Question

1. Explain and describe the three types of diverse data sources.
2. Explain what the challenges to data with a high valence are.
3. Provide an explanation of the veracity of big data.
4. List and explain the challenges with big data that has a high volume.
5. List and explain the steps required for data analysis.

Answer 1

The three types of diverse data resources are

1. Machine Data : it is the digital information that are created by the activityof computers, mobiles, embeded system and other networked devices.These type of data become prelevant as these uses technologis like RFID( Radio frequency Identification) and telematics advanced.These thype of data gained more attention due to the use o internet things and other big management technologies has grown.

Call detail records,, Sensor data, applications & Server and business process logs are the examples of machine data.Other examples of application of machine data are monitoring oil and gas pipelines,Forecasting systems that take data from satelites and weather stations to help to predict weather in small geographical area.

2.Organisational Data: These are the data that provide the information about the organisation like there internal structure and process as well as there as their behavior as corporate in different social and economic context.Firm and enterprises data are the mainlyor frequently used organisational data but now a days there is also intrest growing towards the data on schools, universities and hospitals in economic and social science research.

3.People Data: People data can be defined as datasets describing people in the organisation. People data chages its structure, with the new dimensions being added.People datasets are prepared and stored on mix of systems, including many in excel.People datasets often edited by either adding or deleting with the change or comments which become part of datasets( example-Manager scoring of performance and notes by employee performance).People datasets often have high percentage of gaps and errors.People datasets are usually smaller ranging from 100 to 100000 rows.