What is data or big data?
We are living in the age of data, where there is a bombardment of data in our daily lives. The term Big Data was devised to tackle and treat huge and intricate amounts of structured, semi-structured, unstructured, and heterogeneous data that is both at rest and in circulation. Such raw data, however, has no value. Big data needs to be refined and processed to be useful. It is the ultimate aim of any big data handling platform to analyze, interpret, and refine big data and find insights, hidden patterns, meaning, and prevalent sentiments in it.
Benefits of big data:
Technology gurus and internet companies agree that data is to this century what oil was to the last century. It is the new resource that will shape our lives in the time ahead. Structured data can be used in several ways that will benefit humankind like as example strategic planning, decision making, and reducing time, cost, and effort in operationalizing businesses. Big data, when used in conjunction with various analytical tools, can help us determine the feasibility of a business venture. It can also predict its success or failure and help us in preventing it. We can detect and find out the loopholes in our planning and do the corrective measures needed for it.
Apache Hadoop big data platform:
Apache Hadoop is a software that performs organized and distributed processing of huge piles of datasets scattered across clusters of computers that number from a single server to several thousand. It is an open-source program for effective, efficient, measurable, distributed processing over a massive amount of data. It performs processing in batches and therefore the response time is not immediate but still, it is acceptable. Hadoop’s ecosystem is almost 10 years old now and it keeps on evolving to reflect the realities of changing times. It is said that big data evolves and changes every 2 years so naturally Apache Hadoop has to keep up with it. You can learn more about it by joining a big data Hadoop course online.
Big Data Challenges:
Big data is a complex and mammoth concept. It involves several inputs (both hardware and software) to manipulate and analyze a huge amount of heterogeneous data. Therefore, it is natural that it faces some challenges. These challenges can be both from the data itself and the inputs used to handle it. For instance, storage of data, ensuring its compatibility with various file formats and types, and retrieval of data promptly for its use. Here we would like to highlight two major challenges concerning big data and these are;
Let’s discuss them one by one.
The challenge of reading security pertains to the data itself. As data is stored in a cloud or at some remote storage facility it is of paramount importance that its effective security is ensured. Data security is concerned with its integrity, accountability, confidentiality, availability, and most importantly its ownership for protection.
Hadoop is well aware of that and makes sure that effective security protocols are in place. Its distributed and partitioned file system has a multi-layered security approach and requires authorization and authentication at various levels, thus making the data safe and secure.
You can master more security protocols by signing up for a big data Hadoop online free certification. It will give you further insight into how to enhance your security levels.
The issue of privacy is also linked to security. Big data platforms like Hadoop invite sinister attacks from hackers for a data breach, leak, and its abuse. The incident of Facebook/Cambridge Analytica is still a cause of concern when it comes to big data and its misuse. Users fear that internet companies that have access to sensitive and private data of their users can misuse or abuse to gain their nefarious ends. Your online presence can be easily mapped and monitored and even your offline activities can be easily traced.
Big data is an intricate technology that records, acquires, interprets, analyzes, data. Hadoop is an open-source program that can handle big data processing. Mastering it requires time and effort. You can join big data Hadoop training online free for learning more about it.