BIG DATA AND ANALYTICS

The massive amount of data generated by users using social media platforms is the result of the integration of their background details and daily activities. This enormous volume of generated data known as “big data” is being intensively researched.

Analyzing this data enables personalization allowing brands to approach their customers in a more personalized way based on their choices and likes. It gives in-depth insights and a holistic understanding of the audience, which aids businesses in creating tailored communication for them to enhance retention and elevate their trust.

Big data allows marketers to identify social media trends and gain insights, which can be used to make engagement decisions like which users to communicate with, which group of users should receive marketing emails., etc. It also makes it easier to keep track of the demographics to decide which social media platform to target.

By deriving actionable insights from big data, businesses get an idea about the peak timings of customers, their preferences, behavior, etc., leading to increased effectiveness of the social media campaign. Marketers can get important information about the process their clients took right from the first stage of the buying cycle to post-purchase interaction, making them fine tune the campaign at every stage of the cycle.

Big data will thus enable you to analyze the behavior of buyers and target an exact group of people. By giving you in-depth insights, it will assist you in fine-tuning your social media messages and choosing the right platform to communicate them to buyers. 

With the recent advent of data recording sensors in exploration, drilling, and production operations, oil and gas industry has become a massive data intensive industry. Analyzing seismic and micro-seismic data, improving reservoir characterization and simulation, reducing drilling time and increasing drilling safety, optimization of the performance of production pumps, improved petrochemical asset management, improved shipping and transportation, and improved occupational safety are among some of the applications of Big Data in oil and gas industry. Although the oil and gas industry has become more interested in utilizing Big Data analytics recently, but, there are still challenges mainly due to lack of business support and awareness about the Big Data within the industry. Furthermore, quality of the data and understanding the complexity of the problem are also among the challenging parameters facing the application of Big Data.

The recent technological improvements have resulted in daily generation of massive datasets in oil and gas exploration and production industries. It has been reported that managing these datasets is a major concern among oil and gas companies. A report by Brule [1] stated that petroleum engineers and geoscientists spend over half of their time in searching and assembling data. Big Data refers to the new technologies in handling and processing these massive datasets.

The returned value of investments for Big Data infrastructures is of a great importance. Big Data analyzes huge data sets to reveal the underlying trends and help the engineers to forecast the potential issues. Knowing the future performance of equipments used during operation and identifying the failures before happening can make the company to have competitive advantage and bring value to the company.

Machine learning enables computer systems to learn from and interpret data without human input, refining the process through iterations to produce programs tailored to specific purposes. Within the offshore oil and gas industry, this allows companies to monitor complex internal operations and respond quickly to concerns that human operators may not have been able to detect. It not only ensures more safety, by helping eliminating risk points but also improve on capital expenditure by being prepared before hand.

When big data is implemented in an education sector, the entire educational body reaps the benefits of this technology along with students and parents. Measuring a student’s academic performance is through exams and the results they garner. Each student generates a unique data trail during his or her lifetime, which can be analyzed for a better understanding of a student’s behavior. This can then be used to create the best possible learning environment. Big data analytics monitors student’s activity such as their favorite subjects, their classroom performance, extracurricular activities, the time they take to finish an exam and many other things within a student’s educational environment. A report can be constructed which will indicate the interest areas of a student.

Educators can reap maximum benefits of big data analytics due to the processing of data-driven systems. These can help institutions create many learning experiences according to a student’s learning capability and preference. Multiple programs can be fostered which will encourage individuals to choose what they desire to learn. Through this, many reports can be generated in the life of a student around what they would like to do or be in the future. Educators can improve their teaching skills after receiving feedback for a better learning experience equally for all students.

Digging deep into a student’s performance report will help the responsible authority to understand a student’s progress, strengths and, weaknesses. The reports will suggest the areas in which a student is interested and he/she can further pursue a career in the same field. If a student is keen on learning a particular subject, then the choice should be appreciated and encouraged to follow what the student believes in.