Big Data

Industry 4.0 Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While there is an abundance of tools available in the market, they are underutilized by organizations due to their complexities. Deployment and usage of big data analysis tools require technical expertise which most of the organizations don’t yet possess. Recently, the trend in the IT industry is towards developing prebuilt libraries and dataflow based programming models to abstract users from low-level complexities of these tools. The amount of information produced by IoT and today’s manufacturing systems must be translated into actionable ideas. That’s why Big Data classifies the information collected and draws relevant conclusions that help improve companies’ operations in the following ways:

Improving warehouse processes: Thanks to sensors and portable devices, companies can improve operational efficiency by detecting human errors, performing quality controls and showing optimal production or assembly routes.

Elimination of bottlenecks: Big Data identifies variables that can affect performance, at no extra cost, guiding manufacturers in identifying the problem.

Predictive demand: More accurate and meaningful predictions thanks to the visualization of activity through internal analysis (customer preferences) and external analysis (trends and external events) beyond historical data. This allows the company to modify/optimise its product portfolio.

Predictive maintenance: Data fed sensors identify possible failures in the operation of machinery before it becomes a breakdown, by identifying breakdowns in patterns. The system sends an alert to the equipment so that it can react in time.

Education 4.0 Vast “digital ocean” of data about learners are generated at universities that if analysed can provide valuable insights. Treating data as an asset and becoming a data-driven organization has become necessary for universities in the big-data era. The advantage is, the universities will have the means to improve productivity, make operations more efficient and change the way decisions are made, from opinion-based to fact-based, where they can make better, more informed decisions. Data-driven education enables universities to leverage educational data to get insights about teachinglearning process and to make data-driven educational decisions based on student needs [10]. Datadriven decision-making involves making use of data, such as the sort provided in virtual learning environments or Learning Management Systems (LMS), to inform teaching decisions [11]. Values underlying learning analytics are to analyse student-learning data and its contexts in order to better understand and personalize student-learning experiences [12,13]. Figure 2 shows categories of data that educational institutions need to justify actions, guide actions and prescribe actions [14].

Future Jobs Big Data is everywhere and there is almost an urgent need to collect and preserve whatever data is being generated, for the fear of missing out on something important. There is a huge amount of data floating around. What we do with it is all that matters right now. This is why Big Data Analytics is in the frontiers of IT. Big Data Analytics has become crucial as it aids in improving business, decision makings and providing the biggest edge over the competitors. This applies for organizations as well as professionals in the Analytics domain. For professionals, who are skilled in Big Data Analytics, there is an ocean of opportunities out there. While the other sectors of IT industry are still struggling to create more jobs, the Big Data is creating a great number of jobs with the growing demand for different type of Data from companies. The companies take important decisions with the help their business centric Data. These data are collected, preserved and provided by the Big Data professionals. For this, they are highly paid. As the demand for different kind of data is increasing, the demand for Big Data professionals is also increasing. Although there are many other job opportunities available in other sectors of IT industry, yet Big Data is the future of IT job.