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Common Myths and Misconceptions Associated with Big Data

The advantages that Big Data brings to every organization are many. Initially, only big enterprises have started to implement Big Data techniques and make profits from it. Seeing those benefits, every company is beginning to implement Big Data techniques these days. However, many companies are still implementing Big Data ecosystems to manage and derive useful information out of it. The main reason for this is because there are many misconceptions and myths associated with Big Data. So, let us look at the top myths and conceptions about Big Data.

Big Data is New

Big data is a hot topic in the Business Intelligence world, and because of this big data, Hadoop training and placement courses are gaining more popularity. But still, few businesses are struggling to move from the concept stage to execution. The problems remain the same for the business owners, but the approach to solving the problem is new. With Big Data strategies, companies can make quick decisions with more accuracy. In fact, the dealings with colossal data sets are not a discovery for some of the businesses. They have been dealing with these problems for decades. But in the current world, the amount of data generated from every business has increased significantly. 

Big Data is only about huge information.

The quantitative analysis of the terabytes of data generated from customer transactions, business statistics, social media, photo uploads, etc. plays a vital role in every business’s success. This is the volume, which is one of the three ‘V’s Big Data. The other two are velocity and variety. That means varieties of data include even the small data sets, and thus Big Data is not only about large data sets. Hence the big data Hadoop training and placement in USA are becoming more popular with each passing day. 

Big Data means unstructured data.

The big data handles both structured and unstructured data. That means it is not only related to unstructured data. Unstructured data refers to all types of data which you cannot fit into one model. In short, it has no particular form. The data can be in terms of audio, video, text, and other forms. You can know how to deal with big data if you enroll in big data Hadoop training and placement online courses. Also, people think Big Data means only Hadoop, but it is not the case in Big Data since other tools are available to handle and manage data.

All Big Data is quality data.

The data sets are numerous, and the sources of the data also plenty. But one of the common myths about Big Data is every data obtained from Big Data is quality data. But it is not true. Usually, in Big Data, the information with quality errors is common. But it comes with tools and techniques to rectify and derive the needful information from it. So, as a business owner, you must not rely only on Big Data. 

It is always machine data.

Many people have the misconception that only machine data is the sole source of Big Data creation. Machine data such as the data produced by network switches, IoT sensors, servers, and others are the major source of data generation, but it is the only one. These machine data assist in understanding the IT infrastructures and managing and monitoring its performance. Machine data is a primary source of data, but any other data also qualifies for Big Data. The other kinds of data can be as simple as email and mail addresses of customers. 

Big Data is expensive.

The application of Big Data is mainly used by large organizations like Netflix, Google, etc. This very thought makes us think that only big companies with large capital can apply it. But the fact is you no need to have a large amount of cash or tech giants. Without huge investment, any company can implement Big Data tools and come with excellent big data strategies. If you missed investing in Big Data techniques in the current situation and expected trends for the next few years, be ready to miss more revenue than the capital requirement for implementing Big Data. 

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