Multimedia Big Data Management Processing And Analysis

Big data is the present most-liked theme of today 's technology. These research goes through all description of techniques and technologies of extracting of the data, storing of data, distribution of data, analyzing of data, managing of data with high velocity and from the structured data and helps in the handling of the extreme data. Big data has the presentation the capacity to improve predictions, saving money and enhancing the decision making process in the fields of the traffic control, weather forecasting, disaster prevention, fraud control, business transaction, education system, health and the national security.

Big data is anything which is too large for traditional databases to handle. They range from Terabytes of data to petabytes of data. Big data is generated from various sources, such as social media networks, oil wells, mobile phone conversations, weather data etc.

Variety – The format of data comes in many forms. These forms include numeric data, text documents, email, video, audio, etc.

Big Data is becoming more meaningful with the ever more powerful data technologies, which enable us to derive insights from the data and help us make decisions. Big Data also creates new courses and professional fields such as the data science and data scientist, which are aimed at analyzing the ever growing volume of data. Some might think this exaggerated because data analysis, after all, not a new invention. However, we might all agree that the progress of digitization associated with the generation of ever larger amounts of data have totally changed the ways we deal with data.

Big Data can mean different things to different people/organisations – one organisation’s big data of a few terabytes may seem small compared to another organisation’s big datasets in petabytes or exabytes. Big Data is typically described by the following characteristics, known as the “5 Vs”:

With 3.2 billion internet users [1] and 6.4 billion internet-connected devices in 2016 alone [2], unprecedented amount of data is being generated and processed daily and increasingly every year. With the advent of web 2.0, the growth and creation of new and more complex types of data has created a natural demand for analysis of new data sources in order to gain knowledge. This new data volume and complexity is being called Big Data, famously characterised by Volume, Variety and Velocity and has created data management and processing challenges due to technological limitations, efficiency or cost to store and process in a timely fashion. The large volume and complexity of data cannot be handled and/or processed by most current information systems in a timely manner, while traditional data mining and analytics methods developed for a centralized data system may not be practical for Big Data.

Like the traditional data, big data through a series of steps that contain collection, storage and analysis to form a complete system to help both enterprises and individuals produce an optimum strategy or decision and maximize benefits in their stance. As for traditional data system, it is usually not enough accurate in analyze the phenomenon or the situation due to lack of sufficient data that results from the speed of collecting data is relatively low and the process

Data or piece of information which is generated and used through history. This collected and

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

Big data is defined as “large data sets or to systems and solutions developed to manage such large accumulations of data, as well as for the branch of computing devoted to this development.” (“Big Data”) This definition of big data was not added to the dictionary until 2014. The next big thing in business analytics is a relatively new, yet, explosive business practice known as data mining: the collection and analysis of big data. (Fayyad) These large, seemingly random, sets of data are condensed and analyzed for patterns and trends by people with a very broad set of skills. These people are known as data scientists and are considered unicorns in today’s job market.

Big data refers to the collection and subsequent analysis of any significantly large collection of data that may contain hidden insights or intelligence (user data, sensor data, machine data). when analyzed properly, big data can

Presence of big data is a very common phenomenon now days, specially when talking about medium to large size corporation. Manyika et al., in their article (James Manyika, 2011) defined the term big data as “large pools of data that can be captured, communicated, aggregated, stored, and analyzed”. To clarify they suggested that big data refers to data, whose size makes it impossible to be processed by the typical software used for database management. Gartner (Gartner, 2012)defined big data in terms of its characteristics of high volume, high velocity and high variety. By volume, he referred to the size of the data, by velocity he referred to the speed at which the data is created and by variety he referred to the range of types of data.

Abstract— Big data is a significant subject in modern times with the rapid advancement of new technologies for example, smartphones, pc/laptops, game consoles, that all in some way store information. Big companies require a place to not only store all the data that is coming in but to also analyze it for specific purposes and at the fastest speed manageable. There are many different providers out there who provide this service, this paper will talk about one way the company Google handles data using their own special made platform.

To address the question of how and what techniques has been used to manages this big amount of data or in the field of Big Data, I review some research papers and review articles in the field of Big Data. This paper provides the synthesis of those papers which I found relevant to this field. This paper will focus on the following things:

There are many fundamental issue areas that need to be addressed in dealing with big data: data acquisition, data storage, data transfer, data management, and data processing. Each of these issues represents a large set of technical research problems and challenges in its own right.