Clear Concept About Big Data and Big Data Technologies

by Jhon · November 12, 2016 Cloud Computing

Big Data technology

How Big the Big Data is!

Basically, data means a term that identify some specific measurement of objects or things. Big Data means the large volume of any data. It also describes the data in condition that is in structured and unstructured. In today’s world, Big Data inundated for the every highly established business organizations.

But the Big Data is not that kind of data those are really importance to all. These are those data which only matter to a particular organization. Now Big Data is an important and essential matter which can lead an organization to take better decisions and give some suggestion to motivate more skillful strategic moves by analyzing for insights.

History & Present Deliberation:

Actually, the term Big Data is new but the main thought or idea behind the Big Data term that was eventual ages old. Because the analysis concept is gained information and stored them like today’s Big Data can do so.

big data - webtady

The term Big Data depends on some major factors or dimensions. Those dimensions are focusing via a short summary as given below.

Volume:

In present world, different organizations collect data from different sources. Like business transactions, social networking sites, machine to machine data parsing. But soon, the organizations are faced that, it really become a problem to store a huge amount of data that are collecting by themselves. So, they introduce new technologies called Hadoop that can erase this kind of burden.

Velocity:

To storing data, it is mandatory to access data for further use, it should follow streams methods. But data streams are not good at all. An unpredictable speed and timely manner are the main obstacles in this situation. So, to solve the problems, it has been introduced by the RFID tags, sensors and other smart metering system that directly deal with torrents client of data that can access in near real time.

Variety:

In storing data, it comes or combinations of different types of format. From basic level, structured types to numeric data, structural data language to unstructured texts like documents, email, media files and other economic transactions.

Variability:

When a huge number of data increased the velocity and varieties conditions in storing data, it can be a problem that make a data flows. A data flows is a highly inconsistent with some traditional peaks. Because to manage the daily or a monthly event-triggered peak, it going to be more challenging to manage the whole unstructured data things.

Complexity:

To maintain a huge number of data that comes from multiple sources, it becomes really difficult to link and manage the all sources. It becomes also challenging for cleanse and transforms the data system over the machine. So, to ensure the less complexity its hardly necessary to connect and correlate data with the other data. It will be helpful to find out the easy controlling power in Big data system.

Big Data Analytics:

The process of collecting data from the different sources, organizing those data, and analyzing those data in large scale for identifying some useful pattern or information is called Big Data analytics.

The Big Data analytics help to organize to make a better under stable information that contains a clarification about the result from the Big data.

Big Data is a High-Performance Analytics:

To analysis a huge amount of data an organization needs specialized software or tools. This kind of software helps to predicate the analytics, data mining, optimization and performance information. But there is some limitation, sometimes the collective result or process are not helpful the make the better decision by observing the report of those software.

In this situation, if a company use this Big Data Analytics, it will be easier for make a better decision for the future, which is more relevant even that can be a hundred times better analyzed power.

Big Data Analytics Challenges:

In Bid Data system, the data stores are some particular measure. One is unstructured and structured. So, this is one of the major challenge for big data to process all the data measurement in the same platforms. Typical software and tools cannot perform this task for their limitation but it also takes time for Big Data analytics but also time and cost coefficient.

Another challenge is, break down all the data silos into an ideal format from the storage drive that can access from all data organization and other places as well.

Big Data Hadoop:

Hadoop is part of Big Data term. It’s a kind of an open source software framework which has ability to storing a large number of data and also running the data according some applications from clusters like a commodity hardware profile. Hadoop has a brilliant ability to store a massive number of information for any kind of data, for any kind of file formatting system. Besides this, it also some amazing power that helps to process a task more flexible and also some virtual limitless ability to handle virtual things for the concurrent tasks or jobs.

In 2008 Yahoo released Hadoop as an open source project.

Currently Hadoop’s framework and ecosystem of technologies are managed and maintained by world most prominent software foundation named Apache Software Foundation (ASF). It is a global community of software developers and many contributors from different places of the earth.

Importance of Hadoop:

Hadoop has some special ability to store and a successful processing system of huge amount of any kinds or formats of data. The key consideration of data volumes and varieties comes from the social media and the Internet of Things (IoT).

Another special ability of Hadoop is its own computing power system. By the used of Hadoop distributed computing model, the Big Data is accessing more fast than any other typical kind of data analyze software or tools.

Like relational database system the flexibility is not so handy at all. There some limitations and some other declarations before storing data or particular types of data formats. But in Hadoops users don’t need to decide to make some preprocess of data before storing it. So, in this point, users can store as much as data as they like to store and the how to use it later thinking.

Besides all of these, Hadoop is an open source framework system. So, it is totally free and a user can customize the whole model according to his/her needs.

According to SAS there is some challenges those can be faced by user when he/she going to use Hadoop. Those are listed below according to SAS statements.

MapReduce programming is not a good match for all problems
There’s a widely acknowledged talent gap
Data security
Full-fledged data management and governance

Big Data Technologies:

McKinsey a Global Institute report summarize and characterize the main components and ecosystem of big data as below:

Techniques for analyzing data, such as A/B testing, machine learning and natural language processing
Big Data technologies, like business intelligence, cloud computing and databases
Visualization, such as charts, graphs and other displays of the data

Beside of above components there is also a part that familiar with named Multidimensional Big Data. It is necessary to take some handled and more efficiently tensor based computer to apply the things of Big Data really needs. Based on above circumstance the Big Data stored a huge number of files, that really need for search based applications, data mining, distributed file systems, database as well as cloud based infrastructure.

Big Data Examples:

There are also some world ranking startups, those are working on Big Data things to analyzes the more perfection decision for the organizations. Some examples are given below:

Predictive analytics:

This will be analytics software which use to discover, evaluate and optimize the data from Big Data and deploy the predictive models.

Discover of Sun and Knowledge:

It will be tools or technologies that support own self, to support self-service options. This will be beneficial to extract the information and new insights.

Analytics of Stream:

For the power of Hadoop, now a software can filter, aggregate and also can analyze a really high of data from multiple disparate from the various sources.

Data Integration:

It is a tool that used for data instrumentation across to the solutions such as Amazon Elastic MapReduce (EMR), Apache Hive, Apache Pig, Apache Spark, MapReduce, Couch base, Hadoop, and MongoDB.

Every enterprise always looking for something that makes an enterprise to boost its sales, increase efficiency and flexibility, improvise operations management and other factors. To thinking about above factors, the Big Data term is the right and needed answer to survive with others commercial companies.

About 62 percent of respondents already stated that, they use big data analytics and the other factors for update the system behavior on analyzing, improve the analytics speed and reduce complexity to get the more attention the business area.

In conclude, it can be definitely stated that, the total big data term cannot be expressed in word limitations. If you really like to learn more about it, please go through its WiKi page (https://en.wikipedia.org/wiki/Big_data).

Beside this, if you find out something interesting in Hadoop, you can learn more about it by yourself by a complete visit on https://www.tutorialspoint.com/hadoop/index.htm.

For more and more further information about Big Data terms, the following links will be extremely benefited to you.