Data Trends to watch out for 2019
Data today is the determinant of fates of many a marketing practises and business strategies. 2019 will be the year that will see true large scale integration of data mining, organising and analysis into operations and decision making for businesses. But before looking at what are the markers that will shape Big Data this year, let’s clear up the all important basics, and understand the true meaning behind what is otherwise empty jargon -
Data Science is everything that pertains to the field of data collection and organising. Big Data is just the term used often in industries like Finance and Retail for decision making informed by insight analytics.
Data Analysis is preparing relevant insights to inform said decision making through use of tools and techniques that make up Data Analytics - which is nothing but usable queries and data segregation procedures to look into requisite data sets.
Simple right ? Glad that’s all cleared up. So without further ado , here are the trends set to affect all things Data in 2019 :
Data in the times of IoT
2019 will surely see a more intensified research into Internet of Things (IoT) data analysis. Streaming Analytics is already gathering steam and combined with Machine Learning, it can have interesting implications for data storage and learning models as we know it.
The primary application of Machine Learning is to train models in terms of soft computing, while streaming analysis can enable analysis of data being streamed, which is extremely important for IoT. Combined, that can enable learning for models in environments that aren’t totally controlled.
It was inevitable that AI would eventually be applied to make dynamic platforms, and 2019 seems to be the year when we might even see either startups or existing Internet giants roll out a service based on the same.
AI platforms are frameworks designed to work more efficiently and effectively than more traditional frameworks. This can help reduce costs in several ways—such as by preventing the duplication of efforts, automating basic tasks, and eliminating simple, but time-consuming activities.
The Data Curator
2019 will really be the year of the Data Curator. Responsibilities for the Data Curator include managing metadata of an organisation, ensuring the data is well protected, organising data, and maintaining data integrity.
Data Curators are often responsible for presentations, with the data shown visually in the form of a dashboard, chart, or slideshows. Thus Data Curators will ensure not only maintenance of data but also it’s management.
If you thought 2018 was a rough time with GDPR, think again. 2019 will see the law being truly imposed in the EU, which means big investigation into the obviously questionable data flow model of the information economy.
Across the Atlantic the authorities might have a very different attitude towards privacy but the people nonetheless are becoming aware and more cautious. If the investigation into Facebook are any indication, Internet Giants might have to significantly overhaul the current data transaction model, and the implication of that will be huge.
Along with these trends, it seems certain that in the coming year emphasis for Data Science will be on decentralisation of Data in general. This would mean dismantling of existing data management hierarchies and a move towards a decentralised, cluster-modelled network.
The tiered data storage method, where different media are used for different types of data, will be commonplace in the coming year to optimize space usage and cost.
All in all, the year looks bright for Engineering students who opted for Data Analytics a few years go.