what is big data & big data market opportunity

what is Big data-It’s a platform for next generation data management and analytics. It’s a new platform that allows company to perform more flexible analysis on different types of data. Big data  the trend to have changed some fundamental driver in architecting, administering enterprise storage.what is Big data Enterprise are rapidly adjust to utilize cloud storage techniques to remove barrier that block user from being able to retain, access and learn from their data. Data need to be stored in a persistent, dependable and efficient manner in order to generate any real value out of it. (what is Big data)The hadoop system was developed to enable the transformation and analysis of vast amount of structured and unstructured information. As user embrace hadoop for analytics, it’s  becoming clear that relational DBMS are complimentary tool for solving most deep analytic problem. Here, we explain its purpose, characteristics, techniques and challenges,what is Big data

 what is big data

what is Big data-It’s a collection of data sets which is so complex to capture, store and analyze using traditional database management system. It is a massive volume of data handled by parallel computers can be tens, hundred or thousand in number or many more. These smart planet technology and technique enhance the way to get insight the huge data and find opportunities to change the way things are done. Using traditional tools and techniques it’s difficult to harvest the massive volume of data. They have all the information but they don’t know how to get the value out of it because it is present in a semi order or unordered format and as a result they don’t know how to keep it.

Further, the ability to generate, communicate, share, and access data has been revolutionized by the increasing number of people, devices, and sensors that are now connected by digital networks. In 2010, more than 4 billion people, or 60 percent of the world’s population, were using mobile phones, and about 12 percent of those people had smartphones, whose penetration is growing at more than 20 percent a year. More than 30 million networked sensor nodes are now present in the transportation, automotive, industrial, utilities, and retail sectors. (in refernce of -what is Big data)The number of these sensors is increasing at a rate of more than 30 percent a year. Many big organizations are already using big data to create value and other need to explore how they can do the same they are to complete. Governments also have a significant opportunity to boost their efficiency and the value for money they offer citizens at a time when public finances are constrained—and are likely to remain so due to ageing populations in many countries around the world. As the research suggests that the public sector can increase its productivity significantly through the effective use of big data(in refernce of -what is Big data).

In the internet of things, data is exploding in the form of sensors in embedded devices such as mobile phones, automobiles, retail, railway trafficking, road crossing signals, tracking courier cars, retail industry, social network and genomics. But this size of data varying from organization to organization, increasing exponentially every second. (in refernce of -what is Big data)World data is doubling every 1.2 years. There are billions of people in the world and generating terabytes of data. Above all, we are not just consuming it, but also we are generating it either in the form of images, audio, video, text etc. Looking at the history, data was structured, easy to handle with traditional database system, but today it’s highly unstructured and complex. In present era there are the trend of social networking sites such as facebook, twitter and many more. These networking sites have very big log data and tweet data every day. Some or how we are part of big data and top challenges and priority of business and IT’s  harnessing data and extracting value from it. Through advancement of technology, people and things are becoming increasingly interconnected and not just some of the time. And due to this upliftment we are able to add intelligence to almost everything(in refernce of -what is Big data).

Characteristics of Big Data

2.2 Variety: It represents what is Big data,all types of data semi structured, unstructured data as a panel of the decision making. It manages the complexity of data in many different structures, ranging from relational, to logs, to raw text. Traditional analytic platforms can’t handle variety. However, an organizations success will rely on its ability to draws insight from the various kinds of data available to it, which includes both traditional and nontraditional.

2.3 Velocity: It represents the data  exploding with high speed. With volume, velocity and veracity newer technologies are providing visibility of data in greater depth. Velocity is a social media data streams. Big data can be described by its velocity or speed. You do not need all of the streaming data. Big data velocity deal with the pace at which data flows in from source like business process, machines, network and human interaction with thing like social media sites, mobile device, etc(in refernce of -what is Big data).

