Also, the growing need of big data for making decisions, Artificial Intelligence as service vendors will be able to provide efficient, low-cost AI-powered tools to specific businesses that have already built out their data sets.
#Fifth Prediction – Emergence of Ethical Intelligence
There is a heft of data across industries leads to moral questions such as its capability to take critical decisions where data is not the only element required for concluding.
There is a niche for a machine to respond ethically and base its decisions on ethical background, by looking the data with a new perspective. This would require the emergence of Ethical Intelligence implemented within the AI-powered machines to simulate a closer human-like thinking network. Industries face the rising need for Ethical Intelligence as a field due to the rapid growth of AI technology.
#Sixth Prediction – Rise in Demand for Data Scientists
Since the major players in the technology-based industry have got onto the Artificial Intelligence and Machine Learning movement, there would be a huge requirement for big data to properly utilize said technologies is more of necessity now. This would ultimately lead to a rise in the demand for Data scientist in the coming years.
#Seventh Prediction – Growth in Edge Computing
The growing data collection in organizations, leads to immediate requirement to reduce the lag between the processing and the collection process. This would further emphasise the need for edge computing in the coming years. Edge computing is one of the methods of cloud computing where the servers are brought to the “edge” of the cloud computing barrier. Edge Computing brings the servers that process and collects the said data as close as possible to the users to minimize the lag duration. Edge Computing, can process and collect the data themselves by accessing the closest node to the edge computing that enabled server located nearby ensuring better performance and reducing cloud computing costs.
#Eighth Prediction – Rise in Natural Language Processing
There is an urgent requirement to retrieve data quickly and efficiently. Natural Language Processing (NLP) is a sub-section of Artificial Intelligence field that has been used to interpret verbal human language and convert it into a machine-understandable language. NLP permits to skip writing complex commands that require technical understanding as a prerequisite and just communicate with the machine normally. This integration of NLP within big data will permit easy and faster data retrieval speeds.
#Ninth Prediction – Emphasis on Protecting Personal and Private
Often consumers are hesitant to share their personal while using an application provided by an organization this ultimately puts the focus of the organizations on protecting user’s data on priority. Given the various incidences of data hacking and court hearings for major technology giants with reference to privacy and security has made privacy mainstream.
#Tenth Prediction – Effort to maintain Clean Data
The increasing need for maintaining and collecting data by industries there also arises the requirement for data cleaning i.e., generating uncluttered and reliable data. Data scientist spend most of their time cleaning data even before starting to build reliable data sets and designing relevant algorithms. The increase in the size of clean data there would be a need for new and more reliable cleaning algorithms to build an efficient process. Coming years will experience data cleaning as a priority in a quick and efficient manner
Big Data market is experiencing a considerable shift in trend with the merger of two big data giants – Cloudera and Hortonworks and the coming years are bound to have a upsurge for data scientist and big data professionals.
