What is Big Data?
In general, big data refers to the dataset, usually volumetric, that has been seen and will continue to increase exponentially over time. The main difference between Data and Big Data is self-explanatory and refers to the difference in volume. Unfortunately, no traditional data management tools can be used to store and efficiently process such data. Along with the large size, complexity in processing such data is another underlying issue. Big Data is continuously evolving and expanding. For instance, social media platforms like Facebook and Instagram generate about 500+ terabytes of data every day. This data is generated through photos and video uploads, messages, and commenting in the posts.
- Types of Big Data
Big Data is classified into mainly 3 types depending on its structure and form:
- Structured Data
The data that can be stored and accessed in the raw state and can be further processed in the form of a fixed format is called “Structured Data.” Structured Data, in simple terms, refers to a pre-defined data model, and thus analyzing it is a straightforward process. Advancements in technology have led to tremendous outbreaks in the way such data used to be processed. Now, structured data can be easily and quickly processed to derive value from it, thus extracting crucial information that can influence businesses and augment their growth. There is no extent to which such data can expand up to billions of terabytes.
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2. Unstructured Data
The data with unknown form and structure is classified as unstructured data. Aside from its vast volume, unstructured data is a lot more challenging when processing and deriving value out of it. An unstructured data source is more heterogeneous and contains a combination of texts, images, and videos. One such example is the output returned in a google search, which also shows ads, images, metadata, and links.
- Semi-Structured Data
Semi-Structured Data comprises a mix of both structured and unstructured data. A semi-structured data seems structured in its form, but it is not defined and therefore does not have a fixed format. Unlike structured data, it can not be represented in a tabular manner or any other form of data model or database. A semi-structured data contains tags or markers to demarcate and thus maintain a hierarchy within massive datasets. Hence such data is not very strictly formatted.
- Career Roles in Big Data
A plethora of career opportunities exist in this ever-expanding sector of Big Data. Some of the most prominent yet high-paying roles are listed below to help you understand this science’s crucial role.
- Big Data Engineer: Annual Salary Range – $130,000 – $222,000
- Data Architect: Annual Salary Range – $120,000 – $194,000
- Data Warehouse Manager: Annual Salary Range – $80,000 – $160,000
- Database Manager: Annual Salary Range – $111,000 – $187,000
- Business Intelligence Analyst: Annual Salary Range – $88,000 – $186,000
- Data Scientist: Annual Salary Range – $106,000 – $180,000
- Data Modeler: Annual Salary Range – $81,000 – $170,000
- Database Developer: Annual Salary Range – $101,000 – $173,000
- Database Administrator: Annual Salary Range – $80,000 – $161,000
- Data Analyst: Annual Salary Range – $84,000 – $143,000
- How to become a “Master of Big Data” by pursuing a “Masters in Big Data”?
- Trent University, Canada
Program Name: Master of Science in Big Data Analytics
Duration: 16 months
Standardized Tests: SAT, ACT, GRE, GMAT, TOEFL, IELTS
Being one of the first universities to provide students education in this discipline. The program covers all aspects of Big Data and provides in-depth knowledge about the tools and techniques required to analyze all the data-sets from all departments. Complex areas such as Data Mining, Data Visualization, and Cloud-based approaches to real-world problems are also covered while diving deep into all the programming languages. Through this program, one can even target prominent roles like Chief Data Officer, Data Scientist, Data Solutions Architect, Business Manager, and Business Analyst. Owing to the high demand for this program, the intakes are only accepted in September.
- MIT Sloan School of Management, United States
Program Name: Master of Business Analytics
Duration: 12 – 18 months
Standardized Tests: GRE, GMAT, IELTS, TOEFL
The prestigious university has maintained a top-tier ranking in this stream since 2016. The year-long program focuses on modeling the student’s ability to resolve critical business issues by handling and utilizing vast data sets. The course is open to all aspirants at – undergraduate, graduate, and doctoral levels. The university has a progressive curriculum that consists 5 mandatory subjects, a minimum of 3 electives, six three-hour modules, and another required summer capstone experience & project class. The program is STEM-designated. It means that the graduates will be allowed to stay in the United States for an extended period before the offer letter.
Program Name: MSc in Data Sciences & Business Analytics
Duration: 12 – 16 months
Standardized Tests: GRE, GMAT, IELTS, TOEFL iBT, Cambridge
The university’s program has been ranked #1 in Europe and 3rd worldwide. The program focuses on theoretical and pragmatic exposure, allowing students to take up to 18 advanced elective courses. These electives focus on the all-around web and app development of the students. The program will provide a total of 3 majors in Data Sciences, Business Analytics, and Digital Strategy, along with a plethora of customized electives. Students will be provided with an in-depth knowledge of the technicalities and issues that businesses face globally.
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- ESADE Business School, Spain
Program Name: MSc in Business Analytics
Duration: 12 months
Standardized Tests: GMAT, GRE
The university is well known for its prominent, strong organizational and alumni networks all over the world. These collaborations allow the students to take part in enriching student exchange programs.
The university is known to supplement the students’ practical knowledge by conducting numerous guest lectures and company visits in progressive regions. The curriculum allows the students to collaborate with prominent companies such as Amazon and Microsoft in big data projects. The university also has a “Pre-programme,” which exists to assist the students with no business or industrial background.
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It starts three weeks before the regular classes. Besides, the university will provide the students with a program from Amazon Web Services to help them with Cloud Computing and prepare for the AWS Certified Solutions Architect Associate Exam.
- IE Business School, Spain
Program Name: Master in Business Analytics & Big Data
Duration: 10 months
Standardized Tests: GMAT, GRE, IEGAT
The school aims to produce a generation of well-equipped professionals with the relevant skills to flourish in a Big Data’s career. The program has been ranked #3 in Europe by QS Global. The school also houses alumni and an organizational network of 60,000+ that can provide top-notch guidance and high-paying jobs in this sector. Moreover, there are 114 clubs present in the school in which a student can participate to hone his managerial skills and technical acumen. Around 12 electives are offered in this program ranging from Marketing Intelligence and Digital Analytics to Analytics about Smart Cities, Travelling, Bank, and Health sectors.
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Considering the above content, it becomes vivid that an appreciation for this science is essential. Thus, all business schools worldwide should adopt it as Big Data can affect the organization’s day-to-day inner workings. For an organization to supplement its growth, several key metrics are used. These indicators place the company’s focus on various crucial factors like identifying consumers’ behavioral purchase patterns, market segmentation, and client portfolio management.
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Moreover, the skills gained through the programs mentioned above will allow the aspirant to make tech-induced business decisions and thus manage and communicate with the technical staff. Hence, a career in Big Data is definitely worth the hype.
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