Big Data assignment help

Big Data Define as:

1. Big Data is similar to small data but bigger in size.
2. Lots of data (Terabytes or petabytes)
3. Big data is the term for a collection of data.
4. Volume (click stream, active passive sensor, log, event, printed corpus, speech, social media, traditional)
5. Varity (Unstructures, semi structured, structured)
6. Veracity  (Untrusted, uncleansed)
7. Velocity(speed of generation, rate of analysis)

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Uses of Big data for analytics

Big data is always in form of large volume raw data acquired from number of medium. Such data is meaningless, unless it is studying analyzing and converting to meaningful result by the Data Scientist or analyst, is called big data analytics. Below are some of the uses of big data analytics:

1. Business Development activity

Big Data analysis is very useful in the business world. Companies are widely using Big Data analytical software and spending more and more into it for making the business strategy, marketing plans. Companies are creating the dashboards for specific data and making it live for daily activity. It is very useful before launching any new product in any sector and to improvise any product.  To get best out of data you need good understanding of business, customer demand, product and industry trend. Even small scale industries are using the Big Data Assignment Help services from service providers for relevant data. Now its become industry need to use the Big data for analysis if wanted to sustain in business. 

Example of industries that uses big data are: healthcare & research, Telecom, banking and financial service, fmcg etc.

2. Development of individuals 

Big data is not only used in industries and companies but it is also used by many organizations who works for the development of individual. Such organization collects individual’s data such as health & medical data, habits data, other expenditure, traveling, financial. By using these data they offer the customized solutions as service to individuals such as health planning, diet planner, wealth management, and expenditure planning etc for self-development.   

3. Improvement in Research and health care

Research is always required large information. Big data used in research activity in every sector. Healthcare is one of first and prime users of Big Data and its tools. A large number of data is generated in healthcare research sectors and shared to many other common platforms. Such data used to set a new milestone in human development by studying the disease, treatment, molecule etc. 

4. Social security and Crime Control

Some private and government are tied to develop the software system to control, monitor and prediction of crime in a calculative and logical manner which is a kind of Big data examples.Most of the government agencies collects information of people within or outside the nation which is used to monitor activities of criminals and their crimes. These data are used in a manner to reduce the crime in society and improve social security. 

5. To development public services by government

Government departments, public service sectors and Municipal Corporations are the best example for using Big Data analytical to development planning and improve the government facilities for public. Road, traffic, public transport system can be improved by using Big data analysis. Even the navigation system and google map are the one of the example of Big data systems, which is collection of large size of image and information that are used to navigate any place in the globe. 

Many Sensors are installed in different places to monitor and recording the weather and environment data, which is huge in size and further helps to government with the trend data and planning for future actions.

The Following are Characteristics of Big Data:

1) Volume: The data stored is collected from several of sources; like the business organizations, sectorial company, government, public data, media, machine, social networking and many more. Hence the volume is considerably large for database software to store such.

2) Velocity: The speed or velocity of big data is exceptionally fast.

3) Variety: The data that is stored can be in variable format. It can be in the form of text, diagram, graph audio etc.

Big Data Techniques:

1. Database (Colunmar, hBase, NoSQL, Query, Structure DB, Unstructured DB)
2. Data Set (Data Model, Data placement, Data distribution, Data replacement, Data integration, synchronous asynchrous data)
3. Algorithm (Scheduling, mining, map reduce, supervise learning, un-supervise learning)
4. IDE tools (statistical, analytics, visualization, simulators/predictors)
5. Hadoop based platform (DFS, YARN, Hive, Scaling, Data node, Name node, deploying)
6. File system (google file system, in-memory file system, optimization distributed system, scalable file system, parallel virtual file system)
7. Computing (parallelized computing, streams computing, cloud/grid computing, graphics computing, distributed computing, batch computing)
8. Management (cloud managing, resource managing, managing data placement, Ms management, Cluster management)

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