On a broad spectrum, big data is a term applied to data sets whose management is beyond the abilities of traditional data-processing software. Typically, big data is defined as the three V’s: high volume, velocity, and variety.
Basically, this means that data which streams in rapidly from a multitude of different sources and is formatted in different ways is called big data. These sources include (but is not limited to) most of the public information stored on social networks, information collected via trackers on search engines, purchases made via your credit cards and what you watch on online streaming websites.
What is Big Data Analysis?
Even before ‘Big Data’ became a household term, manufacturers regularly scrutinised business patterns to identify problem areas and profit points. Big Data Analytics is analogous to this but on a much larger scale.
Considering the rate of flow of input, it is a near-impossible task to manually organise, sort, filter, and culminate useful data in a limited span of time. Big Data Analytics relies on techniques such as machine learning, data mining, and statistics to selectively organize valuable data to optimise business productivity.
Importance of Big Data Analysis
Simply put, if all the data available to a business is captured and analysed, patterns and trends are obtained. These can help the business target its marketing or point of focus to maximize profits. Big Data Analytics help businesses make smarter moves, increase efficiency, and help bridge the producer-consumer gap.
Big Data Analysis first developed into its current form around the year 2012. In today’s world, any type of firm in any type of industry can cash in on this data-driven economy to optimise their business.
Consider Macys.com, effectively a single store of the giant retailer. It places great emphasis on customer-oriented service by means of personalising advertisements, emails, and products. The analytics team has groups dedicated to Data Science, Business Insights, and Customer Insights. Due to this thorough and effective analysis structure, Macys.com is growing at a highly remarkable rate of 50% per year.
Big Data can not only reduce net expenditure by decreasing the costs of storage and shipping but also help industries identify the most profitable moves. Rather than risking failed campaigns, companies can predict success rates to a reasonably accurate extent.
Everyday applications of Big Data
Whether or not we are aware of it, Big Data surrounds us. Whether it’s government, media, healthcare or other service providers, Big Data is slowly beginning to play a major role in effective functioning.
Big Data Analytics can play a major role in smoothly running cities. Traffic flow can be regulated with real-time traffic information, weather data, and social media. If the same data can be accessed by every unit of infrastructure, we may never again need to worry about missing a train due to a delayed bus or being late to work due to traffic.
E-commerce websites like Amazon and eBay can highly personalize product recommendations and emails based on data collected from search history, viewed products, and previous purchases. Analysing the data collected can not only help improve the website’s accessibility and customer-friendliness but can also optimise business by listing products in a most-likely-to-buy order.
Even streaming services such as Netflix, Amazon Prime or YouTube make use of big data in order to provide recommendations to its users.
Insurance fraud can be detected with significantly greater ease using Big Data Analytics. Fraud can cost the medical industry up to $5 billion a year. The current system of fraud detection involves complex SQL queries that can take several weeks to yield results, causing huge losses. With Big Data, billions of billing and claim records can be easily analysed by fraud investigators. Moreover, machine learning and predictive analyses assist greatly by alerting users when a pattern homologous to known fraud schemes is noticed.
Big Data could play a crucial role in maintaining law and order. National security agencies use Big Data to keep abreast of terrorist activity. Big Data can improve cybersecurity. Police forces often use Big Data tools to not only locate and apprehend criminals but also to predict criminal activity. Credit card companies use it to detect fraudulent transactions.
Major players in Big Data
- Apache Hadoop: This project develops open source software for the distributed processing of large data sets. It is gradually being used more and more by high-profile companies as it allows for the processing and transfer of large quantities of data at a fraction of original prices.
- Tableau: With humble origins as a research project at Stanford University, Tableau is currently one of the biggest names in Big Data. It helps in the creation of valuable insights from raw data by providing interactive visualisations.
- Dataiku: Rated by employees as the best Big Data company to work for in 2018, Dataiku specialises in developing data science software meant specifically to handle Big Data. They place emphasis on collaborative work to create highly effective products.
- Google: Famous for the search engine, Google also has powerful data and analytics services. Google is focused on making its products as personalised and user-friendly as possible by incorporating machine learning and data science at the grassroots level.
- IBM: With a whole blog dedicated to their advances in the field of data and analytics, IBM certainly makes it abundantly clear that they are a pioneer of Big Data management. Placing emphasis on acquiring accurate results in less time, IBM is constantly updating and remodelling current tech to optimise the user experience
What could go wrong?
As with any other field, the advent of Big Data comes with its own set of flaws and fears.
First and foremost, there is no guarantee of privacy. As it usually proceeds behind-the-scenes, there is no way for a user to know how much of their personal data is being used. At this point, not even a complete boycott of technology can fully protect all personal details.
Secondly, Big Data analytics isn’t always accurate. Machine learning and data scientists, despite trying their best to improve insight quality, cannot yet keep up with the variability of incoming data. The reliability of Big Data is questioned as even mild inaccuracies can cause losses for businesses.
Thirdly, data could facilitate discrimination. When Big Data is used to check someone’s candidacy for a certain post, the qualification markers are set by the person in power. If they are biased, the verdict will be biased. Suppose you are applying for a job. Your conservative potential employer may be able to access data that indicates that you have extremely liberal views. Hence, he could reject you for the position on completely arbitrary grounds even though you are perfectly qualified.
Of course, as Big Data continues to grow, dialogue and discussion regarding ethics will arise. Steps have already been taken at the global level to ensure privacy. Rest assured, laws will be made to protect people before Big Data can reach its maximum potential.
What to expect?
Big Data and affiliated fields such as analysis, storage, transfer, and privacy are expanding at a rapid rate. Global Big Data revenue is projected to rise from $42 billion in 2018 to $103 billion in 2027. The compound annual growth rate of Big Data is expected to be a whopping 10.48%
Big Data Analytics is mostly a background mechanism, so no drastic changes ought to be superficially visible. However, prepare to be surprised and impressed by how well your search engines and favourite brands seem to know you. Though the changes may not be apparent all at once, the world will change to such an extent that we may very look back on this year and wonder how we ever managed to exist this way.
Akshaya is an aspiring cardiac surgeon who writes both content and creative pieces at any given juncture. As a powerful orator, a voracious reader, and a bit of a know-it-all, she is usually found with a book in hand. A self-labelled fangirl, Akshaya considers herself a connoisseur of all things nerdy.
Contact Akshaya via email: [email protected] or call: +91-522-4333653