What is Big Data , 5'v of BIG DATA and Challenges
- 4. We produce a massive amount of data each day, whether we know about it or not. Every click on the internet, every bank transaction, every video we watch on YouTube, every email we send, every like on our Instagram post makes up data for tech companies. With such a massive amount of data being collected, it only makes sense for companies to use this data to understand their customers and their behavior better. This is the reason why the popularity of Data Science has grown manifold over the last few years. Let’s try to understand what is big data and its benefits and uses!
- 5. What is Big Data? Big data is exactly what the name suggests, a “big” amount of data. Big Data means a data set that is large in terms of volume and is more complex. Big data refers to extremely large and diverse collections of structured, unstructured, and semi-structured data that continues to grow exponentially over time. These datasets are so huge and complex in volume, velocity, and variety, that traditional data management systems cannot store, process, and analyze them. Big data is used in machine learning, predictive modeling, and other advanced analytics to solve business problems and make informed decisions.
- 6. The amount and availability of data is growing rapidly, spurred on by digital technology advancements, such as connectivity, mobility, the Internet of Things (IoT), and artificial intelligence (AI).
- 8. Big Data allows companies to address issues they are facing in their business, and solve these problems effectively using Big Data Analytics. Companies try to identify patterns and draw insights from this sea of data so that it can be acted upon to solve the problem(s) at hand.
- 12. How Does Big Data Work? Big data involves collecting, processing, and analyzing vast amounts of data from multiple sources to uncover patterns, relationships, and insights that can inform decision-making. The process involves several steps:
- 14. How to Store and Process Big Data? The volume and velocity of Big Data can be huge, which makes it almost impossible to store it in traditional data warehouses. Although some and sensitive information can be stored on company premises, for most of the data, companies have to opt for cloud storage or Hadoop.
- 15. Cloud storage allows businesses to store their data on the internet with the help of a cloud service provider (like Amazon Web Services, Microsoft Azure, or Google Cloud Platform) who takes the responsibility of managing and storing the data. The data can be accessed easily and quickly with an API. Hadoop also does the same thing, by giving you the ability to store and process large amounts of data at once. Hadoop is an open-source software framework and is free. It allows users to process large datasets across clusters of computers.
- 16. What are the main challenges? For all its benefits, there are still some challenges to overcome with Big Data. 1. Data Growth Managing datasets having terabytes of information can be a big challenge for companies. As datasets grow in size, storing them not only becomes a challenge but also becomes an expensive affair for companies.
- 17. 2. Data Security Data security is often prioritized quite low in the Big Data workflow, which can backfire at times. With such a large amount of data being collected, security challenges are bound to come up sooner or later. Mining of sensitive information, fake data generation, and lack of cryptographic protection (encryption) are some of the challenges businesses face when trying to adopt Big Data techniques.
- 18. 3. Data Integration Data is coming in from a lot of different sources (social media applications, emails, customer verification documents, survey forms, etc.). It often becomes a very big operational challenge for companies to combine and reconcile all of this data. There are several Big Data solution vendors that offer ETL (Extract, Transform, Load) and data integration solutions to companies that are trying to overcome data integration problems.