Big Data: Big Data Categories and The Top 5 Big Data Technologies

Big Data Categories and The Top 5 Big Data Technologies 

Traditional data processing application software may not be competent enough to analyze data sets that are very large so this is one reason which has led to the advent of Big data. Big data can be considered as a field that treats ways to analyze or systematically extract information from or deal with data sets regarded as complex. The coming years will surely see more development as far as the Big data world is concerned. Most people who have a connection with this field or are familiar with it know that Spark, No - SQL databases, Hadoop as well as other Big data technologies are extremely productive and such technologies are emerging at a very fast rate. Do we know which of these Big Data technologies are beneficial and will fetch us maximum productivity? Perhaps some of us are not aware of the same. So let's find out more about Big Data in this article.

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If you are interested in Big Data Technology then we would like to inform you that it can be defined as software tools meant for analyzing, processing and extracting data from a large data set. If the data set is too large or complex then it gets pretty difficult to analyze, process or extract information from them. In such a scenario such technologies are extremely handy therefore, they get preference. You may be interested to know the various categories of Big Data technologies.

Such Technologies are Segregated into two Categories Discussed Below

1. Operational Big Data Technologies

This category of Big Data technologies includes online transactions, social media or information from a particular company used for analysis by software dependent on Big Data Technology. Operational Big data Technologies offer operational features to run real-time, interactive workloads. They also let ingest and store data. Some eg. Walmart, online ticketing for flights, railways, etc, Flipkart and many more.

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2. Analytical Big Data Technologies

For retrospective, sophisticated analytics of data, Analytical Big Data Technologies are considered extremely useful. We must highlight the fact, that for a complete big data solution, both are equally important i.e. operational & analytical and both play a pivotal role in Big Data Solution.  Yes, it makes sense to state clearly that Analytical Big Data Technologies relate to advanced adjustment of Big Data Technologies and is more complicated in comparison to Operational Big Data Analysis. This type of Big Data Analysis is associated with real-time analysis, is extremely significant for making correct business decisions and can help business houses immensely. Certain eg. Medical record analysis, stock market-related decisions, or even weather forecasting.

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Top 5 Big Data Technologies

1. Hadoop Ecosystem

First up, we would like to discuss Hadoop Framework. It was developed to store and process data by using a simple programming model in distributed data processing. If you take into account the trend of the past year, you will come to know that Enterprises have fallen back on Hadoop for their warehouse requirements big time. This trend is likely to continue in times ahead as well. More companies will use Hadoop shortly and draw benefits from it.

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2. Artificial Intelligence

Artificial Intelligence ( AI) is a field that deals with developing intelligent machines having a very high degree of efficiency and performance level without the intervention of human intelligence or presence. AI is an ever-growing field and is making its presence felt across various domains. It also takes into account several approaches including Deep Learning and Machine Learning. It won't be an exaggeration if we say that AI is revolutionizing the present Big Data Technologies. Its impact is strongly evident in Big Data Technologies.

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3. NoSQL Database

NoSQL consists of a wide variety of different Big Data Technologies in the database meant for the purpose of designing modern applications. For Web and Big Data Analytics in real time its contribution is noteworthy. For storing unstructured data one can consider it pretty handy. It offers faster performance and is flexible while dealing with various data types like Redis, Cassandra, and MongoDB. It is worth mentioning that it provides easier horizontal scaling and design integrity. It also provides control over opportunities in a range of devices. So it is undoubtedly gaining popularity and getting its due share of credit for its amazing qualities.

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4. R Programming

R is very popular among statisticians and data miners for developing statistical software and data analysis. It is one of the open-source Big Data Technologies as well as programming Languages. It is used extensively for visualization, statistical computing and in unified development environments including Visual Studio assistance communication and Eclipse. It is regarded as the world's leading language by a lot of people. This programming language has been successful in stamping its authority as a strong entity in this field.

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5. Data Lake

In simple terms, it can be described as a consolidated repository meant to store all data formats at all levels both structural and unstructured data or you can say, it is a system of storing data in its natural format.

It has been observed that those business organization that uses Data Lakes usually stays ahead of their competitors and this seems to be one of its major USP. It lets you perform various types of data analysis starting from the dashboard, Data visualization to Big Data transformation in real time which enhances business prospects remarkably. It offers certain distinct advantages by assisting organizations respond to growth opportunities, sustaining productivity, improving decision-making and active device maintenance.

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Conclusion

To summarize this topic, we must admit it's a field with plenty of potential and is growing all the time. It is emerging strongly and we can see it is capable of impacting us in various ways. Traditional methods are not equipped enough to analyze complex data however, in the absence of not being able to analyze and extract proper information, we are set to lose a lot. Fortunately, we have Big Data Technologies that are there to guide us and this is the most immense contribution of this field. If you have any suggestions to offer then kindly express your point of view in the comment section. We will incorporate the same as much as we can. We would like to thank all our esteemed readers for their support.

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