2.4 Visibility: The greatest distance at which a black object of appropriate dimensions, located near the ground, can be seen and recognized when observed against a bright background dashboard that show top trend. With millions of traffic flows across thousands of endpoints, visibility needs to be pervasive, intelligent and dynamic.(in refernce of -what is Big data) Visibility are using our patented, unique technology, we created in innovative new approach for delivering this visibility called visibility fabric architecture.

2.5 Veracity: The social media data drift while not as bulky as machine generated data produce a large stream of idea and relationship valuable to customer relationship management. Big data veracity refers to the biases, noise and abnormality in data. In scoping out your big data strategy you need to have your team and partner work to help keep your data clean and process to keep dirty data from accumulating in your system(in refernce of -what is Big data).

2.6 Volatility: The big data volatility refers to how long  data valid and how long should it be stored. Big data clearly deal with issues beyond volume, variety and velocity to other concerns like veracity, validity and volatility(what is Big data).

3. PURPOSE

Analysis of records is done to make predictions that help individuals and organizations to integrate, analyze, visualize and consume the growing torrent of big data. As now Digital Data is at all around us as in every economy, in every sector, in every organization and other users of this digital technology. Big data is related with all the activities perform in customer’s products and services stand. An analysis of big data  most important in order to have the ability to storage, aggregate and join the data and then use the results as per usage. Big Data can help to gain insights and make better decisions. Big Data presents an opportunity to create unprecedented business advantage and better service delivery(what is Big data).

4. Techniques used in Big Data

The wide variety of techniques has been developed and adapted to visualize, analyze, big data to make this kind of data volume tractable. Network analysis analyzes connections between nodes in a network and their strength. Lastly, Machine learning uses artificial intelligence to automatically learn to recognize complex patterns and make intelligent decisions based on data. Big data are use seven techniques

• Association rule learning: Association rules are created by analyzing data for happen or done many time at short space between two periods of time if patterns and using the standard against which something is measured support and confidence to identify the most important relationships. Support is something which indicates of how often the items appear in the database(what is Big data).

• Classification tree analysis: Methods are a good choice when the data mining task is classification of outcomes and the targets to generate rules that can be easily understood, explained, and translated into SQL or a natural query language. Classification tree can also provide the measure of faith in one self that the classification is correct.

• Genetic algorithms: Genetic algorithms have been used successfully in a diversity of search and optimization problems. Work on (what is  Big data)genetic algorithm based learning has in traditional form been grouped into one of two general approaches.

• Machine learning: Machine learning, a branch of artificial intelligence, involves the construction and study of systems that can learn from data. Data mining uses many machine learning methods, but in many cases with a slightly different goal in mind. On the other hand, machine learning also employs data mining methods as not controlled learning or as act of processing in advance step to improve learner exactness.

• Regression analysis: Regression analysis found a relationship between a dependent or outcome variable and a set of forecaster. Regression, as a data mining technique,supervised learning. Supervised learning partitions the database into training and validation data.

• Sentiment analysis: Sentiment analysisalso known as opinion mining refers to the use of natural language processing, text analysis and calculative scientific discipline to identify and extract subjective information in source materials.

• Social network analysis: Social Network Analysis and data mining a applying to many different branches of education   journal serving(what is Big data) researchers and professional in academia and industry. It’s the main venue for a wide range of researchers and readers from computer science, network science, social sciences, management and political sciences, etc. We solicit experimental and theoretical work on social network analysis and mining using a wide range of techniques from social sciences, mathematics, statistics, physics, network science and computer science.

5. Challenges faced by Big Data

Big data presents a number of challenges relating to its complexity. Another challenges how we can capture the most important data as it happens and deliver that to the right people in real time.(in refernce of -what is Big data) To aggregate all of this data in a single place while still making it easily obtainable to analysts, you need a customized database. By strengthen your data into a(what is Big data) more user-friendly system data being aggregated from various sources can be segmented, allowing you to determine the effectiveness of each channel. Arithmetic operation databases can be customized to aggregate only the data your company needs, removing the unnecessary noise and making it easier to uncover consumer behavioral trends.