by Mansi Pareek
What is Big Data?
Big data is data that is too large, quick, or complex to process using typical statistical or analytical methods. In the early 2000s, industry analyst Doug Laney described the now-standard definition of big data as the three V's: volume, variety, and velocity.
• Volume: Transactions, smart (IoT) devices, industrial equipment, videos, photos, audio, social media, and other sources are all used to collect data. Earlier, storing data was prohibitively expensive but today there are cheaper storage options such as data lakes, Hadoop, and options such as the cloud have alleviated the strain.
• Velocity: Data floods into businesses at an unprecedented rate as the Internet of Things grows, and it must be handled quickly. The need to cope with these torrents of data in near-real time is being driven by RFID tags, sensors, and smart meters.
• Variety: Data comes in a variety of formats, from organized quantitative data in traditional databases to unstructured text documents, emails, movies, audios, stock ticker data, and financial transactions.
Why is Big Data important?
The value of big data isn't solely determined by the amount of data available. It’s worth is determined by how you use it.
You can get answers that
1) streamline resource management,
2) increase operational efficiencies,
3) optimize product development,
4) drive new revenue and growth prospects, and
5) enable smart decision making by evaluating data from any source.
When big data and high-performance analytics are combined, you can do business-related tasks such as:
• determine the root causes of failures, difficulties, and flaws, in near-real time
• detect anomalies faster and more accurately than with the naked eye
• improve patient outcomes by transforming medical data into insights quickly
• recalculate entire risk portfolios in minutes
• increase the ability of deep learning models to effectively respond to changing variables and
• detect fraudulent activity before it has a negative impact on your company
How does Big Data work?
Before getting big data to work, companies must analyze how it moves across a variety of locations, sources, systems, owners, and users. To take control of this "big data fabric," which contains traditional, structured data as well as unstructured and semi structured data, there are five critical stages to follow:
• Make a plan for large data
• Determine the sources of huge data
• Data can be accessed, managed, and stored
• Analyze the information
• Make data-driven, informed decisions
Why study Big Data?
There are Big Data jobs available in practically every sector because Big Data is being used by everyone from retail and banking to healthcare and manufacturing.
Educational software is used by government agencies and businesses to implement effective education systems. It is also used by individual students to improve their learning experience. Social media sees widespread use of big data. Tech companies rely on Big Data not only for their own work but also to provide competitive service to their clients.
This is a growing industry that will only continue to grow.
Given the vast usage of Big Data in today's tech-driven industry, there are also many roles in the Big Data domain, such as data analyst, data scientist, database administrator, machine learning engineer, and statistician, to name a few.
Big Data Courses in the UK and in Ireland
A growing number of UK and Ireland universities are offering postgraduate courses in big data as the subject becomes increasingly in demand.
This is due to the growing understanding of big data and its potential uses, both within businesses and within society as a whole.
Most data science programs lead directly to a career in data science. They include courses in statistics, programming, and data visualization, among others.
You will learn about key concepts, techniques and methodologies, essential coding skills, web analytics, machine learning, advanced database skills and how to analyze, visualize and interpret data. You will learn how to use Apache Hadoop, a software framework that is designed to store and process big data.
A Big Data Master’s degree typically includes taking a series of required and optional modules, as well as completing a major project that integrates what you've learned throughout the year.
A Taught Master's course in the UK or in Ireland is typically for a year. For a master’s course in computing-related or other quantitative subjects, the typical entry requirements are a 2:1 degree. However, this can vary from institution to institution especially for international students.
Given that Big Data is the FUTURE, this is the time to build on your qualifications as Computer Science graduates and make the most of this growing field has to offer.
With high placement rates and high salaries, Big Data is definitely a very strong career option!
Mansi Pareek is a Computer Science Engineering graduate with a flair for teaching. She is a creative thinker, reads all sorts of books and supports ideas that push boundaries. A part of the POLYGLOT team, she also writes on relevant industry trends which are useful for students planning to Study Abroad.