The growing role of integrated and insightful big and real-time data analytics platforms

Abstract

Abstract Digitization era is altering several industries which include the way in which the data is analyzed and it is inferred that about 2.7 Zettabytes of data exist in the digital world today. By 2020 the data generated per second for every human being will approximate amount to 1.7 megabytes and the volume of data would double every 2 years thus reach the 40 ZB point by 2020. Interactive Data Corporation (IDC) estimated that by the end of year 2020, the e-commerce transactions B2B and B2C will hit 450 billion per day on the internet. The advent of Big and real time Data has triggered disruptive changes in many fields and the exploding volume of different sources of data like heterogeneous data, data integration, spatio-temporal correlation of data, batch analytics and real-time analytics, data sharing, semantic interoperability requires the development of a scalable platform that can fuse multiple data layers to handles the data intelligently. In Big Data approaches, the challenge is not anymore to collect the data, but to draw valuable conclusions by properly analyzing them. The growth in Unstructured Data generated by business is irrefutable and they are under more pressure to preserve it for longer periods of time. To be clear, exploiting the collected data has been always considered by practitioners and researchers, but the huge velocity, heterogeneity and enormity of massive stream of real-time data shove the limits of the current storage, management and processing capabilities. Admittedly, the traditional method of Extract, Transform and Load (ETL) are challenged and cannot be applied on the emerging opportunistically and crowed sensed data streams. Some of these data streams are structured in a way that serve only one predefined purpose and cannot be directly used for other means. Yet, there are emerging unstructured data such as context-based data from the internet and social media as well as credit card transactions that is not clear if they can be used to better understand the mobility patterns. The analytical company Gartner states that by 2020 there will be over 26 billion interconnected devices. It is obvious, that they will produce massive amounts of meaningful data. Those data can be used for many applications such as real-time industrial equipment monitoring, traffic planning, automated maintenance, etc. Therefore, it is essential to develop modern system abstractions that allow us to resourcefully process huge and new data streams. This enormous amount of data urges the growth of integrated and insightful big and real-time data analytics Platforms. The upcoming contemporary technology like digital twin, integrates historical data from past machine usage to the current data. It uses sensors to collect the real-time data, working status and other operational data attached to the physical model. These components send the relevant data via a cloud-based system to the other side of the bridge with the help of data analytics platform which produces the required insights. The big and real-time data analytics Platforms assist to perform useful operations on data analytics as a complete package. For this purpose, data analytics platform are used to acquire constructive insight from the huge volume of data. Data analytics platform is an ecosystem of technologies and services that can help the businesses in increasing revenues, enhance operational efficiency, stabilize marketing campaigns and customer service efforts, respond more quickly to emerging market trends and gain a competitive edge over rivals. The data analytics platform finds the pattern and relationships in data by applying statistical techniques and communicates the results generated by analytical models to executives and end users to make decisions with the help of data visualization tools that display data on a single screen and can be updated in real time as new information becomes available. Big data and real-time data analytics platform supports the full spectrum of data types, protocols and integration to speed up and simplify the data wrangling process. The big data and real time platform provides accurate data, increase efficiency in the workspace, gives answers to complex questions along with security and hence it plays the key role in business analytics.